Job Description Company Description TechSur Solutions is a digital services company whose mission is to enable digital transformation for our customers to improve quality and efficiency. Based in the DC metropolitan area, TechSur specializes in advanced cloud services, modernization for both IT structures and applications, leveraging Agile development, and Data Analytics. Since we were formed in August of 2016, we have supported multiple impactful and exciting government programs. Job Description TechSur is seeking a Cloud Network Engineer to design and run the network that connects a federal customer's private cloud, data centers, and four public cloud providers. You will build hub-and-spoke topologies, dedicated cloud interconnects, and firewall policies that put Zero Trust principles into practice across AWS, Azure, Google Cloud, and Oracle Cloud. You will work with cloud engineers, security specialists, and customer network teams to integrate cloud networks with the customer's enterprise network and WAN. You will then keep that connectivity secure, observable, and resilient in production. Key Responsibilities Design and implement hub-and-spoke network architectures across AWS, Azure, GCP, and OCI, integrated with the customer's WAN and DNS services. Provision and manage dedicated connections and VPNs: AWS Direct Connect, Azure ExpressRoute, Google Cloud Interconnect, OCI FastConnect, and IPsec site-to-site VPN. Configure BGP routing, route tables, transit gateways, and failover between on-premises data centers and cloud regions. Create and maintain firewall policies, security groups, and network segmentation for production, integration, development, and sandbox environments. Implement Zero Trust network controls (micro-segmentation, private endpoints, identity-aware access) aligned with NIST SP 800-207 and customer security standards. Build network configurations as code with Terraform and track changes through ServiceNow change management. Monitor network performance and flows with CSP-native tools (VPC Flow Logs, Network Watcher, Network Intelligence Center, OCI Network Path Analyzer) and forward events to Splunk. Troubleshoot connectivity, latency, and DNS issues and support incident response as part of 24/7 operations. Document network designs, runbooks, and diagrams, and provide evidence for ATO packages. Qualifications Required Qualifications Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field. At least 5 years of network engineering experience, including cloud networking in at least one major cloud provider. Hands-on experience creating and managing firewall policies in cloud-native and/or next-generation firewalls. Experience provisioning dedicated cloud connections (Direct Connect, ExpressRoute, Cloud Interconnect, or FastConnect) and IPsec VPNs. Strong working knowledge of BGP, TCP/IP, subnetting, routing, load balancing, and DNS. Experience implementing Zero Trust network architecture or segmentation. Ability to obtain and maintain the background investigation required by the federal customer. Preferred Qualifications Cisco CCNP Enterprise or CCNP Security, or Palo Alto Networks PCNSE. AWS Certified Advanced Networking - Specialty, Microsoft Azure Network Engineer Associate (AZ-700), or Google Professional Cloud Network Engineer. Networking experience across more than one of AWS, Azure, GCP, and OCI. Experience with Terraform or Ansible for network automation. Experience with multi-cloud network or Zero Trust platforms (e.g., Aviatrix, Zscaler, Palo Alto Prisma Access). Experience in federal environments and with NIST SP 800-53 network controls. Prior support of a civilian federal agency.
11/14/2026
Full time
Job Description Company Description TechSur Solutions is a digital services company whose mission is to enable digital transformation for our customers to improve quality and efficiency. Based in the DC metropolitan area, TechSur specializes in advanced cloud services, modernization for both IT structures and applications, leveraging Agile development, and Data Analytics. Since we were formed in August of 2016, we have supported multiple impactful and exciting government programs. Job Description TechSur is seeking a Cloud Network Engineer to design and run the network that connects a federal customer's private cloud, data centers, and four public cloud providers. You will build hub-and-spoke topologies, dedicated cloud interconnects, and firewall policies that put Zero Trust principles into practice across AWS, Azure, Google Cloud, and Oracle Cloud. You will work with cloud engineers, security specialists, and customer network teams to integrate cloud networks with the customer's enterprise network and WAN. You will then keep that connectivity secure, observable, and resilient in production. Key Responsibilities Design and implement hub-and-spoke network architectures across AWS, Azure, GCP, and OCI, integrated with the customer's WAN and DNS services. Provision and manage dedicated connections and VPNs: AWS Direct Connect, Azure ExpressRoute, Google Cloud Interconnect, OCI FastConnect, and IPsec site-to-site VPN. Configure BGP routing, route tables, transit gateways, and failover between on-premises data centers and cloud regions. Create and maintain firewall policies, security groups, and network segmentation for production, integration, development, and sandbox environments. Implement Zero Trust network controls (micro-segmentation, private endpoints, identity-aware access) aligned with NIST SP 800-207 and customer security standards. Build network configurations as code with Terraform and track changes through ServiceNow change management. Monitor network performance and flows with CSP-native tools (VPC Flow Logs, Network Watcher, Network Intelligence Center, OCI Network Path Analyzer) and forward events to Splunk. Troubleshoot connectivity, latency, and DNS issues and support incident response as part of 24/7 operations. Document network designs, runbooks, and diagrams, and provide evidence for ATO packages. Qualifications Required Qualifications Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field. At least 5 years of network engineering experience, including cloud networking in at least one major cloud provider. Hands-on experience creating and managing firewall policies in cloud-native and/or next-generation firewalls. Experience provisioning dedicated cloud connections (Direct Connect, ExpressRoute, Cloud Interconnect, or FastConnect) and IPsec VPNs. Strong working knowledge of BGP, TCP/IP, subnetting, routing, load balancing, and DNS. Experience implementing Zero Trust network architecture or segmentation. Ability to obtain and maintain the background investigation required by the federal customer. Preferred Qualifications Cisco CCNP Enterprise or CCNP Security, or Palo Alto Networks PCNSE. AWS Certified Advanced Networking - Specialty, Microsoft Azure Network Engineer Associate (AZ-700), or Google Professional Cloud Network Engineer. Networking experience across more than one of AWS, Azure, GCP, and OCI. Experience with Terraform or Ansible for network automation. Experience with multi-cloud network or Zero Trust platforms (e.g., Aviatrix, Zscaler, Palo Alto Prisma Access). Experience in federal environments and with NIST SP 800-53 network controls. Prior support of a civilian federal agency.
Job Description Job Summary Neutrino Advisory is looking for a Senior Analytics Engineer to help build modern, scalable, and trusted data foundations that enable organizations to make better business decisions. In this role, you will design, build, and maintain transformation and semantic layers that convert raw data from enterprise platforms into governed, well-tested, documented, and business-ready datasets and metrics. You will play a key role in enabling both centralized and self-service analytics, ensuring that analysts, business stakeholders, and AI-enabled tools can access and generate trustworthy insights from enterprise data. The ideal candidate brings strong software engineering discipline to analytics development, including version control, automated testing, code reviews, and continuous integration and deployment. You will work closely with business stakeholders, data engineers, BI developers, and technology teams to establish best practices and deliver high-quality data products. This is a hands-on senior-level role with opportunities to influence architecture, establish engineering standards, mentor team members, and contribute to Neutrino's growing Data & Analytics practice. Key Responsibilities • Design, develop, and maintain dbt models on Microsoft Fabric, transforming raw source data into clean, well-documented staging, intermediate, and mart layers using consistent modeling standards and naming conventions. • Design and co-own Power BI semantic models, including certified datasets, shared measures, and row-level security, ensuring consistent metric definitions across reports, dashboards, and self-service analytics. • Establish and implement data quality standards through dbt tests, source freshness checks, data contracts, monitoring, and alerting mechanisms. • Implement software engineering best practices for analytics development, including Git-based workflows, pull request reviews, automated CI/CD for dbt and Fabric deployments, and environment management across development, testing, and production. • Collaborate with business stakeholders, finance, operations, and technology teams to translate business requirements into reliable data models, metrics, and analytical solutions. • Establish clear documentation for data models, metrics, business definitions, and data lineage to enable analysts, business users, and AI-powered tools to discover and confidently use enterprise data. • Develop and maintain a catalog of certified datasets, business metrics, and data ownership. • Optimize data transformation pipelines and semantic models for performance, scalability, and cost through incremental loading, partitioning, and efficient query design. • Apply appropriate data access controls, privacy protections, security standards, and auditability requirements in collaboration with information security and compliance teams. • Review technical deliverables, mentor junior analysts and engineers, and promote best practices in analytics engineering and data modeling. • Contribute to the development of reusable templates, technical standards, frameworks, and onboarding documentation. • Evaluate emerging tools, technologies, and architectural approaches to continuously improve the data and analytics ecosystem. • Troubleshoot complex data and pipeline issues, conduct root cause analysis, and communicate resolutions and business impact effectively to technical and non-technical stakeholders. Required Knowledge, Skills & Qualifications • Bachelor's degree in Computer Science, Engineering, Data Science, Statistics, Information Systems, or a related field, or equivalent practical experience. • 6+ years of experience in Analytics Engineering, Data Engineering, or Business Intelligence development, with demonstrated experience delivering production-grade data models. • Advanced SQL skills, including query optimization, dimensional modeling, fact and dimension tables, and slowly changing dimensions (SCD). • Hands-on experience with dbt in production environments, including modular model development, testing, documentation, macros, incremental models, and deployment practices. • Experience with Microsoft Fabric, including Lakehouse, Warehouse, OneLake, Data Factory, and data pipelines, or comparable cloud data platforms such as Snowflake, Databricks, or BigQuery. • Strong Power BI experience, including semantic model design, DAX, row-level security, and governance of shared datasets. • Familiarity with AI-enabled analytics tools and the data architecture, governed metrics, metadata, and documentation required to support reliable AI-driven insights. • Working knowledge of Git, pull request workflows, and CI/CD pipelines using tools such as Azure DevOps or GitHub Actions. • Proficiency in Python for scripting, automation, and data validation. • Experience implementing data quality, testing, monitoring, and observability practices. • Ability to translate complex or ambiguous business requirements into clear technical designs and communicate architectural decisions and trade-offs effectively. • Strong written and verbal communication skills, with the ability to collaborate across technical and business teams. • Understanding of data privacy, security, governance, and compliance principles. Preferred Qualifications • Experience in financial services, wealth management, banking, healthcare, or other regulated industries. • Familiarity with CRM, portfolio accounting, financial reporting, or custodial data. • Experience building enterprise-scale analytics platforms using Microsoft Azure and Microsoft Fabric. • Exposure to modern data architecture patterns, including medallion architecture, data lakes, lakehouses, and enterprise data warehouses. • Experience working with AI-powered analytics, natural language querying, and enterprise data governance for AI adoption. What We Offer • Opportunity to work on modern data engineering and analytics transformation initiatives. • Exposure to enterprise-scale implementations across Microsoft Fabric, Power BI, Azure, and modern data platforms. • Opportunity to work with emerging AI technologies and help shape the future of enterprise analytics. • A collaborative, technology-driven environment with opportunities for continuous learning and professional growth. • The opportunity to take ownership, influence technical direction, and contribute to building Neutrino's Data & Analytics practice. About Neutrino Advisory Neutrino Advisory is a Digital Strategy, Advisory & Marketing Technology firm helping organizations navigate digital transformation through data, cloud, CRM, enterprise platforms, and applied AI. We combine business strategy with technology expertise to build scalable solutions that deliver measurable business outcomes. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform crucial job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
11/14/2026
Full time
Job Description Job Summary Neutrino Advisory is looking for a Senior Analytics Engineer to help build modern, scalable, and trusted data foundations that enable organizations to make better business decisions. In this role, you will design, build, and maintain transformation and semantic layers that convert raw data from enterprise platforms into governed, well-tested, documented, and business-ready datasets and metrics. You will play a key role in enabling both centralized and self-service analytics, ensuring that analysts, business stakeholders, and AI-enabled tools can access and generate trustworthy insights from enterprise data. The ideal candidate brings strong software engineering discipline to analytics development, including version control, automated testing, code reviews, and continuous integration and deployment. You will work closely with business stakeholders, data engineers, BI developers, and technology teams to establish best practices and deliver high-quality data products. This is a hands-on senior-level role with opportunities to influence architecture, establish engineering standards, mentor team members, and contribute to Neutrino's growing Data & Analytics practice. Key Responsibilities • Design, develop, and maintain dbt models on Microsoft Fabric, transforming raw source data into clean, well-documented staging, intermediate, and mart layers using consistent modeling standards and naming conventions. • Design and co-own Power BI semantic models, including certified datasets, shared measures, and row-level security, ensuring consistent metric definitions across reports, dashboards, and self-service analytics. • Establish and implement data quality standards through dbt tests, source freshness checks, data contracts, monitoring, and alerting mechanisms. • Implement software engineering best practices for analytics development, including Git-based workflows, pull request reviews, automated CI/CD for dbt and Fabric deployments, and environment management across development, testing, and production. • Collaborate with business stakeholders, finance, operations, and technology teams to translate business requirements into reliable data models, metrics, and analytical solutions. • Establish clear documentation for data models, metrics, business definitions, and data lineage to enable analysts, business users, and AI-powered tools to discover and confidently use enterprise data. • Develop and maintain a catalog of certified datasets, business metrics, and data ownership. • Optimize data transformation pipelines and semantic models for performance, scalability, and cost through incremental loading, partitioning, and efficient query design. • Apply appropriate data access controls, privacy protections, security standards, and auditability requirements in collaboration with information security and compliance teams. • Review technical deliverables, mentor junior analysts and engineers, and promote best practices in analytics engineering and data modeling. • Contribute to the development of reusable templates, technical standards, frameworks, and onboarding documentation. • Evaluate emerging tools, technologies, and architectural approaches to continuously improve the data and analytics ecosystem. • Troubleshoot complex data and pipeline issues, conduct root cause analysis, and communicate resolutions and business impact effectively to technical and non-technical stakeholders. Required Knowledge, Skills & Qualifications • Bachelor's degree in Computer Science, Engineering, Data Science, Statistics, Information Systems, or a related field, or equivalent practical experience. • 6+ years of experience in Analytics Engineering, Data Engineering, or Business Intelligence development, with demonstrated experience delivering production-grade data models. • Advanced SQL skills, including query optimization, dimensional modeling, fact and dimension tables, and slowly changing dimensions (SCD). • Hands-on experience with dbt in production environments, including modular model development, testing, documentation, macros, incremental models, and deployment practices. • Experience with Microsoft Fabric, including Lakehouse, Warehouse, OneLake, Data Factory, and data pipelines, or comparable cloud data platforms such as Snowflake, Databricks, or BigQuery. • Strong Power BI experience, including semantic model design, DAX, row-level security, and governance of shared datasets. • Familiarity with AI-enabled analytics tools and the data architecture, governed metrics, metadata, and documentation required to support reliable AI-driven insights. • Working knowledge of Git, pull request workflows, and CI/CD pipelines using tools such as Azure DevOps or GitHub Actions. • Proficiency in Python for scripting, automation, and data validation. • Experience implementing data quality, testing, monitoring, and observability practices. • Ability to translate complex or ambiguous business requirements into clear technical designs and communicate architectural decisions and trade-offs effectively. • Strong written and verbal communication skills, with the ability to collaborate across technical and business teams. • Understanding of data privacy, security, governance, and compliance principles. Preferred Qualifications • Experience in financial services, wealth management, banking, healthcare, or other regulated industries. • Familiarity with CRM, portfolio accounting, financial reporting, or custodial data. • Experience building enterprise-scale analytics platforms using Microsoft Azure and Microsoft Fabric. • Exposure to modern data architecture patterns, including medallion architecture, data lakes, lakehouses, and enterprise data warehouses. • Experience working with AI-powered analytics, natural language querying, and enterprise data governance for AI adoption. What We Offer • Opportunity to work on modern data engineering and analytics transformation initiatives. • Exposure to enterprise-scale implementations across Microsoft Fabric, Power BI, Azure, and modern data platforms. • Opportunity to work with emerging AI technologies and help shape the future of enterprise analytics. • A collaborative, technology-driven environment with opportunities for continuous learning and professional growth. • The opportunity to take ownership, influence technical direction, and contribute to building Neutrino's Data & Analytics practice. About Neutrino Advisory Neutrino Advisory is a Digital Strategy, Advisory & Marketing Technology firm helping organizations navigate digital transformation through data, cloud, CRM, enterprise platforms, and applied AI. We combine business strategy with technology expertise to build scalable solutions that deliver measurable business outcomes. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform crucial job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Job Description Job Description: Agentic AI Engineer Experience: (8-10) + Years Location: Fort Mill, SC Annual Salary: $120K Per Annum Job Summary We are seeking an experienced Agentic AI Engineer with 10+ years of experience in software engineering, AI/ML, and enterprise application development to design, develop, and deploy intelligent AI agents for wealth management applications. The ideal candidate will have strong expertise in Python, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), multi-agent architectures, and enterprise AI integration. This role requires hands-on experience building production-grade AI solutions that can reason, plan, use tools, retrieve information, and execute business workflows with appropriate human oversight. Experience in wealth management, financial services, investment management, portfolio analytics, or financial advisory platforms is highly preferred. Key Responsibilities Design, develop, and deploy production-ready Agentic AI solutions for wealth management and financial services applications. Build autonomous and semi-autonomous AI agents capable of planning tasks, reasoning, invoking tools, and executing multi-step workflows. Develop multi-agent systems using frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, or equivalent technologies. Design and implement LLM-powered applications using models from OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, or similar platforms. Develop and optimize RAG pipelines, including document ingestion, chunking, embeddings, semantic search, reranking, and context retrieval. Integrate AI agents with enterprise systems, REST APIs, databases, knowledge repositories, and financial data platforms. Implement tool/function calling, structured outputs, workflow orchestration, memory management, and stateful agent execution. Build solutions for wealth management use cases, including portfolio research, advisor assistance, investment document analysis, client servicing, financial insights, and knowledge retrieval. Implement responsible AI practices, including guardrails, prompt-injection protection, access controls, PII protection, auditability, and human-in-the-loop approvals. Evaluate AI solutions for accuracy, groundedness, latency, reliability, cost, and business effectiveness. Deploy, monitor, and maintain AI applications using CI/CD, containerization, cloud services, logging, and observability tools. Collaborate with product managers, architects, data engineers, business analysts, and compliance teams to translate business requirements into scalable AI solutions. Mentor engineers, establish engineering best practices, and provide technical leadership across AI initiatives. Required Technical Skills 1. Programming and Software Engineering Strong hands-on experience with Python and object-oriented programming. Expertise in REST APIs, microservices, asynchronous processing, and enterprise application integration. Proficiency with Git, automated testing, debugging, and software engineering best practices. 2. Agentic AI and LLMs Hands-on experience designing and implementing AI agents and multi-agent workflows. Strong understanding of LLM architecture, prompt engineering, context management, and model selection. Experience with agent orchestration frameworks such as LangGraph, LangChain, Semantic Kernel, or AutoGen. Experience implementing tool calling, function calling, planning, state management, retries, and error handling. Understanding of agent autonomy, workflow determinism, and human-in-the-loop controls. 3. RAG and Knowledge Retrieval Experience building enterprise-grade RAG applications and document intelligence solutions. Knowledge of embedding models, vector search, hybrid search, reranking, and retrieval optimization. Experience with vector databases such as Pinecone, Weaviate, Milvus, Chroma, or FAISS. Familiarity with Elasticsearch/OpenSearch and traditional relational or NoSQL databases. 4. Cloud and AI Deployment Experience deploying AI applications on AWS, Azure, or GCP. Familiarity with services such as AWS Bedrock, Azure OpenAI, or equivalent managed AI platforms. Experience with Docker, Kubernetes, CI/CD pipelines, and production monitoring. Understanding of scalability, performance optimization, model serving, and LLM cost management. 5. AI Quality, Security, and Governance Experience implementing LLM evaluation, hallucination mitigation, grounded responses, and AI guardrails. Knowledge of responsible AI, data privacy, secure API integration, and enterprise access controls. Understanding of observability, tracing, prompt/version management, and production incident troubleshooting. Wealth Management Domain Experience Experience working in wealth management, financial services, investment management, banking, or fintech. Understanding of portfolio management, asset allocation, investment research, financial advisors, and client servicing workflows. Familiarity with financial statements, investment reports, market data, and financial research documents. Ability to develop AI solutions that support advisors and operations teams while maintaining data confidentiality, traceability, and compliance requirements. Experience with regulated financial environments and human approval workflows for sensitive or consequential actions is a strong plus. Preferred Qualifications Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related field. 10+ years of overall software engineering experience, with substantial hands-on experience in AI/ML, LLM applications, or Generative AI. Demonstrated experience delivering AI solutions from proof of concept through production deployment. Strong analytical, problem-solving, communication, and stakeholder-management skills. Experience leading technical design discussions and mentoring engineering teams. Important: Candidates should demonstrate hands-on implementation of production-grade Agentic AI solutions, not just chatbot development, prompt engineering, or proof-of-concept projects.
11/14/2026
Full time
Job Description Job Description: Agentic AI Engineer Experience: (8-10) + Years Location: Fort Mill, SC Annual Salary: $120K Per Annum Job Summary We are seeking an experienced Agentic AI Engineer with 10+ years of experience in software engineering, AI/ML, and enterprise application development to design, develop, and deploy intelligent AI agents for wealth management applications. The ideal candidate will have strong expertise in Python, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), multi-agent architectures, and enterprise AI integration. This role requires hands-on experience building production-grade AI solutions that can reason, plan, use tools, retrieve information, and execute business workflows with appropriate human oversight. Experience in wealth management, financial services, investment management, portfolio analytics, or financial advisory platforms is highly preferred. Key Responsibilities Design, develop, and deploy production-ready Agentic AI solutions for wealth management and financial services applications. Build autonomous and semi-autonomous AI agents capable of planning tasks, reasoning, invoking tools, and executing multi-step workflows. Develop multi-agent systems using frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, or equivalent technologies. Design and implement LLM-powered applications using models from OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, or similar platforms. Develop and optimize RAG pipelines, including document ingestion, chunking, embeddings, semantic search, reranking, and context retrieval. Integrate AI agents with enterprise systems, REST APIs, databases, knowledge repositories, and financial data platforms. Implement tool/function calling, structured outputs, workflow orchestration, memory management, and stateful agent execution. Build solutions for wealth management use cases, including portfolio research, advisor assistance, investment document analysis, client servicing, financial insights, and knowledge retrieval. Implement responsible AI practices, including guardrails, prompt-injection protection, access controls, PII protection, auditability, and human-in-the-loop approvals. Evaluate AI solutions for accuracy, groundedness, latency, reliability, cost, and business effectiveness. Deploy, monitor, and maintain AI applications using CI/CD, containerization, cloud services, logging, and observability tools. Collaborate with product managers, architects, data engineers, business analysts, and compliance teams to translate business requirements into scalable AI solutions. Mentor engineers, establish engineering best practices, and provide technical leadership across AI initiatives. Required Technical Skills 1. Programming and Software Engineering Strong hands-on experience with Python and object-oriented programming. Expertise in REST APIs, microservices, asynchronous processing, and enterprise application integration. Proficiency with Git, automated testing, debugging, and software engineering best practices. 2. Agentic AI and LLMs Hands-on experience designing and implementing AI agents and multi-agent workflows. Strong understanding of LLM architecture, prompt engineering, context management, and model selection. Experience with agent orchestration frameworks such as LangGraph, LangChain, Semantic Kernel, or AutoGen. Experience implementing tool calling, function calling, planning, state management, retries, and error handling. Understanding of agent autonomy, workflow determinism, and human-in-the-loop controls. 3. RAG and Knowledge Retrieval Experience building enterprise-grade RAG applications and document intelligence solutions. Knowledge of embedding models, vector search, hybrid search, reranking, and retrieval optimization. Experience with vector databases such as Pinecone, Weaviate, Milvus, Chroma, or FAISS. Familiarity with Elasticsearch/OpenSearch and traditional relational or NoSQL databases. 4. Cloud and AI Deployment Experience deploying AI applications on AWS, Azure, or GCP. Familiarity with services such as AWS Bedrock, Azure OpenAI, or equivalent managed AI platforms. Experience with Docker, Kubernetes, CI/CD pipelines, and production monitoring. Understanding of scalability, performance optimization, model serving, and LLM cost management. 5. AI Quality, Security, and Governance Experience implementing LLM evaluation, hallucination mitigation, grounded responses, and AI guardrails. Knowledge of responsible AI, data privacy, secure API integration, and enterprise access controls. Understanding of observability, tracing, prompt/version management, and production incident troubleshooting. Wealth Management Domain Experience Experience working in wealth management, financial services, investment management, banking, or fintech. Understanding of portfolio management, asset allocation, investment research, financial advisors, and client servicing workflows. Familiarity with financial statements, investment reports, market data, and financial research documents. Ability to develop AI solutions that support advisors and operations teams while maintaining data confidentiality, traceability, and compliance requirements. Experience with regulated financial environments and human approval workflows for sensitive or consequential actions is a strong plus. Preferred Qualifications Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related field. 10+ years of overall software engineering experience, with substantial hands-on experience in AI/ML, LLM applications, or Generative AI. Demonstrated experience delivering AI solutions from proof of concept through production deployment. Strong analytical, problem-solving, communication, and stakeholder-management skills. Experience leading technical design discussions and mentoring engineering teams. Important: Candidates should demonstrate hands-on implementation of production-grade Agentic AI solutions, not just chatbot development, prompt engineering, or proof-of-concept projects.
Job Description Company Description TechSur Solutions is a digital services company whose mission is to enable digital transformation for our customers to improve quality and efficiency. Based in the DC metropolitan area, TechSur specializes in advanced cloud services, modernization for both IT structures and applications, leveraging Agile development, and Data Analytics. Since we were formed in August of 2016, we have supported multiple impactful and exciting government programs. Job Description TechSur is seeking a Senior Cloud Engineer who is fluent in both Google Cloud Platform (GCP) and Oracle Cloud Infrastructure (OCI). You will be the program's go-to engineer for both platforms, splitting your time roughly evenly between them. You will build GCP and OCI foundations that match the same enterprise standards the team applies on AWS and Azure. On GCP, you will establish the organization and folder hierarchy, Shared VPC networking, and organization policies. On OCI, you will build tenancies, compartments, VCN/DRG networking, and Security Zones. On both, you will automate with Infrastructure-as-Code, integrate with the customer's identity, monitoring, and service management tools, and support the platforms in production. Key Responsibilities Design and deploy GCP landing zones: resource hierarchy (organization, folders, projects), Shared VPC hub-and-spoke networking, Cloud Interconnect or HA VPN, and Cloud DNS. Design and deploy OCI landing zones: tenancy and compartment structure, VCN and Dynamic Routing Gateway (DRG) hub-and-spoke networking, FastConnect or IPsec VPN, and DNS. Build and maintain Terraform modules (including OCI Resource Manager) and GitOps workflows for production, integration, development, and sandbox environments on both platforms. Configure IAM and federation with the customer's enterprise identity provider using SAML 2.0 and OIDC, aligned with Zero Trust principles. Enforce guardrails with GCP Organization Policy and Security Command Center, and with OCI Cloud Guard and Security Zones, against NIST SP 800-53 Rev 5 and customer security standards. Apply the enterprise tagging and labeling strategy for asset management and chargeback/showback using GCP Billing Reports and OCI Cost Analysis. Monitor environments with Google Cloud Operations Suite and OCI Monitoring, integrated with Datadog, Splunk, and ServiceNow. Perform patching, routine maintenance, capacity planning, and rightsizing; troubleshoot and resolve incidents as part of 24/7 operations support. Design and test high availability, backup, and disaster recovery on both platforms. Write runbooks and SOPs, supply ATO evidence, and transfer knowledge to customer operations staff. Qualifications Required Qualifications Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field. At least 9 years of experience deploying and configuring cloud environments. Hands-on production experience with both Google Cloud Platform and Oracle Cloud Infrastructure. Production experience with Infrastructure-as-Code using Terraform on GCP and OCI. Experience with cloud network design, including private connectivity (Cloud Interconnect, FastConnect, or IPsec VPN), routing, and DNS. Experience implementing IAM and single sign-on federation (SAML 2.0/OIDC). Working knowledge of NIST SP 800-53 security controls in a federal environment. Ability to obtain and maintain the background investigation required by the federal customer. Preferred Qualifications Google Cloud Certified Professional Cloud Architect or Professional Cloud Security Engineer. Oracle Cloud Infrastructure Architect Professional or OCI Multicloud Architect Professional. Experience hosting Oracle Database workloads on OCI (Autonomous Database, Exadata Cloud Service, Base Database Service). Experience with GCP Assured Workloads, OCI US Government regions, or FedRAMP Moderate/High environments. Experience with GCP Cloud Build/Cloud Deploy or OCI DevOps pipelines. Working knowledge of AWS or Azure. Prior support of a civilian federal agency.
11/14/2026
Full time
Job Description Company Description TechSur Solutions is a digital services company whose mission is to enable digital transformation for our customers to improve quality and efficiency. Based in the DC metropolitan area, TechSur specializes in advanced cloud services, modernization for both IT structures and applications, leveraging Agile development, and Data Analytics. Since we were formed in August of 2016, we have supported multiple impactful and exciting government programs. Job Description TechSur is seeking a Senior Cloud Engineer who is fluent in both Google Cloud Platform (GCP) and Oracle Cloud Infrastructure (OCI). You will be the program's go-to engineer for both platforms, splitting your time roughly evenly between them. You will build GCP and OCI foundations that match the same enterprise standards the team applies on AWS and Azure. On GCP, you will establish the organization and folder hierarchy, Shared VPC networking, and organization policies. On OCI, you will build tenancies, compartments, VCN/DRG networking, and Security Zones. On both, you will automate with Infrastructure-as-Code, integrate with the customer's identity, monitoring, and service management tools, and support the platforms in production. Key Responsibilities Design and deploy GCP landing zones: resource hierarchy (organization, folders, projects), Shared VPC hub-and-spoke networking, Cloud Interconnect or HA VPN, and Cloud DNS. Design and deploy OCI landing zones: tenancy and compartment structure, VCN and Dynamic Routing Gateway (DRG) hub-and-spoke networking, FastConnect or IPsec VPN, and DNS. Build and maintain Terraform modules (including OCI Resource Manager) and GitOps workflows for production, integration, development, and sandbox environments on both platforms. Configure IAM and federation with the customer's enterprise identity provider using SAML 2.0 and OIDC, aligned with Zero Trust principles. Enforce guardrails with GCP Organization Policy and Security Command Center, and with OCI Cloud Guard and Security Zones, against NIST SP 800-53 Rev 5 and customer security standards. Apply the enterprise tagging and labeling strategy for asset management and chargeback/showback using GCP Billing Reports and OCI Cost Analysis. Monitor environments with Google Cloud Operations Suite and OCI Monitoring, integrated with Datadog, Splunk, and ServiceNow. Perform patching, routine maintenance, capacity planning, and rightsizing; troubleshoot and resolve incidents as part of 24/7 operations support. Design and test high availability, backup, and disaster recovery on both platforms. Write runbooks and SOPs, supply ATO evidence, and transfer knowledge to customer operations staff. Qualifications Required Qualifications Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field. At least 9 years of experience deploying and configuring cloud environments. Hands-on production experience with both Google Cloud Platform and Oracle Cloud Infrastructure. Production experience with Infrastructure-as-Code using Terraform on GCP and OCI. Experience with cloud network design, including private connectivity (Cloud Interconnect, FastConnect, or IPsec VPN), routing, and DNS. Experience implementing IAM and single sign-on federation (SAML 2.0/OIDC). Working knowledge of NIST SP 800-53 security controls in a federal environment. Ability to obtain and maintain the background investigation required by the federal customer. Preferred Qualifications Google Cloud Certified Professional Cloud Architect or Professional Cloud Security Engineer. Oracle Cloud Infrastructure Architect Professional or OCI Multicloud Architect Professional. Experience hosting Oracle Database workloads on OCI (Autonomous Database, Exadata Cloud Service, Base Database Service). Experience with GCP Assured Workloads, OCI US Government regions, or FedRAMP Moderate/High environments. Experience with GCP Cloud Build/Cloud Deploy or OCI DevOps pipelines. Working knowledge of AWS or Azure. Prior support of a civilian federal agency.
Job Description C&F is a technology services company providing innovative solutions in Data Management, Big Data, Advanced Analytics and Compliance. With a highly integrated team of 400+ experts, for over 20 years C&F has been delivering superior engineering and premium operations to Fortune 500 companies, primarily in the Life Science industry. About Our Manufacturing Business Unit Our company is organized into unique Business Units, each delivering innovative and differentiated business technology solutions across industries. The Manufacturing Business Unit specializes in enterprise-scale manufacturing solutions that drive site- and network-level outcomes aligned to strategic objectives and KPIs. Our applications, data products, and advanced platform technologies-including AI and IoT-enable Digital Manufacturing at Scale. We primarily serve enterprise clients across Human Pharma, Animal Health, and Consumer Goods industries. Our Manufacturing Business Unit operates through three integrated functions: • Strategy & Growth - Develops differentiated offerings and industry thought leadership. • Business Consulting - Defines client-customized solutions and ensures sustained value realization. • Engineering Delivery - Delivers solution architecture, development, deployment, and sustainment. The Business Consulting function is hiring a Manager, Manufacturing Solutions Business Consultant to serve as a Product Owner and consulting lead across manufacturing digital initiatives. Position Overview The Consultant supports delivery of Digital Manufacturing initiatives by acting as a Business Analyst and/or Junior Product Owner within client engagements. This role partners closely with Managers and Senior Managers to define requirements, structure documentation, develop client-ready materials, and support Agile delivery execution. The Consultant plays a key role in translating manufacturing business needs into functional artifacts that enable engineering teams to deliver value. This is a hands-on, consulting and analytical role suited for individuals with early experience in Manufacturing OT, Manufacturing IT or technology. The role also requires a working understanding of artificial intelligence (AI), including generative AI and agentic technologies, and an interest in applying these capabilities to practical manufacturing and business challenges. Key Responsibilities Consulting & Problem Solving Support consulting engagements by analyzing manufacturing business needs, contributing to client discussions, and helping develop practical recommendations and solutions. Business Analysis & Requirements Development • Support facilitation of client workshops to gather functional and non-functional requirements. • Document business processes, current-state pain points, and future-state solution designs. • Develop structured requirements documentation, user stories, and acceptance criteria. • Assist in translating manufacturing KPIs (OEE, quality, throughput, asset performance) into measurable solution objectives. • Maintain traceability between business requirements and delivered functionality. Product & Backlog Support • Support backlog development and refinement under guidance of a Manager or Senior Manager. • Draft epics, features, and user stories aligned to defined roadmap priorities. • Participate in sprint planning, demos, and retrospectives. • Track action items, risks, and dependencies across delivery workstreams. • Assist in maintaining roadmap documentation and milestone trackers. Documentation & Presentation Development Develop high-quality client-ready materials including: Roadmap summaries Workshop outputs Business case inputs Solution overviews Executive presentation drafts: -Structure content using clear, logical storytelling and data-supported insights. -Support development of proposal materials and Statements of Work. -Ensure documentation is clear, concise, and professionally formatted. Agile & Delivery Support • Operate within Agile delivery models (Scrum, SAFe, or hybrid environments). • Support backlog grooming and sprint documentation. • Assist with tracking sprint progress and updating delivery artifacts. • Promote disciplined documentation and communication standards. Manufacturing Domain & Technical Acumen • Build working knowledge of manufacturing business processes (production execution, quality, maintenance, traceability). • Develop familiarity with manufacturing technology ecosystems • Support analysis of integration points across MES, ERP, IoT, and data platforms. AI & Agentic Solution Support • Support identification and documentation of AI-enabled use cases across manufacturing processes, knowledge workflows, decision support, and task automation. • Translate AI use cases into business requirements, process flows, user stories, acceptance criteria, test scenarios, and measurable success criteria. • Build familiarity with large language models, AI agents, retrieval-augmented generation, machine learning, and enterprise AI governance concepts. Required Qualifications • 3+ years of consulting experience in manufacturing, technology, or digital delivery environments. • Proven consulting experience supporting client discussions and helping develop practical recommendations and solutions. • Experience supporting requirements gathering and documentation. • Exposure to Agile delivery methodologies. • Strong written and verbal communication skills. • Analytical mindset with structured problem-solving capabilities. • Proficiency in presentation development tools (e.g., PowerPoint, Excel). Preferred Qualifications • Bachelor's degree • Experience in technology delivery or implementation • Experience with project management practices and project management software • Experience working with cross functional teams such as UI/UX designers, software/data engineers and end users What we offer: Competitive remuneration and various benefits: 401(k) Retirement Plan (Immediate eligibility with 100% employer match up to 4%.) Medical Insurance Maternity and Paternity Leave Long-Term Disability Bereavement leave Generous Sick Leave Internet and Phone stipend Development stipend Wellness stipend Generous Paid Time Off: 20 days in the first year, increasing to 25 days We work fully remotely but expect openness to occasional travel Company culture is rooted in respect and cooperation. You'll be working with great people, who are open to new challenges and directions. If you are tired of the proverbial corporate treadmill, come to us to rest mentally. If you've had luck with employers, we'll do our best not to buck the trend. Additional Info: Range: $100,000 - $115,000 + Bonus Location: Remote (US East Coast) Travel: 10%
11/14/2026
Full time
Job Description C&F is a technology services company providing innovative solutions in Data Management, Big Data, Advanced Analytics and Compliance. With a highly integrated team of 400+ experts, for over 20 years C&F has been delivering superior engineering and premium operations to Fortune 500 companies, primarily in the Life Science industry. About Our Manufacturing Business Unit Our company is organized into unique Business Units, each delivering innovative and differentiated business technology solutions across industries. The Manufacturing Business Unit specializes in enterprise-scale manufacturing solutions that drive site- and network-level outcomes aligned to strategic objectives and KPIs. Our applications, data products, and advanced platform technologies-including AI and IoT-enable Digital Manufacturing at Scale. We primarily serve enterprise clients across Human Pharma, Animal Health, and Consumer Goods industries. Our Manufacturing Business Unit operates through three integrated functions: • Strategy & Growth - Develops differentiated offerings and industry thought leadership. • Business Consulting - Defines client-customized solutions and ensures sustained value realization. • Engineering Delivery - Delivers solution architecture, development, deployment, and sustainment. The Business Consulting function is hiring a Manager, Manufacturing Solutions Business Consultant to serve as a Product Owner and consulting lead across manufacturing digital initiatives. Position Overview The Consultant supports delivery of Digital Manufacturing initiatives by acting as a Business Analyst and/or Junior Product Owner within client engagements. This role partners closely with Managers and Senior Managers to define requirements, structure documentation, develop client-ready materials, and support Agile delivery execution. The Consultant plays a key role in translating manufacturing business needs into functional artifacts that enable engineering teams to deliver value. This is a hands-on, consulting and analytical role suited for individuals with early experience in Manufacturing OT, Manufacturing IT or technology. The role also requires a working understanding of artificial intelligence (AI), including generative AI and agentic technologies, and an interest in applying these capabilities to practical manufacturing and business challenges. Key Responsibilities Consulting & Problem Solving Support consulting engagements by analyzing manufacturing business needs, contributing to client discussions, and helping develop practical recommendations and solutions. Business Analysis & Requirements Development • Support facilitation of client workshops to gather functional and non-functional requirements. • Document business processes, current-state pain points, and future-state solution designs. • Develop structured requirements documentation, user stories, and acceptance criteria. • Assist in translating manufacturing KPIs (OEE, quality, throughput, asset performance) into measurable solution objectives. • Maintain traceability between business requirements and delivered functionality. Product & Backlog Support • Support backlog development and refinement under guidance of a Manager or Senior Manager. • Draft epics, features, and user stories aligned to defined roadmap priorities. • Participate in sprint planning, demos, and retrospectives. • Track action items, risks, and dependencies across delivery workstreams. • Assist in maintaining roadmap documentation and milestone trackers. Documentation & Presentation Development Develop high-quality client-ready materials including: Roadmap summaries Workshop outputs Business case inputs Solution overviews Executive presentation drafts: -Structure content using clear, logical storytelling and data-supported insights. -Support development of proposal materials and Statements of Work. -Ensure documentation is clear, concise, and professionally formatted. Agile & Delivery Support • Operate within Agile delivery models (Scrum, SAFe, or hybrid environments). • Support backlog grooming and sprint documentation. • Assist with tracking sprint progress and updating delivery artifacts. • Promote disciplined documentation and communication standards. Manufacturing Domain & Technical Acumen • Build working knowledge of manufacturing business processes (production execution, quality, maintenance, traceability). • Develop familiarity with manufacturing technology ecosystems • Support analysis of integration points across MES, ERP, IoT, and data platforms. AI & Agentic Solution Support • Support identification and documentation of AI-enabled use cases across manufacturing processes, knowledge workflows, decision support, and task automation. • Translate AI use cases into business requirements, process flows, user stories, acceptance criteria, test scenarios, and measurable success criteria. • Build familiarity with large language models, AI agents, retrieval-augmented generation, machine learning, and enterprise AI governance concepts. Required Qualifications • 3+ years of consulting experience in manufacturing, technology, or digital delivery environments. • Proven consulting experience supporting client discussions and helping develop practical recommendations and solutions. • Experience supporting requirements gathering and documentation. • Exposure to Agile delivery methodologies. • Strong written and verbal communication skills. • Analytical mindset with structured problem-solving capabilities. • Proficiency in presentation development tools (e.g., PowerPoint, Excel). Preferred Qualifications • Bachelor's degree • Experience in technology delivery or implementation • Experience with project management practices and project management software • Experience working with cross functional teams such as UI/UX designers, software/data engineers and end users What we offer: Competitive remuneration and various benefits: 401(k) Retirement Plan (Immediate eligibility with 100% employer match up to 4%.) Medical Insurance Maternity and Paternity Leave Long-Term Disability Bereavement leave Generous Sick Leave Internet and Phone stipend Development stipend Wellness stipend Generous Paid Time Off: 20 days in the first year, increasing to 25 days We work fully remotely but expect openness to occasional travel Company culture is rooted in respect and cooperation. You'll be working with great people, who are open to new challenges and directions. If you are tired of the proverbial corporate treadmill, come to us to rest mentally. If you've had luck with employers, we'll do our best not to buck the trend. Additional Info: Range: $100,000 - $115,000 + Bonus Location: Remote (US East Coast) Travel: 10%
Job Description Candidate must already live in Chicago! No exceptions! Senior Full Stack Engineer Contract Position Position Overview We are seeking an experienced Senior Full Stack & Cloud-Native AI Engineer to transform an existing Data Insight proof of concept into a secure, scalable, production-ready enterprise application. The application enables users to explore reporting data, ask contextual follow-up questions, and gain actionable insights supported by verifiable source evidence. In this role, you will design and develop end-to-end application capabilities, including agentic AI workflows, full-stack user experiences, cloud-native services, and enterprise integrations. You will play a critical role in establishing the evaluation, testing, and monitoring frameworks required to ensure the accuracy, reliability, security, and continuous improvement of AI-powered functionality. The ideal candidate combines strong full-stack engineering expertise with hands-on experience developing production-grade AI applications, particularly agentic workflows, retrieval-augmented generation (RAG), and AI evaluation frameworks. Key Responsibilities Agentic AI Application Development Design, develop, and deploy production-grade agentic AI applications using large language models (LLMs), tool calling, structured outputs, and multi-step reasoning workflows. Build intelligent workflows that interpret user intent, maintain conversation context, orchestrate tools and APIs, and support human review when appropriate. Implement prompt engineering, context management, workflow orchestration, and error-handling strategies to improve application reliability and response quality. Integrate retrieval-augmented generation (RAG) capabilities to ground AI-generated responses in trusted enterprise data and source documents. F ull Stack & Cloud-Native Development Develop responsive, user-friendly web applications using Angular and modern front-end development practices. Design and implement scalable backend services and RESTful APIs using C# and .NET. Develop Python-based AI services and agent orchestration components. Integrate application services with existing enterprise reporting platforms, databases, authentication providers, and data-access systems. Build and deploy cloud-native solutions using Microsoft Azure and associated cloud services. Implement secure API integrations, asynchronous processing, and resilient service-to-service communication. AI Evaluation, Testing & Quality Engineering Own the design and implementation of comprehensive evaluation frameworks for AI-powered applications. Collaborate with healthcare domain experts and product owners to curate representative evaluation datasets and define scoring rubrics, quality metrics, and acceptance criteria. Develop automated evaluation processes to assess: Accuracy and relevance of AI-generated answers. Correctness and traceability of supporting evidence. Tool selection, execution, and workflow orchestration. Context retention and multi-turn conversation quality. End-to-end task completion and user experience. Handling of ambiguous, unsupported, and out-of-scope requests. Combine automated evaluation with human review to validate analytical accuracy and domain-specific correctness. Establish regression testing and baseline comparisons to identify quality degradation resulting from changes to models, prompts, datasets, or application code. Integrate AI evaluation suites, automated tests, and quality gates into CI/CD pipelines. Maintain version-controlled prompts, evaluation datasets, test configurations, and performance baselines. Reliability, Security & Production Operations Design resilient execution workflows incorporating timeouts, retries, cancellation, durable state management, and recovery mechanisms. Implement authentication, authorization, and data-access controls across APIs, AI agents, tools, and underlying data sources. Ensure sensitive healthcare and enterprise data is handled securely and in accordance with applicable organizational policies. Establish observability through application logging, distributed tracing, performance monitoring, and error reporting. Monitor production AI quality, response latency, operational costs, and failure rates. Analyze production feedback and failures, convert findings into reproducible test cases, and drive measurable improvements. Optimize application performance, scalability, reliability, and cloud operating costs. Data Engineering & Analytical Integrity Develop and optimize SQL queries, relational data models, and data-access services. Ensure analytical results are accurate, reproducible, and supported by traceable source data. Address data-quality challenges, including missing values, inconsistencies, numerical precision, and aggregation accuracy. Work closely with business stakeholders and healthcare domain experts to validate analytical findings and communicate uncertainty and system limitations. Required Qualifications 8+ years of professional software engineering experience delivering and supporting secure, scalable enterprise applications. Hands-on experience designing and developing agentic AI applications using LLMs, tool calling, structured outputs, prompt engineering, and multi-step workflows. Strong full-stack development experience with Angular, C#/.NET Web APIs, and Python. Practical experience building AI evaluation and quality pipelines, including evaluation datasets, scoring methodologies, automated regression testing, and human-in-the-loop validation. Demonstrated ability to use evaluation results and production feedback to improve AI application quality and reliability. Strong experience with SQL, relational database design, data modeling, and analytical data processing. Experience building and deploying cloud-native applications using Microsoft Azure. Hands-on experience with CI/CD pipelines, automated unit testing, integration testing, and end-to-end testing. Strong understanding of enterprise application security, authentication, authorization, secure API design, and data-access controls. Experience implementing observability, distributed tracing, asynchronous processing, and fault-tolerant application architectures. Strong analytical, problem-solving, communication, and collaboration skills. Ability to work independently and effectively collaborate with engineering teams, product owners, and business/domain experts. Preferred Qualifications Experience implementing retrieval-augmented generation (RAG), including document ingestion, embedding generation, vector search, retrieval strategies, and grounding evaluation. Experience with healthcare analytics, enterprise reporting platforms, or data-intensive applications involving sensitive information. Experience transitioning AI proof-of-concept solutions into production-grade enterprise applications. Familiarity with AI quality metrics, LLM-as-a-judge approaches, semantic evaluation, groundedness assessment, and human evaluation workflows. Experience optimizing AI application performance, model selection, inference latency, token consumption, and cloud operating costs. Familiarity with Azure AI services and enterprise AI application architecture.
11/14/2026
Full time
Job Description Candidate must already live in Chicago! No exceptions! Senior Full Stack Engineer Contract Position Position Overview We are seeking an experienced Senior Full Stack & Cloud-Native AI Engineer to transform an existing Data Insight proof of concept into a secure, scalable, production-ready enterprise application. The application enables users to explore reporting data, ask contextual follow-up questions, and gain actionable insights supported by verifiable source evidence. In this role, you will design and develop end-to-end application capabilities, including agentic AI workflows, full-stack user experiences, cloud-native services, and enterprise integrations. You will play a critical role in establishing the evaluation, testing, and monitoring frameworks required to ensure the accuracy, reliability, security, and continuous improvement of AI-powered functionality. The ideal candidate combines strong full-stack engineering expertise with hands-on experience developing production-grade AI applications, particularly agentic workflows, retrieval-augmented generation (RAG), and AI evaluation frameworks. Key Responsibilities Agentic AI Application Development Design, develop, and deploy production-grade agentic AI applications using large language models (LLMs), tool calling, structured outputs, and multi-step reasoning workflows. Build intelligent workflows that interpret user intent, maintain conversation context, orchestrate tools and APIs, and support human review when appropriate. Implement prompt engineering, context management, workflow orchestration, and error-handling strategies to improve application reliability and response quality. Integrate retrieval-augmented generation (RAG) capabilities to ground AI-generated responses in trusted enterprise data and source documents. F ull Stack & Cloud-Native Development Develop responsive, user-friendly web applications using Angular and modern front-end development practices. Design and implement scalable backend services and RESTful APIs using C# and .NET. Develop Python-based AI services and agent orchestration components. Integrate application services with existing enterprise reporting platforms, databases, authentication providers, and data-access systems. Build and deploy cloud-native solutions using Microsoft Azure and associated cloud services. Implement secure API integrations, asynchronous processing, and resilient service-to-service communication. AI Evaluation, Testing & Quality Engineering Own the design and implementation of comprehensive evaluation frameworks for AI-powered applications. Collaborate with healthcare domain experts and product owners to curate representative evaluation datasets and define scoring rubrics, quality metrics, and acceptance criteria. Develop automated evaluation processes to assess: Accuracy and relevance of AI-generated answers. Correctness and traceability of supporting evidence. Tool selection, execution, and workflow orchestration. Context retention and multi-turn conversation quality. End-to-end task completion and user experience. Handling of ambiguous, unsupported, and out-of-scope requests. Combine automated evaluation with human review to validate analytical accuracy and domain-specific correctness. Establish regression testing and baseline comparisons to identify quality degradation resulting from changes to models, prompts, datasets, or application code. Integrate AI evaluation suites, automated tests, and quality gates into CI/CD pipelines. Maintain version-controlled prompts, evaluation datasets, test configurations, and performance baselines. Reliability, Security & Production Operations Design resilient execution workflows incorporating timeouts, retries, cancellation, durable state management, and recovery mechanisms. Implement authentication, authorization, and data-access controls across APIs, AI agents, tools, and underlying data sources. Ensure sensitive healthcare and enterprise data is handled securely and in accordance with applicable organizational policies. Establish observability through application logging, distributed tracing, performance monitoring, and error reporting. Monitor production AI quality, response latency, operational costs, and failure rates. Analyze production feedback and failures, convert findings into reproducible test cases, and drive measurable improvements. Optimize application performance, scalability, reliability, and cloud operating costs. Data Engineering & Analytical Integrity Develop and optimize SQL queries, relational data models, and data-access services. Ensure analytical results are accurate, reproducible, and supported by traceable source data. Address data-quality challenges, including missing values, inconsistencies, numerical precision, and aggregation accuracy. Work closely with business stakeholders and healthcare domain experts to validate analytical findings and communicate uncertainty and system limitations. Required Qualifications 8+ years of professional software engineering experience delivering and supporting secure, scalable enterprise applications. Hands-on experience designing and developing agentic AI applications using LLMs, tool calling, structured outputs, prompt engineering, and multi-step workflows. Strong full-stack development experience with Angular, C#/.NET Web APIs, and Python. Practical experience building AI evaluation and quality pipelines, including evaluation datasets, scoring methodologies, automated regression testing, and human-in-the-loop validation. Demonstrated ability to use evaluation results and production feedback to improve AI application quality and reliability. Strong experience with SQL, relational database design, data modeling, and analytical data processing. Experience building and deploying cloud-native applications using Microsoft Azure. Hands-on experience with CI/CD pipelines, automated unit testing, integration testing, and end-to-end testing. Strong understanding of enterprise application security, authentication, authorization, secure API design, and data-access controls. Experience implementing observability, distributed tracing, asynchronous processing, and fault-tolerant application architectures. Strong analytical, problem-solving, communication, and collaboration skills. Ability to work independently and effectively collaborate with engineering teams, product owners, and business/domain experts. Preferred Qualifications Experience implementing retrieval-augmented generation (RAG), including document ingestion, embedding generation, vector search, retrieval strategies, and grounding evaluation. Experience with healthcare analytics, enterprise reporting platforms, or data-intensive applications involving sensitive information. Experience transitioning AI proof-of-concept solutions into production-grade enterprise applications. Familiarity with AI quality metrics, LLM-as-a-judge approaches, semantic evaluation, groundedness assessment, and human evaluation workflows. Experience optimizing AI application performance, model selection, inference latency, token consumption, and cloud operating costs. Familiarity with Azure AI services and enterprise AI application architecture.
LexisNexis Legal & Professional
Raleigh, North Carolina
This job is with LexisNexis Legal & Professional , an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Are you excited to lead the development of next-generation AI-powered legal solutions that help professionals draft, reason, and work more effectively with complex legal information? Do you thrive at the intersection of people leadership, large language models, retrieval-augmented generation, and product innovation, turning emerging AI capabilities into meaningful customer outcomes ? About our Team LexisNexis Legal & Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of RELX (), a global provider of information-based analytics and decision tools for professional and business customers. Our company has been a long-time leader in deploying AI and advanced technologies to the legal market to improve productivity and transform the overall business and practice of law, deploying ethical and powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model from today's top model creators for each individual legal use case. The company employs over 2,000 technologists, data scientists, and experts to develop, test, and validate solutions in line with RELX Responsible AI Principles. About LexisNexis Data Sciences: At LexisNexis, we're redefining legal intelligence through advanced AI. Our teams harness the power of large language models (LLMs), retrieval-augmented generation (RAG), and agentic systems to build tools that analyze, draft, and reason with legal text. Join us in building AI systems that help legal professionals move faster, think deeper, and operate with confidence. Role Overview: We are seeking a Manager of Data Science to lead a high-impact team focused on building intelligent systems powered by LLMs and RAG architectures. This role will focus on improving LLM-powered drafting and retrieval solutions through advanced search, embeddings, reranking, evaluation, and production-grade ML components. You'll drive the strategy, technical execution, and team growth necessary to build next-generation legal assistants, capable of contextual document drafting, and interaction with structured and unstructured data sources. Key Responsibilities: Vision & Strategy: Define the roadmap for applying LLMs and agentic AI to real-world legal drafting. Evangelize and embed AI-driven change across legal product platforms. Translate evolving generative AI capabilities into tangible customer value within the legal domain. Technical & Product Leadership: Architect systems that combine foundation models with RAG pipelines to draft contracts, memos, and pleadings grounded in enterprise knowledge. Guide the development of AI agents that perform multi-step reasoning, cite evidence, retrieve domain-specific content, and produce compliant outputs. Team & Operational Excellence: Mentor and grow a multidisciplinary team of LLM-focused Data Scientists and ML Engineers. Drive cross-functional collaboration with Legal SMEs, Data Engineers, Product Managers, and Design. Establish best practices for evaluation, observability, and responsible use of generative AI. Core Qualifications: Experience Previous people management experience (3+ years) of teams building LLM-based applications, especially in domains requiring rigor and traceability like legal, finance, or compliance. Hands-on experience delivering systems using LangChain, LLM agent frameworks, vector databases, and prompt orchestration pipelines. Strong background in deploying retrieval-augmented generation (RAG) systems for grounded and auditable responses. Demonstrated success in taking LLM-powered applications from prototype to production. Technical Proficiency Proficient with Python and LLM tooling: LangChain, HuggingFace Transformers, OpenAI APIs, and prompt tuning techniques. Familiarity with vector databases (e.g., Solr, Elasticsearch, Qdrant, Weaviate), knowledge graphs, and hybrid retrieval architectures. Working knowledge of containerization (Docker, Kubernetes), CI/CD, and model serving tools (TorchServe, Triton, Ray Serve). Cloud infrastructure experience on AWS, Azure, or GCP. Preferred Background Graduate degree in Computer Science, AI, Machine Learning, or equivalent experience. 6 years of post-degree experience, with 3+ years in a data science or applied AI leadership role, with a focus on NLP/LLM systems. Prior experience in legal tech, legal AI, or document-intensive domains is highly desirable. Familiarity with ethical/legal considerations in deploying generative AI in professional settings. Work in a Way That Works for You We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals. Working Pattern Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive. About the Business LexisNexis Legal & Professional provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis and Nexis services. U.S. National Base Pay Range: $115,400 - $192,300. Geographic differentials may apply in some locations to better reflect local market rates. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here . Please read our Candidate Privacy Policy . We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights .
11/14/2026
Full time
This job is with LexisNexis Legal & Professional , an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Are you excited to lead the development of next-generation AI-powered legal solutions that help professionals draft, reason, and work more effectively with complex legal information? Do you thrive at the intersection of people leadership, large language models, retrieval-augmented generation, and product innovation, turning emerging AI capabilities into meaningful customer outcomes ? About our Team LexisNexis Legal & Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of RELX (), a global provider of information-based analytics and decision tools for professional and business customers. Our company has been a long-time leader in deploying AI and advanced technologies to the legal market to improve productivity and transform the overall business and practice of law, deploying ethical and powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model from today's top model creators for each individual legal use case. The company employs over 2,000 technologists, data scientists, and experts to develop, test, and validate solutions in line with RELX Responsible AI Principles. About LexisNexis Data Sciences: At LexisNexis, we're redefining legal intelligence through advanced AI. Our teams harness the power of large language models (LLMs), retrieval-augmented generation (RAG), and agentic systems to build tools that analyze, draft, and reason with legal text. Join us in building AI systems that help legal professionals move faster, think deeper, and operate with confidence. Role Overview: We are seeking a Manager of Data Science to lead a high-impact team focused on building intelligent systems powered by LLMs and RAG architectures. This role will focus on improving LLM-powered drafting and retrieval solutions through advanced search, embeddings, reranking, evaluation, and production-grade ML components. You'll drive the strategy, technical execution, and team growth necessary to build next-generation legal assistants, capable of contextual document drafting, and interaction with structured and unstructured data sources. Key Responsibilities: Vision & Strategy: Define the roadmap for applying LLMs and agentic AI to real-world legal drafting. Evangelize and embed AI-driven change across legal product platforms. Translate evolving generative AI capabilities into tangible customer value within the legal domain. Technical & Product Leadership: Architect systems that combine foundation models with RAG pipelines to draft contracts, memos, and pleadings grounded in enterprise knowledge. Guide the development of AI agents that perform multi-step reasoning, cite evidence, retrieve domain-specific content, and produce compliant outputs. Team & Operational Excellence: Mentor and grow a multidisciplinary team of LLM-focused Data Scientists and ML Engineers. Drive cross-functional collaboration with Legal SMEs, Data Engineers, Product Managers, and Design. Establish best practices for evaluation, observability, and responsible use of generative AI. Core Qualifications: Experience Previous people management experience (3+ years) of teams building LLM-based applications, especially in domains requiring rigor and traceability like legal, finance, or compliance. Hands-on experience delivering systems using LangChain, LLM agent frameworks, vector databases, and prompt orchestration pipelines. Strong background in deploying retrieval-augmented generation (RAG) systems for grounded and auditable responses. Demonstrated success in taking LLM-powered applications from prototype to production. Technical Proficiency Proficient with Python and LLM tooling: LangChain, HuggingFace Transformers, OpenAI APIs, and prompt tuning techniques. Familiarity with vector databases (e.g., Solr, Elasticsearch, Qdrant, Weaviate), knowledge graphs, and hybrid retrieval architectures. Working knowledge of containerization (Docker, Kubernetes), CI/CD, and model serving tools (TorchServe, Triton, Ray Serve). Cloud infrastructure experience on AWS, Azure, or GCP. Preferred Background Graduate degree in Computer Science, AI, Machine Learning, or equivalent experience. 6 years of post-degree experience, with 3+ years in a data science or applied AI leadership role, with a focus on NLP/LLM systems. Prior experience in legal tech, legal AI, or document-intensive domains is highly desirable. Familiarity with ethical/legal considerations in deploying generative AI in professional settings. Work in a Way That Works for You We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals. Working Pattern Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive. About the Business LexisNexis Legal & Professional provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis and Nexis services. U.S. National Base Pay Range: $115,400 - $192,300. Geographic differentials may apply in some locations to better reflect local market rates. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here . Please read our Candidate Privacy Policy . We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights .
POSITION SUMMARY: The Senior Manager, Network Infrastructure & Services is responsible for the strategy, architecture, security, availability, and lifecycle management of all network and connectivity services supporting LBCT's critical business and terminal operations. This position provides leadership and oversight for enterprise networking, telecommunications, wireless infrastructure, operational technology (OT) connectivity, carrier services, network security platforms, and managed service providers. The Senior Manager oversees Cisco networking, Fortinet and Palo Alto security platforms, enterprise wireless infrastructure, network segmentation, carrier services, and managed service provider governance. The role ensures highly available, secure, and resilient network services capable of supporting 24x7 marine terminal operations. The Senior Manager develops technology roadmaps, establishes engineering standards, manages vendor relationships, and drives continuous improvement through automation, analytics, and emerging technologies. This position works closely with Cyber Security, Systems Administration, Operations, and business stakeholders to ensure infrastructure services meet operational and strategic business requirements. ESSENTIAL DUTIES AND RESPONSIBILITIES Maintain a safe and secure working environment while promoting IT Operational excellence throughout the organization. Develop and maintain the terminal's network architecture, standards, technology roadmap, and lifecycle strategy. Architect highly available LAN, WAN, wireless, Internet, data center, cloud, and remote-access connectivity. Design networks for environments requiring extremely high availability and rapid recovery from infrastructure failures. Establish architecture and engineering standards for enterprise and outdoor wireless infrastructure. Establish network segmentation and security architectures separating corporate IT, OT, vendors, Internet-facing systems, and other security zones. Develop standards for switching, routing, firewalls, wireless, IP addressing, DNS/DHCP, network access control, and connectivity services. Evaluate emerging technologies and determine their applicability to terminal operations. Ensure infrastructure capacity supports growth in automation, IoT/OT devices, video, telemetry, mobile equipment, and cloud services. Participate in operational change management to minimize disruption to terminal activities. Provide technical leadership and governance for the terminal's Cisco environment. Maintain configuration, architecture, lifecycle, and resilience standards across the network environment. Lead network-security architecture and operations using technologies including Fortinet and Palo Alto Networks, as applicable. Maintain compliance with industry regulations and standards, including those specific to maritime and port operations. Partner with cybersecurity team to implement Zero Trust principles and strengthen protection of critical IT and operational infrastructure. Assist cyber team with regular security audits and vulnerability assessments. Own the performance and governance of network-related managed service providers, telecommunications carriers, contractors, and technology vendors. Maintain appropriate records of vendor issues, decisions, commitments, and outstanding actions. Enforce and monitor contractual service level agreements (SLAs) with IT vendors and assigned independent contractors. Foster a culture of accountability, technical excellence, continuous improvement, and customer service. With other IT management, contribute to the development and implementation of the IT strategy for the terminal. Perform other related duties as assigned. REQUIRED KNOWLEDGE, SKILLS, AND ABILITIES : Strong managerial, supervisory, and decision-making skills to achieve department and company goals. Excellent interpersonal skills. Ability to interact with a variety of people throughout the corporation. Ability to remain calm and professional during confrontational situations. Effective public speaking and presentation skills. Be able to present and defend a point of view. Possess excellent communication, written, oral, and interpersonal and teamwork skills, communicate constructively and confidently, listen openly, and collaborate well with staff and others in different groups. Ability to relate information from a multitude of sources. Capability to turn theoretical information into practical applications. Convey a professional and positive attitude with action/results orientation to problem solving and elimination of backlogs. Proven ability and experience in exercising good judgment and discretion in handling confidential materials and matters. Possess strong organizational and analytical skills in managing daily, weekly, monthly, quarterly, or annual deadlines, but flexible to a changing list of priorities, sometimes daily. Excellent attention to detail with a high degree of accuracy. Ability to handle multiple demands; prioritize workloads; establish and maintain positive, cooperative, and productive working relationships. Advanced understanding and familiarity with Microsoft: Server, SQL, Office Suite, Azure, Active Directory, and DNS. Advanced understanding of and familiarity with VMWare and Dell EMC storage solutions. Experience with vulnerability scanning solutions. Familiarity with the NIST Cybersecurity Framework, CIS Controls, and relevant cybersecurity frameworks. In-depth knowledge of Routing and switching, TCP/IP, BGP and OSPF, VLANs and VRFs, Wireless networking, Firewalls, VPN technologies, Network segmentation, DNS/DHCP, Network monitoring, and High-availability architecture. Network automation using APIs, scripting, orchestration platforms, or infrastructure as code. Knowledge of marine terminal technology is highly desirable, including Terminal Operating Systems, Gate systems, OCR, RFID, GPS/location technologies, and truck appointment systems (NAVIS experience a plus). Stay informed about emerging technologies and trends and make recommendations for future IT investments. EDUCATION AND/OR EXPERIENCE Bachelor's degree in Information Technology, Computer Science, Engineering, or a related field. Seven (7+) years of progressive experience in network engineering, telecommunications, or infrastructure operations. Five (5+) years of leadership experience managing technical teams or critical infrastructure services. Advanced experience with Cisco networking technologies. Significant experience with enterprise firewall and security technologies, Palo Alto and/or Fortinet preferred. Experience in a marine container terminal or similar industrial environment is preferred Experience working in a unionized environment, a plus. PHYSICAL REQUIREMENTS The ability to work any days or hours, including weekends and holidays. The ability to walk and stand for extended periods of time. The ability to use a computer and keyboard. The ability to sit and work at a desk and/or computer for extended periods of time. The ability to lift 30-50 pounds with or without assistance. The ability to drive a company owned pickup truck. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions of the position. WORKING ENVIRONMENT The work is performed both inside and outside at LBCT sites, various marine terminal locations, in temporary offices and in classrooms. Position is based in Long Beach, CA; work assignments may require travel to other marine terminal sites or travel to other offices. TWIC: You will be required to apply and successfully obtain a TWIC (Transportation Worker's Identification Credential). NOTE: This job description is not all-inclusive. An Employee may perform other related duties as required to meet the ongoing needs of LBCT LLC. LBCT LLC is an equal opportunity employer committed to equity and inclusion in the workplace. Compensation details: 00 Yearly Salary PI65aebe2bcb05-7712
11/14/2026
Full time
POSITION SUMMARY: The Senior Manager, Network Infrastructure & Services is responsible for the strategy, architecture, security, availability, and lifecycle management of all network and connectivity services supporting LBCT's critical business and terminal operations. This position provides leadership and oversight for enterprise networking, telecommunications, wireless infrastructure, operational technology (OT) connectivity, carrier services, network security platforms, and managed service providers. The Senior Manager oversees Cisco networking, Fortinet and Palo Alto security platforms, enterprise wireless infrastructure, network segmentation, carrier services, and managed service provider governance. The role ensures highly available, secure, and resilient network services capable of supporting 24x7 marine terminal operations. The Senior Manager develops technology roadmaps, establishes engineering standards, manages vendor relationships, and drives continuous improvement through automation, analytics, and emerging technologies. This position works closely with Cyber Security, Systems Administration, Operations, and business stakeholders to ensure infrastructure services meet operational and strategic business requirements. ESSENTIAL DUTIES AND RESPONSIBILITIES Maintain a safe and secure working environment while promoting IT Operational excellence throughout the organization. Develop and maintain the terminal's network architecture, standards, technology roadmap, and lifecycle strategy. Architect highly available LAN, WAN, wireless, Internet, data center, cloud, and remote-access connectivity. Design networks for environments requiring extremely high availability and rapid recovery from infrastructure failures. Establish architecture and engineering standards for enterprise and outdoor wireless infrastructure. Establish network segmentation and security architectures separating corporate IT, OT, vendors, Internet-facing systems, and other security zones. Develop standards for switching, routing, firewalls, wireless, IP addressing, DNS/DHCP, network access control, and connectivity services. Evaluate emerging technologies and determine their applicability to terminal operations. Ensure infrastructure capacity supports growth in automation, IoT/OT devices, video, telemetry, mobile equipment, and cloud services. Participate in operational change management to minimize disruption to terminal activities. Provide technical leadership and governance for the terminal's Cisco environment. Maintain configuration, architecture, lifecycle, and resilience standards across the network environment. Lead network-security architecture and operations using technologies including Fortinet and Palo Alto Networks, as applicable. Maintain compliance with industry regulations and standards, including those specific to maritime and port operations. Partner with cybersecurity team to implement Zero Trust principles and strengthen protection of critical IT and operational infrastructure. Assist cyber team with regular security audits and vulnerability assessments. Own the performance and governance of network-related managed service providers, telecommunications carriers, contractors, and technology vendors. Maintain appropriate records of vendor issues, decisions, commitments, and outstanding actions. Enforce and monitor contractual service level agreements (SLAs) with IT vendors and assigned independent contractors. Foster a culture of accountability, technical excellence, continuous improvement, and customer service. With other IT management, contribute to the development and implementation of the IT strategy for the terminal. Perform other related duties as assigned. REQUIRED KNOWLEDGE, SKILLS, AND ABILITIES : Strong managerial, supervisory, and decision-making skills to achieve department and company goals. Excellent interpersonal skills. Ability to interact with a variety of people throughout the corporation. Ability to remain calm and professional during confrontational situations. Effective public speaking and presentation skills. Be able to present and defend a point of view. Possess excellent communication, written, oral, and interpersonal and teamwork skills, communicate constructively and confidently, listen openly, and collaborate well with staff and others in different groups. Ability to relate information from a multitude of sources. Capability to turn theoretical information into practical applications. Convey a professional and positive attitude with action/results orientation to problem solving and elimination of backlogs. Proven ability and experience in exercising good judgment and discretion in handling confidential materials and matters. Possess strong organizational and analytical skills in managing daily, weekly, monthly, quarterly, or annual deadlines, but flexible to a changing list of priorities, sometimes daily. Excellent attention to detail with a high degree of accuracy. Ability to handle multiple demands; prioritize workloads; establish and maintain positive, cooperative, and productive working relationships. Advanced understanding and familiarity with Microsoft: Server, SQL, Office Suite, Azure, Active Directory, and DNS. Advanced understanding of and familiarity with VMWare and Dell EMC storage solutions. Experience with vulnerability scanning solutions. Familiarity with the NIST Cybersecurity Framework, CIS Controls, and relevant cybersecurity frameworks. In-depth knowledge of Routing and switching, TCP/IP, BGP and OSPF, VLANs and VRFs, Wireless networking, Firewalls, VPN technologies, Network segmentation, DNS/DHCP, Network monitoring, and High-availability architecture. Network automation using APIs, scripting, orchestration platforms, or infrastructure as code. Knowledge of marine terminal technology is highly desirable, including Terminal Operating Systems, Gate systems, OCR, RFID, GPS/location technologies, and truck appointment systems (NAVIS experience a plus). Stay informed about emerging technologies and trends and make recommendations for future IT investments. EDUCATION AND/OR EXPERIENCE Bachelor's degree in Information Technology, Computer Science, Engineering, or a related field. Seven (7+) years of progressive experience in network engineering, telecommunications, or infrastructure operations. Five (5+) years of leadership experience managing technical teams or critical infrastructure services. Advanced experience with Cisco networking technologies. Significant experience with enterprise firewall and security technologies, Palo Alto and/or Fortinet preferred. Experience in a marine container terminal or similar industrial environment is preferred Experience working in a unionized environment, a plus. PHYSICAL REQUIREMENTS The ability to work any days or hours, including weekends and holidays. The ability to walk and stand for extended periods of time. The ability to use a computer and keyboard. The ability to sit and work at a desk and/or computer for extended periods of time. The ability to lift 30-50 pounds with or without assistance. The ability to drive a company owned pickup truck. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions of the position. WORKING ENVIRONMENT The work is performed both inside and outside at LBCT sites, various marine terminal locations, in temporary offices and in classrooms. Position is based in Long Beach, CA; work assignments may require travel to other marine terminal sites or travel to other offices. TWIC: You will be required to apply and successfully obtain a TWIC (Transportation Worker's Identification Credential). NOTE: This job description is not all-inclusive. An Employee may perform other related duties as required to meet the ongoing needs of LBCT LLC. LBCT LLC is an equal opportunity employer committed to equity and inclusion in the workplace. Compensation details: 00 Yearly Salary PI65aebe2bcb05-7712
Job Description Job Description Description: Position Summary Avum is seeking an AI/ML Integration Specialist to integrate artificial intelligence and machine learning capabilities into business applications and technology platforms. This role works with engineering, data, and business teams to turn AI solutions into reliable, secure, and scalable production capabilities. Key Responsibilities Design, develop, and maintain integrations connecting AI/ML models, APIs, and services with existing applications. Implement generative AI, large language models (LLMs), natural language processing, computer vision, and predictive analytics capabilities to support business needs. Build and maintain APIs, data pipelines, middleware, and integration workflows. Collaborate with data scientists, engineers, product teams, and business stakeholders to define requirements and move models from development into production. Evaluate and improve AI solution performance, scalability, security, reliability, and cost. Monitor deployed solutions, troubleshoot issues, and establish practices for testing, version control, deployment, and ongoing monitoring. Ensure solutions meet organizational security, privacy, governance, and responsible AI requirements. Document architectures, integrations, and operating procedures, and recommend emerging technologies that support business goals. Compensation Actual compensation and position level will be determined based on experience, qualifications, certifications, geographic location, and the responsibilities of the assigned role. Avum offers a comprehensive benefits package including medical (Cigna), dental and vision (Principal), 401(k), PTO, education reimbursement, and certification reimbursement. Work Environment & Requirements Hybrid/remote work environment with potential on-site requirements based on contract needs U.S. citizenship required Security clearance may be required based on contract assignment Equal Employment Opportunity Avum, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected class under federal, state, or local law. Avum is committed to compliance with Section 503 of the Rehabilitation Act and VEVRAA, and maintains an active Affirmative Action Plan. Requirements: Required Qualifications U.S. citizenship with the ability to obtain and maintain a U.S. Government security clearance. Bachelor's degree in Computer Science, Software Engineering, Data Science, AI/ML, or a related field. Three or more years of experience in software engineering, systems integration, ML engineering, data engineering, or a related discipline. Experience integrating REST APIs, SDKs, microservices, and third party platforms. Strong programming skills in Python and/or Java, JavaScript, or TypeScript. Understanding of machine learning concepts, the model lifecycle, and AI application architecture. Experience working with databases, data pipelines, JSON, SQL, and cloud environments. Familiarity with Git, CI/CD, testing, logging, monitoring, and production deployment practices. Strong analytical, troubleshooting, communication, and problem solving skills. Preferred Qualifications Experience integrating LLMs and generative AI applications using OpenAI, Azure AI, AWS AI/ML, Google Cloud AI, or comparable platforms. Knowledge of retrieval augmented generation (RAG), vector databases, embeddings, and semantic search. Experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn. Familiarity with Docker, Kubernetes, serverless architectures, and cloud native development. Experience with MLOps, LLMOps, and model monitoring. Knowledge of AI security, governance, privacy, and responsible AI practices. Experience integrating AI capabilities with Salesforce, ServiceNow, SAP, Microsoft Dynamics, or similar enterprise platforms.
11/14/2026
Full time
Job Description Job Description Description: Position Summary Avum is seeking an AI/ML Integration Specialist to integrate artificial intelligence and machine learning capabilities into business applications and technology platforms. This role works with engineering, data, and business teams to turn AI solutions into reliable, secure, and scalable production capabilities. Key Responsibilities Design, develop, and maintain integrations connecting AI/ML models, APIs, and services with existing applications. Implement generative AI, large language models (LLMs), natural language processing, computer vision, and predictive analytics capabilities to support business needs. Build and maintain APIs, data pipelines, middleware, and integration workflows. Collaborate with data scientists, engineers, product teams, and business stakeholders to define requirements and move models from development into production. Evaluate and improve AI solution performance, scalability, security, reliability, and cost. Monitor deployed solutions, troubleshoot issues, and establish practices for testing, version control, deployment, and ongoing monitoring. Ensure solutions meet organizational security, privacy, governance, and responsible AI requirements. Document architectures, integrations, and operating procedures, and recommend emerging technologies that support business goals. Compensation Actual compensation and position level will be determined based on experience, qualifications, certifications, geographic location, and the responsibilities of the assigned role. Avum offers a comprehensive benefits package including medical (Cigna), dental and vision (Principal), 401(k), PTO, education reimbursement, and certification reimbursement. Work Environment & Requirements Hybrid/remote work environment with potential on-site requirements based on contract needs U.S. citizenship required Security clearance may be required based on contract assignment Equal Employment Opportunity Avum, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected class under federal, state, or local law. Avum is committed to compliance with Section 503 of the Rehabilitation Act and VEVRAA, and maintains an active Affirmative Action Plan. Requirements: Required Qualifications U.S. citizenship with the ability to obtain and maintain a U.S. Government security clearance. Bachelor's degree in Computer Science, Software Engineering, Data Science, AI/ML, or a related field. Three or more years of experience in software engineering, systems integration, ML engineering, data engineering, or a related discipline. Experience integrating REST APIs, SDKs, microservices, and third party platforms. Strong programming skills in Python and/or Java, JavaScript, or TypeScript. Understanding of machine learning concepts, the model lifecycle, and AI application architecture. Experience working with databases, data pipelines, JSON, SQL, and cloud environments. Familiarity with Git, CI/CD, testing, logging, monitoring, and production deployment practices. Strong analytical, troubleshooting, communication, and problem solving skills. Preferred Qualifications Experience integrating LLMs and generative AI applications using OpenAI, Azure AI, AWS AI/ML, Google Cloud AI, or comparable platforms. Knowledge of retrieval augmented generation (RAG), vector databases, embeddings, and semantic search. Experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn. Familiarity with Docker, Kubernetes, serverless architectures, and cloud native development. Experience with MLOps, LLMOps, and model monitoring. Knowledge of AI security, governance, privacy, and responsible AI practices. Experience integrating AI capabilities with Salesforce, ServiceNow, SAP, Microsoft Dynamics, or similar enterprise platforms.
LexisNexis Legal & Professional
Horsham, Pennsylvania
This job is with LexisNexis Legal & Professional , an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. About Our Team For over 50 years, LexisNexis Reed Technology has partnered with the U.S. Patent and Trademark Office (USPTO) to deliver secure, scalable, and high-quality patent data processing solutions. Our work transforms complex, unstructured patent submissions into standardized, searchable outputs that power examiner workflows and public dissemination. We operate in a highly regulated environment with strict security requirements, large-scale data volumes, and complex business rules. Our focus is on modernizing legacy workflows through automation, AI, and platform transformation to improve efficiency, accuracy, and cost effectiveness. About the Role Principal AI Engineer - Architecture Track We are seeking a hands-on Principal AI Engineer who can design and build production-grade AI solutions while growing into a broader AI Architect role. This position is ideal for an experienced AI developer or technical lead who has strong engineering depth, understands modern AI architecture, and is ready to expand their influence across platforms, products, and delivery teams. The Principal AI Engineer will work closely with product managers, architects, data scientists, software engineers, security teams, and government stakeholders to translate mission and business needs into secure, scalable, and reusable AI capabilities. The role will initially focus on solution design and hands-on implementation, with increasing responsibility for architecture standards, technical strategy, governance, and cross-team alignment. Conditions of Employment: You must be a U.S. citizen to apply for this position. You must successfully pass a background investigation and achieve Public Trust security clearance. Must be located near the Horsham, PA location for a hybrid onsite schedule. Responsibilities AI Solution Design and Development Design, prototype, and implement AI-powered applications, services, agents, and workflows. Translate business, user, and government mission requirements into practical technical solutions. Develop solutions using large language models, retrieval-augmented generation, machine learning, natural language processing, computer vision, or other relevant AI technologies. Build reusable AI components, services, APIs, evaluation frameworks, and reference implementations. Integrate AI capabilities with enterprise platforms, data sources, workflows, and existing applications. Balance rapid experimentation with the engineering discipline required for secure, reliable production systems. Evaluate models, platforms, frameworks, and vendors based on performance, cost, security, scalability, and mission fit. Architecture and Technical Leadership Contribute to solution architectures covering applications, models, data, integrations, infrastructure, security, and operational monitoring. Partner with senior architects to establish AI architecture patterns, guardrails, standards, and reference architectures. Help teams make informed decisions regarding commercial, open-source, and internally developed AI capabilities. Identify opportunities to create shared AI services and reusable capabilities across products, contracts, and government agencies. Participate in architecture reviews and clearly document technical decisions, tradeoffs, assumptions, and risks. Provide technical guidance, code reviews, mentoring, and hands-on support to engineering and data science teams. Grow into ownership of end-to-end AI solution architecture and broader technical strategy. Government and Stakeholder Engagement Support technical discovery sessions, demonstrations, proofs of concept, proposals, RFIs, and RFP responses. Communicate complex AI concepts, limitations, risks, and tradeoffs clearly to both technical and non-technical audiences. Help move successful prototypes into secure, supportable, and scalable production capabilities. Stay informed about evolving government AI policies, standards, acquisition practices, and responsible-AI expectations. Requirement Bachelor's degree in computer science, engineering, data science, information systems, or a related field, or equivalent practical experience. Significant professional software engineering experience, including experience delivering production applications or platforms. Hands-on experience developing AI, machine-learning, or data-intensive solutions. Proficiency in Python and experience with APIs, cloud services, data pipelines, software development practices, and source control. Experience with modern generative-AI patterns, such as large language models, retrieval-augmented generation, embeddings, vector search, tool use, structured outputs, or AI agents. Understanding of cloud-native architecture, system integration, identity and access management, observability, and secure development practices. Ability to evaluate technical alternatives and explain architecture decisions and tradeoffs. Experience working across product, engineering, data, security, and business teams. Strong written and verbal communication skills. Ability to satisfy applicable government background, suitability, or contractual requirements. Incorporate security, privacy, accessibility, explainability, auditability, and human oversight into solution designs. Establish appropriate evaluation methods for accuracy, relevance, groundedness, bias, safety, and reliability. Design controls for model and prompt versioning, data lineage, access management, logging, monitoring, and traceability. Partner with cybersecurity, legal, privacy, compliance, and governance teams throughout the solution lifecycle. Ensure solutions align with applicable organizational policies, contractual obligations, and government requirements. Design human-in-the-loop controls based on the risk and impact of the decisions supported or performed by AI. Preferred Qualifications Experience delivering technology solutions for U.S. federal, state, or local government customers. Experience working in government contracting, regulated environments, or programs involving sensitive data. Familiarity with government security and compliance frameworks, such as NIST, FedRAMP, FISMA, or agency-specific controls. Experience with one or more major cloud platforms, particularly AWS, Microsoft Azure, or Google Cloud. Experience with AI orchestration frameworks, model gateways, vector databases, evaluation platforms, MLOps, or LLMOps. Understanding of model evaluation, prompt engineering, fine-tuning, data governance, and responsible-AI practices. Experience moving AI proofs of concept into production. Experience supporting technical proposals, RFIs, RFPs, solution demonstrations, or customer workshops. Prior technical leadership, mentoring, or architecture-review experience. Relevant cloud, architecture, security, data, or AI certifications. Work in a Way That Works for You We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals. Working flexible hours to help you fit everything in and work when you are the most productive Working for You We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer: Health Benefits: Comprehensive, multi-carrier program for medical, dental and vision benefits Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan Wellbeing: Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time-off Programs Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity Family Benefits, including bonding and family care leaves, adoption and surrogacy benefits Health Savings, Health Care, Dependent Care and Commuter Spending Accounts Up to two days of paid leave each to participate in Employee Resource Groups and to volunteer with your charity of choice About the Business LexisNexis Legal & Professional provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis and Nexis services. U.S. National Base Pay Range: $136,100 - $252,800. Geographic differentials may apply in some locations to better reflect local market rates. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process . click apply for full job details
11/14/2026
Full time
This job is with LexisNexis Legal & Professional , an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. About Our Team For over 50 years, LexisNexis Reed Technology has partnered with the U.S. Patent and Trademark Office (USPTO) to deliver secure, scalable, and high-quality patent data processing solutions. Our work transforms complex, unstructured patent submissions into standardized, searchable outputs that power examiner workflows and public dissemination. We operate in a highly regulated environment with strict security requirements, large-scale data volumes, and complex business rules. Our focus is on modernizing legacy workflows through automation, AI, and platform transformation to improve efficiency, accuracy, and cost effectiveness. About the Role Principal AI Engineer - Architecture Track We are seeking a hands-on Principal AI Engineer who can design and build production-grade AI solutions while growing into a broader AI Architect role. This position is ideal for an experienced AI developer or technical lead who has strong engineering depth, understands modern AI architecture, and is ready to expand their influence across platforms, products, and delivery teams. The Principal AI Engineer will work closely with product managers, architects, data scientists, software engineers, security teams, and government stakeholders to translate mission and business needs into secure, scalable, and reusable AI capabilities. The role will initially focus on solution design and hands-on implementation, with increasing responsibility for architecture standards, technical strategy, governance, and cross-team alignment. Conditions of Employment: You must be a U.S. citizen to apply for this position. You must successfully pass a background investigation and achieve Public Trust security clearance. Must be located near the Horsham, PA location for a hybrid onsite schedule. Responsibilities AI Solution Design and Development Design, prototype, and implement AI-powered applications, services, agents, and workflows. Translate business, user, and government mission requirements into practical technical solutions. Develop solutions using large language models, retrieval-augmented generation, machine learning, natural language processing, computer vision, or other relevant AI technologies. Build reusable AI components, services, APIs, evaluation frameworks, and reference implementations. Integrate AI capabilities with enterprise platforms, data sources, workflows, and existing applications. Balance rapid experimentation with the engineering discipline required for secure, reliable production systems. Evaluate models, platforms, frameworks, and vendors based on performance, cost, security, scalability, and mission fit. Architecture and Technical Leadership Contribute to solution architectures covering applications, models, data, integrations, infrastructure, security, and operational monitoring. Partner with senior architects to establish AI architecture patterns, guardrails, standards, and reference architectures. Help teams make informed decisions regarding commercial, open-source, and internally developed AI capabilities. Identify opportunities to create shared AI services and reusable capabilities across products, contracts, and government agencies. Participate in architecture reviews and clearly document technical decisions, tradeoffs, assumptions, and risks. Provide technical guidance, code reviews, mentoring, and hands-on support to engineering and data science teams. Grow into ownership of end-to-end AI solution architecture and broader technical strategy. Government and Stakeholder Engagement Support technical discovery sessions, demonstrations, proofs of concept, proposals, RFIs, and RFP responses. Communicate complex AI concepts, limitations, risks, and tradeoffs clearly to both technical and non-technical audiences. Help move successful prototypes into secure, supportable, and scalable production capabilities. Stay informed about evolving government AI policies, standards, acquisition practices, and responsible-AI expectations. Requirement Bachelor's degree in computer science, engineering, data science, information systems, or a related field, or equivalent practical experience. Significant professional software engineering experience, including experience delivering production applications or platforms. Hands-on experience developing AI, machine-learning, or data-intensive solutions. Proficiency in Python and experience with APIs, cloud services, data pipelines, software development practices, and source control. Experience with modern generative-AI patterns, such as large language models, retrieval-augmented generation, embeddings, vector search, tool use, structured outputs, or AI agents. Understanding of cloud-native architecture, system integration, identity and access management, observability, and secure development practices. Ability to evaluate technical alternatives and explain architecture decisions and tradeoffs. Experience working across product, engineering, data, security, and business teams. Strong written and verbal communication skills. Ability to satisfy applicable government background, suitability, or contractual requirements. Incorporate security, privacy, accessibility, explainability, auditability, and human oversight into solution designs. Establish appropriate evaluation methods for accuracy, relevance, groundedness, bias, safety, and reliability. Design controls for model and prompt versioning, data lineage, access management, logging, monitoring, and traceability. Partner with cybersecurity, legal, privacy, compliance, and governance teams throughout the solution lifecycle. Ensure solutions align with applicable organizational policies, contractual obligations, and government requirements. Design human-in-the-loop controls based on the risk and impact of the decisions supported or performed by AI. Preferred Qualifications Experience delivering technology solutions for U.S. federal, state, or local government customers. Experience working in government contracting, regulated environments, or programs involving sensitive data. Familiarity with government security and compliance frameworks, such as NIST, FedRAMP, FISMA, or agency-specific controls. Experience with one or more major cloud platforms, particularly AWS, Microsoft Azure, or Google Cloud. Experience with AI orchestration frameworks, model gateways, vector databases, evaluation platforms, MLOps, or LLMOps. Understanding of model evaluation, prompt engineering, fine-tuning, data governance, and responsible-AI practices. Experience moving AI proofs of concept into production. Experience supporting technical proposals, RFIs, RFPs, solution demonstrations, or customer workshops. Prior technical leadership, mentoring, or architecture-review experience. Relevant cloud, architecture, security, data, or AI certifications. Work in a Way That Works for You We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals. Working flexible hours to help you fit everything in and work when you are the most productive Working for You We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer: Health Benefits: Comprehensive, multi-carrier program for medical, dental and vision benefits Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan Wellbeing: Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time-off Programs Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity Family Benefits, including bonding and family care leaves, adoption and surrogacy benefits Health Savings, Health Care, Dependent Care and Commuter Spending Accounts Up to two days of paid leave each to participate in Employee Resource Groups and to volunteer with your charity of choice About the Business LexisNexis Legal & Professional provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis and Nexis services. U.S. National Base Pay Range: $136,100 - $252,800. Geographic differentials may apply in some locations to better reflect local market rates. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process . click apply for full job details
Job Title: GenAI Platform Lead / Senior Python AI Engineer - LLM, RAG & FastAPI Location: Pennington, NJ / Jersey City, NJ / Charlotte, NC Duration: Contract - 12 months Pay Range: Pennington: NJ2-150-04-71 -BR $96.92 (Pay Rate: $68.25) Jersey City: NJ2-525-31-02 -BR $96.92 (Pay Rate: $68.25) Charlotte: NC1-021-03-13 BR $ 92.39 (Pay Rate: $65.06) Job ID: 412171 About BCforward BCforward is a leading global IT consulting and workforce solutions firm providing services and support to Fortune 500 and government clients. Founded in 1998, BCforward has grown with our customers needs into a full-service business solutions provider. With delivery centers and offices across North America and India, we take pride in building long-term relationships and delivering excellence through innovation, collaboration, and integrity. Job Description We are seeking an GenAI Platform Lead / Senior Python AI Engineer - LLM, RAG & FastAPI to join our team and lead the build-out of a next-generation GenAI platform. The ideal candidate will have strong experience in Python, modern microservices architectures, and AI solution delivery and a proven ability to design, implement, and scale resilient enterprise platforms that meet performance and regulatory requirements. Responsibilities: Design, develop, and oversee end-to-end implementation of the GM GenAI platform and related business use cases. Develop architectural approaches for AI software and hardware integration with emphasis on quality, performance, resiliency, and reusability. Collaborate with business and IT stakeholders to understand and fulfill business needs and objectives. Lead cross-disciplinary teams to deliver technical solutions that align with business priorities and expectations. Identify, prioritize, and execute tasks across the software development life cycle. Establish standards and drive automation to improve end-to-end SDLC efficiency. Mentor team members in technical design and development best practices. Drive platform performance, scalability, and resiliency testing. Implement hardware upgrades and software enhancements to meet global performance expectations. Address regulatory and performance-driven requirements for regional and localized infrastructure and platform deployments. Conduct research and prototyping to identify solutions that enhance platform and team capabilities. Monitor AI industry trends and advancements in AI, machine learning, and data science to continuously improve solutions. Required Skills & Qualifications: 7+ years of Python development, including production-grade services and tooling. Experience implementing and integrating LLMs, including Retrieval Augmented Generation (RAG). FastAPI or similar Python web frameworks for building APIs and microservices. Extensive experience designing and implementing multi-tier and microservices application platforms. Proven ability to plan and lead delivery with functionally diverse and geographically dispersed teams. Track record of delivering projects on time and on budget. High proficiency in Unix scripting and automation for SDLC efficiencies. In-depth knowledge of relational databases such as Oracle or MySQL and NoSQL databases such as MongoDB, including processing large structured and unstructured datasets. Knowledge of front-end languages, libraries, and frameworks such as HTML, CSS, JavaScript, XML, React, and jQuery. Strong communication, critical thinking, and problem-solving skills. Preferred Skills: Experience implementing data analytics and AI solutions in enterprise environments. Knowledge of TensorFlow or PyTorch, LLM fine-tuning, RAG patterns, and tools for agentic solutions. Additional Details: Start expectation: 2-4 weeks after offer. Candidates must be able to meet a defined start date. Please account for any potential visa-related delays before submission. Schedule: 8 hours per day. Labor Type: Technical. Assessment: GLIDER - BOA-AppProg-IV-V-3 may apply. Why BCforward? At BCforward, we believe in advancing lives and careers. When you join our team, you gain access to: Competitive compensation and benefits. Opportunities for growth with global clients. A supportive, inclusive culture that values innovation and people. Exposure to cutting-edge technologies and projects. About Our Commitment BCforward is an equal opportunity employer. We value diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, or veteran status. Interested? Apply Now! If this sounds like the right opportunity for you, please apply with your most recent resume. Ensure your preferred approved location is listed at the top of your resume.
11/14/2026
Full time
Job Title: GenAI Platform Lead / Senior Python AI Engineer - LLM, RAG & FastAPI Location: Pennington, NJ / Jersey City, NJ / Charlotte, NC Duration: Contract - 12 months Pay Range: Pennington: NJ2-150-04-71 -BR $96.92 (Pay Rate: $68.25) Jersey City: NJ2-525-31-02 -BR $96.92 (Pay Rate: $68.25) Charlotte: NC1-021-03-13 BR $ 92.39 (Pay Rate: $65.06) Job ID: 412171 About BCforward BCforward is a leading global IT consulting and workforce solutions firm providing services and support to Fortune 500 and government clients. Founded in 1998, BCforward has grown with our customers needs into a full-service business solutions provider. With delivery centers and offices across North America and India, we take pride in building long-term relationships and delivering excellence through innovation, collaboration, and integrity. Job Description We are seeking an GenAI Platform Lead / Senior Python AI Engineer - LLM, RAG & FastAPI to join our team and lead the build-out of a next-generation GenAI platform. The ideal candidate will have strong experience in Python, modern microservices architectures, and AI solution delivery and a proven ability to design, implement, and scale resilient enterprise platforms that meet performance and regulatory requirements. Responsibilities: Design, develop, and oversee end-to-end implementation of the GM GenAI platform and related business use cases. Develop architectural approaches for AI software and hardware integration with emphasis on quality, performance, resiliency, and reusability. Collaborate with business and IT stakeholders to understand and fulfill business needs and objectives. Lead cross-disciplinary teams to deliver technical solutions that align with business priorities and expectations. Identify, prioritize, and execute tasks across the software development life cycle. Establish standards and drive automation to improve end-to-end SDLC efficiency. Mentor team members in technical design and development best practices. Drive platform performance, scalability, and resiliency testing. Implement hardware upgrades and software enhancements to meet global performance expectations. Address regulatory and performance-driven requirements for regional and localized infrastructure and platform deployments. Conduct research and prototyping to identify solutions that enhance platform and team capabilities. Monitor AI industry trends and advancements in AI, machine learning, and data science to continuously improve solutions. Required Skills & Qualifications: 7+ years of Python development, including production-grade services and tooling. Experience implementing and integrating LLMs, including Retrieval Augmented Generation (RAG). FastAPI or similar Python web frameworks for building APIs and microservices. Extensive experience designing and implementing multi-tier and microservices application platforms. Proven ability to plan and lead delivery with functionally diverse and geographically dispersed teams. Track record of delivering projects on time and on budget. High proficiency in Unix scripting and automation for SDLC efficiencies. In-depth knowledge of relational databases such as Oracle or MySQL and NoSQL databases such as MongoDB, including processing large structured and unstructured datasets. Knowledge of front-end languages, libraries, and frameworks such as HTML, CSS, JavaScript, XML, React, and jQuery. Strong communication, critical thinking, and problem-solving skills. Preferred Skills: Experience implementing data analytics and AI solutions in enterprise environments. Knowledge of TensorFlow or PyTorch, LLM fine-tuning, RAG patterns, and tools for agentic solutions. Additional Details: Start expectation: 2-4 weeks after offer. Candidates must be able to meet a defined start date. Please account for any potential visa-related delays before submission. Schedule: 8 hours per day. Labor Type: Technical. Assessment: GLIDER - BOA-AppProg-IV-V-3 may apply. Why BCforward? At BCforward, we believe in advancing lives and careers. When you join our team, you gain access to: Competitive compensation and benefits. Opportunities for growth with global clients. A supportive, inclusive culture that values innovation and people. Exposure to cutting-edge technologies and projects. About Our Commitment BCforward is an equal opportunity employer. We value diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, or veteran status. Interested? Apply Now! If this sounds like the right opportunity for you, please apply with your most recent resume. Ensure your preferred approved location is listed at the top of your resume.
Description: GXM is seeking a full-time Enterprise Architect to support enterprise architecture development, digital engineering initiatives, and strategic mission integration activities supporting advanced operational Command and Control (C2) environments. The ideal candidate will possess deep expertise in Enterprise Architecture, operational mission systems, Digital Engineering, and Model-Based Systems Engineering (MBSE) with the ability to architect scalable operational solutions across cloud infrastructure, mission applications, operational data environments, cyber security domains and distributed mission systems. This role serves as the strategic architecture authority responsible for defining the target state operational architecture, integrations standards, interoperability frameworks, and long-term scalability model supporting integrated multi-domain mission operations. This individual will support modernization initiatives involving integrated C2 architectures, cloud-native mission systems, operational data fusion environments, AI/ML-enabled analytics platforms, and Joint Force operational integration constructs across defense environments. This role is onsite in Colorado Springs, CO. Hybrid flexibility may be available over time based on mission requirements, program execution needs and achievement of objectives. Responsibilities Serve as the strategic architecture authority for integrated multi-domain C2 mission environment. Develop and maintain enterprise and operational system architectures supporting integrated operational and mission environments. Define and maintain the overall C2 architecture baseline, including operational concepts, integration standards, interface strategies, interoperability frameworks, and long-term scalability models. Apply Model-Based Systems Engineering (MBSE) methodologies to support system architecture development, requirements traceability, integration planning, digital engineering and lifecycle engineering activities. Develop and maintain engineering artifacts, system models, interface definitions, and architecture products, operational workflows, and reference architectures supporting integrated mission operations. Utilize MBSE tools and enterprise architecture frameworks to support digital engineering and operational mission architecture activities. Develop integrated engineering execution plans and schedules using Cameo Systems Modeler or similar enterprise planning tools. Architect scalable cloud, hybrid-cloud, and distributed system environments supporting operational mission needs. Define enterprise integration standards supporting APIs, middleware, event-driven architectures, operational data exchange frameworks, and mission interoperability requirements. Contribute to technical solution development involving AI/ML-enabled operation analytics, DevSecOps pipelines, cybersecurity architectures, software engineering, and operational data fusion capabilities. Develop integrated engineering execution roadmaps, transition architectures, modernization strategies, and scalability frameworks supporting follow-on operational deployment. Collaborate with engineering teams, leadership, and government stakeholders to refine operational mission architectures. Requirements: U.S. Citizen and Active TS/SCI clearance required. Bachelor's degree in systems engineering, Computer Science, Engineering, Information Systems, or related technical field. 8+ years of experience supporting enterprise architecture, operational mission systems, systems engineering, or strategic modernization initiatives within defense or intelligence environments. Strong understanding of Enterprise Architecture, Digital Engineering, and Model-Based Systems Engineering (MBSE) principles. Experience defining architecture governance standards, integration frameworks, interface strategies, and target-state operational architecture. Experience developing enterprise/system architectures, engineering artifacts, integration strategies, and operational workflows. Experience using Cameo Systems Modeler or other Digital Engineering toolsets to develop operational architecture products, integrated engineering execution models, system interaction diagrams, mission workflows, interface definitions, and requirements traceability artifacts supporting complex mission and operational environments. Understanding of cloud architectures, DevSecOps, cybersecurity, AI/ML, system integration, and enterprise modernization approaches. Strong communication, collaboration, and technical writing skills. Proven ability to communicate complex technical architectures to Government leadership, operational stakeholders, and engineering teams. Desired Qualifications Experience supporting defense, space, or multi-domain operational environments. Experience supporting DoD, federal mission systems, enterprise modernization, or operational C2 environments. Experience with MBSE tools such as Cameo Systems Modeler or other Digital Engineering tools. Expert with DoDAF, UAF, SysML, BPMN, and related enterprise architecture, operational architecture, MBSE frameworks supporting DoD mission engineering and digital engineering initiatives. Experience with enterprise cloud platforms, cloud-native and hybrid-cloud environments, container orchestration technologies, and distributed mission infrastructure supporting secure operational workloads. Knowledge of RMF, DISA STIGs, and Zero Trust cybersecurity frameworks. Experience supporting proposals, capture, or strategic modernization efforts for federal or defense programs. $150,000-$235,000 salary + annual bonus eligibility + medical/dental/vision/STD/LTD/Life + 401(k) + PTO Equal Employment Opportunity / Legal Disclaimer GXM Technologies LLC is an Equal Opportunity Employer and participates in E-Verify to confirm employment eligibility. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy), sexual orientation, gender identity, national origin, age, disability, genetic information, veteran status, or any other legally protected status. GXM Technologies LLC provides reasonable accommodations in accordance with applicable law. This job description is not intended to be a complete list of duties and responsibilities, which may change at any time with or without notice. Employment is at-will where permitted by law , meaning either the employee or the Company may terminate employment at any time, with or without cause or notice, subject to applicable legal requirements. PIc68a4-6194
11/13/2026
Full time
Description: GXM is seeking a full-time Enterprise Architect to support enterprise architecture development, digital engineering initiatives, and strategic mission integration activities supporting advanced operational Command and Control (C2) environments. The ideal candidate will possess deep expertise in Enterprise Architecture, operational mission systems, Digital Engineering, and Model-Based Systems Engineering (MBSE) with the ability to architect scalable operational solutions across cloud infrastructure, mission applications, operational data environments, cyber security domains and distributed mission systems. This role serves as the strategic architecture authority responsible for defining the target state operational architecture, integrations standards, interoperability frameworks, and long-term scalability model supporting integrated multi-domain mission operations. This individual will support modernization initiatives involving integrated C2 architectures, cloud-native mission systems, operational data fusion environments, AI/ML-enabled analytics platforms, and Joint Force operational integration constructs across defense environments. This role is onsite in Colorado Springs, CO. Hybrid flexibility may be available over time based on mission requirements, program execution needs and achievement of objectives. Responsibilities Serve as the strategic architecture authority for integrated multi-domain C2 mission environment. Develop and maintain enterprise and operational system architectures supporting integrated operational and mission environments. Define and maintain the overall C2 architecture baseline, including operational concepts, integration standards, interface strategies, interoperability frameworks, and long-term scalability models. Apply Model-Based Systems Engineering (MBSE) methodologies to support system architecture development, requirements traceability, integration planning, digital engineering and lifecycle engineering activities. Develop and maintain engineering artifacts, system models, interface definitions, and architecture products, operational workflows, and reference architectures supporting integrated mission operations. Utilize MBSE tools and enterprise architecture frameworks to support digital engineering and operational mission architecture activities. Develop integrated engineering execution plans and schedules using Cameo Systems Modeler or similar enterprise planning tools. Architect scalable cloud, hybrid-cloud, and distributed system environments supporting operational mission needs. Define enterprise integration standards supporting APIs, middleware, event-driven architectures, operational data exchange frameworks, and mission interoperability requirements. Contribute to technical solution development involving AI/ML-enabled operation analytics, DevSecOps pipelines, cybersecurity architectures, software engineering, and operational data fusion capabilities. Develop integrated engineering execution roadmaps, transition architectures, modernization strategies, and scalability frameworks supporting follow-on operational deployment. Collaborate with engineering teams, leadership, and government stakeholders to refine operational mission architectures. Requirements: U.S. Citizen and Active TS/SCI clearance required. Bachelor's degree in systems engineering, Computer Science, Engineering, Information Systems, or related technical field. 8+ years of experience supporting enterprise architecture, operational mission systems, systems engineering, or strategic modernization initiatives within defense or intelligence environments. Strong understanding of Enterprise Architecture, Digital Engineering, and Model-Based Systems Engineering (MBSE) principles. Experience defining architecture governance standards, integration frameworks, interface strategies, and target-state operational architecture. Experience developing enterprise/system architectures, engineering artifacts, integration strategies, and operational workflows. Experience using Cameo Systems Modeler or other Digital Engineering toolsets to develop operational architecture products, integrated engineering execution models, system interaction diagrams, mission workflows, interface definitions, and requirements traceability artifacts supporting complex mission and operational environments. Understanding of cloud architectures, DevSecOps, cybersecurity, AI/ML, system integration, and enterprise modernization approaches. Strong communication, collaboration, and technical writing skills. Proven ability to communicate complex technical architectures to Government leadership, operational stakeholders, and engineering teams. Desired Qualifications Experience supporting defense, space, or multi-domain operational environments. Experience supporting DoD, federal mission systems, enterprise modernization, or operational C2 environments. Experience with MBSE tools such as Cameo Systems Modeler or other Digital Engineering tools. Expert with DoDAF, UAF, SysML, BPMN, and related enterprise architecture, operational architecture, MBSE frameworks supporting DoD mission engineering and digital engineering initiatives. Experience with enterprise cloud platforms, cloud-native and hybrid-cloud environments, container orchestration technologies, and distributed mission infrastructure supporting secure operational workloads. Knowledge of RMF, DISA STIGs, and Zero Trust cybersecurity frameworks. Experience supporting proposals, capture, or strategic modernization efforts for federal or defense programs. $150,000-$235,000 salary + annual bonus eligibility + medical/dental/vision/STD/LTD/Life + 401(k) + PTO Equal Employment Opportunity / Legal Disclaimer GXM Technologies LLC is an Equal Opportunity Employer and participates in E-Verify to confirm employment eligibility. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy), sexual orientation, gender identity, national origin, age, disability, genetic information, veteran status, or any other legally protected status. GXM Technologies LLC provides reasonable accommodations in accordance with applicable law. This job description is not intended to be a complete list of duties and responsibilities, which may change at any time with or without notice. Employment is at-will where permitted by law , meaning either the employee or the Company may terminate employment at any time, with or without cause or notice, subject to applicable legal requirements. PIc68a4-6194
Position summary The Solutions Development Manager leads the design, development, and delivery of innovative software solutions that enhance legal practices and enterprise support functions. This role partners with stakeholders to translate complex requirements into technology solutions, overseeing assigned global platforms, system integrations, and software development projects while managing resources, monitoring project costs, and ensuring compliance with security, regulatory, and internal policies. The Manager leads a team of Analysts and Developers and drives the adoption of emerging technologies to support operational efficiency and transformative business outcomes. Job duties and responsibilities Lead the design, development, and implementation of tailored technology solutions for practice groups, attorneys, and clients, ensuring alignment with the firm's strategic objectives and enterprise technology roadmap. Partner with senior stakeholders to define requirements, evaluate technical solution options, recommend innovative solutions, and lead the implementation of assigned complex projects and system integrations. Lead and manage software development projects, including defining scope, allocating resources, managing deliverables, and coordinating vendor support to ensure successful outcomes. Develop project cost estimates and track project expenditures. Identify and assess risks associated with assigned technology solutions and projects, implement appropriate mitigation measures within established authority, and escalate significant risks to leadership. Ensure compliance with regulatory requirements, data privacy standards, and cybersecurity protocols. Monitor key performance indicators (KPIs) and success metrics for assigned technology solutions and development teams, using performance data to identify opportunities for continuous improvement. Communicate project status, risks, and recommendations to stakeholders and leadership, ensuring timely escalation of significant issues and supporting informed decision-making. Oversee the production and maintenance of assigned projects and platforms, including implementation strategies, project plans, cost analyses, and compliance records, adhering to firm standards, regulatory requirements, and cybersecurity best practices. Manage assigned global platforms such as intranet, extranet, room scheduling, and business intelligence (BI) systems, ensuring reliability, scalability, and continuous improvement. Champion the adoption and integration of emerging technologies, including cloud computing, automation, and artificial intelligence, to drive operational efficiency and innovation. Lead, mentor, and develop a team of Analysts and Developers, including hiring, performance management, and coaching to support team effectiveness and professional development. Establish, refine, and enforce software development policies, methodologies, best practices, and security standards, under the directorion of the Assistant Director, ensuring firm requirements, alignment with industry advancements and compliance obligations. Represent Solutions Development on firmwide committees, governance boards, or cross-functional project teams, providing technical expertise and contributing to enterprise technology initiatives. Perform other duties as assigned. Job duties and responsibilities included are not exhaustive and may be supplemented asnecessary. Reed Smith reserves the right to revise or modify job duties and responsibilities at any time. Requirements Education: Bachelor's Degree in an IT-related discipline is required. A Master's Degree and other relevant training, education, and certifications are preferred. Experience: Minimum of 7 years of software development experience, including expertise with React, MS SQL, and enterprise system integrations. Minimum of 3 years of experience leading or managing technical teams. Experience leading complex software development projects using Agile and DevOps methodologies. Expertise with BI platforms (Power BI, Tableau) and enterprise data visualization, analytics, and dashboard strategy. Deep knowledge of SharePoint-based intranet/extranet development and large-scale platform customization. Experience implementing emerging technologies, including cloud, AI, and automation, to support enterprise technology initiatives. Experience coordinating vendor relationships, including overseeing technical deliverables and evaluating third-party performance. Experience in a law firm or professional services environment strongly preferred. Skills: Demonstrated management and supervisory capability, leading, mentoring, and developing global technical teams. Strong knowledge of software development methodologies, system architecture, integrations, and enterprise platforms supporting the firm's technology environment. Strong project management capability, defining scope, allocating resources, managing deliverables, and overseeing multiple concurrent initiatives. Strong written and oral communication skills, presenting complex technical information clearly to senior leadership and diverse stakeholders. High degree of professionalism, discretion, and sound judgment, with the flexibility and adaptability to respond effectively in complex, dynamic, or rapidly evolving situations. Analytical and critical thinking capability, including defining KPIs, interpreting data, and using insights to drive continuous improvement. Ability to prioritize work effectively, manage competing responsibilities, and meet established timelines. Capable of working independently and collaboratively, including leading and supporting a team in a remote or hybrid work environment. Additional information Supervisory responsibilities: IT Solutions Development Team Equipment used: Personal computer and other office equipment such as telephone, calculator, copier, scanner, etc. Essential job functions Ability to sit or stand for extended periods and perform tasks requiring prolonged and/or extensive computer use. Ability to use computers, telecommunications, and digital collaboration tools to perform core job responsibilities. Ability to engage in effective and professional communication. Ability to analyze complex information while maintaining attention to detail, managing multiple priorities, and exercising sound judgment in decision-making. Ability to access, use, and safeguard confidential and sensitive information while performing job responsibilities in work environments that support confidentiality, privacy, and information security requirements. Ability to work extended or adjusted hours as needed, including evenings, weekends, holidays, and early start times to support collaboration with international stakeholders across EMEA and the US, and to meet business, operational, or project needs. Ability to work in-office as required to meet business or project needs. Working conditions You will be required to work in the office at minimum 4 days per week. Occasionally called upon to work hours in excess of your normal daily schedule. The details of your weekly schedule will be discussed further with your direct supervisor. Pay ranges This represents the presently anticipated low and high end of Reed Smith's pay range for this position. Actual pay may vary based on various factors, including but not limited to location and experience. Pittsburgh: $148,000 - $162,000 Employee benefits overview Our comprehensive benefits package includes: 401(k) Retirement Plan Medical Insurance Health Savings Account (HSA) Virtual Health Services Dental Insurance Vision Insurance Accident Insurance Hospital Indemnity Insurance Critical Illness Insurance Life Insurance Short-Term Disability Coverage Long-Term Disability Coverage Flexible Spending Accounts (FSA) Lyra Health Employee Assistance Program (EAP) Paid Family Leave (for eligible Exempt and Non-Exempt staff) Transportation Benefit Back-up Child Care Services College Coach Program Pet Insurance Paid Sick Time (for Exempt staff) Paid Time Off (available to all full-time, non-temporary employees) Reed Smith offers a challenging work environment, business casual dress code and a total compensation package that includes a competitive salary, flexible benefits program, tuition assistance, and generous 401(k) plan. Reed Smith is an Equal Opportunity Employer with Core Values of Integrity, Excellence, Teamwork & Respect, Innovation, and Impact. Reed Smith also provides reasonable accommodations in accordance with law, including in the application and interview process. Qualified candidates only. No search firms.
11/13/2026
Full time
Position summary The Solutions Development Manager leads the design, development, and delivery of innovative software solutions that enhance legal practices and enterprise support functions. This role partners with stakeholders to translate complex requirements into technology solutions, overseeing assigned global platforms, system integrations, and software development projects while managing resources, monitoring project costs, and ensuring compliance with security, regulatory, and internal policies. The Manager leads a team of Analysts and Developers and drives the adoption of emerging technologies to support operational efficiency and transformative business outcomes. Job duties and responsibilities Lead the design, development, and implementation of tailored technology solutions for practice groups, attorneys, and clients, ensuring alignment with the firm's strategic objectives and enterprise technology roadmap. Partner with senior stakeholders to define requirements, evaluate technical solution options, recommend innovative solutions, and lead the implementation of assigned complex projects and system integrations. Lead and manage software development projects, including defining scope, allocating resources, managing deliverables, and coordinating vendor support to ensure successful outcomes. Develop project cost estimates and track project expenditures. Identify and assess risks associated with assigned technology solutions and projects, implement appropriate mitigation measures within established authority, and escalate significant risks to leadership. Ensure compliance with regulatory requirements, data privacy standards, and cybersecurity protocols. Monitor key performance indicators (KPIs) and success metrics for assigned technology solutions and development teams, using performance data to identify opportunities for continuous improvement. Communicate project status, risks, and recommendations to stakeholders and leadership, ensuring timely escalation of significant issues and supporting informed decision-making. Oversee the production and maintenance of assigned projects and platforms, including implementation strategies, project plans, cost analyses, and compliance records, adhering to firm standards, regulatory requirements, and cybersecurity best practices. Manage assigned global platforms such as intranet, extranet, room scheduling, and business intelligence (BI) systems, ensuring reliability, scalability, and continuous improvement. Champion the adoption and integration of emerging technologies, including cloud computing, automation, and artificial intelligence, to drive operational efficiency and innovation. Lead, mentor, and develop a team of Analysts and Developers, including hiring, performance management, and coaching to support team effectiveness and professional development. Establish, refine, and enforce software development policies, methodologies, best practices, and security standards, under the directorion of the Assistant Director, ensuring firm requirements, alignment with industry advancements and compliance obligations. Represent Solutions Development on firmwide committees, governance boards, or cross-functional project teams, providing technical expertise and contributing to enterprise technology initiatives. Perform other duties as assigned. Job duties and responsibilities included are not exhaustive and may be supplemented asnecessary. Reed Smith reserves the right to revise or modify job duties and responsibilities at any time. Requirements Education: Bachelor's Degree in an IT-related discipline is required. A Master's Degree and other relevant training, education, and certifications are preferred. Experience: Minimum of 7 years of software development experience, including expertise with React, MS SQL, and enterprise system integrations. Minimum of 3 years of experience leading or managing technical teams. Experience leading complex software development projects using Agile and DevOps methodologies. Expertise with BI platforms (Power BI, Tableau) and enterprise data visualization, analytics, and dashboard strategy. Deep knowledge of SharePoint-based intranet/extranet development and large-scale platform customization. Experience implementing emerging technologies, including cloud, AI, and automation, to support enterprise technology initiatives. Experience coordinating vendor relationships, including overseeing technical deliverables and evaluating third-party performance. Experience in a law firm or professional services environment strongly preferred. Skills: Demonstrated management and supervisory capability, leading, mentoring, and developing global technical teams. Strong knowledge of software development methodologies, system architecture, integrations, and enterprise platforms supporting the firm's technology environment. Strong project management capability, defining scope, allocating resources, managing deliverables, and overseeing multiple concurrent initiatives. Strong written and oral communication skills, presenting complex technical information clearly to senior leadership and diverse stakeholders. High degree of professionalism, discretion, and sound judgment, with the flexibility and adaptability to respond effectively in complex, dynamic, or rapidly evolving situations. Analytical and critical thinking capability, including defining KPIs, interpreting data, and using insights to drive continuous improvement. Ability to prioritize work effectively, manage competing responsibilities, and meet established timelines. Capable of working independently and collaboratively, including leading and supporting a team in a remote or hybrid work environment. Additional information Supervisory responsibilities: IT Solutions Development Team Equipment used: Personal computer and other office equipment such as telephone, calculator, copier, scanner, etc. Essential job functions Ability to sit or stand for extended periods and perform tasks requiring prolonged and/or extensive computer use. Ability to use computers, telecommunications, and digital collaboration tools to perform core job responsibilities. Ability to engage in effective and professional communication. Ability to analyze complex information while maintaining attention to detail, managing multiple priorities, and exercising sound judgment in decision-making. Ability to access, use, and safeguard confidential and sensitive information while performing job responsibilities in work environments that support confidentiality, privacy, and information security requirements. Ability to work extended or adjusted hours as needed, including evenings, weekends, holidays, and early start times to support collaboration with international stakeholders across EMEA and the US, and to meet business, operational, or project needs. Ability to work in-office as required to meet business or project needs. Working conditions You will be required to work in the office at minimum 4 days per week. Occasionally called upon to work hours in excess of your normal daily schedule. The details of your weekly schedule will be discussed further with your direct supervisor. Pay ranges This represents the presently anticipated low and high end of Reed Smith's pay range for this position. Actual pay may vary based on various factors, including but not limited to location and experience. Pittsburgh: $148,000 - $162,000 Employee benefits overview Our comprehensive benefits package includes: 401(k) Retirement Plan Medical Insurance Health Savings Account (HSA) Virtual Health Services Dental Insurance Vision Insurance Accident Insurance Hospital Indemnity Insurance Critical Illness Insurance Life Insurance Short-Term Disability Coverage Long-Term Disability Coverage Flexible Spending Accounts (FSA) Lyra Health Employee Assistance Program (EAP) Paid Family Leave (for eligible Exempt and Non-Exempt staff) Transportation Benefit Back-up Child Care Services College Coach Program Pet Insurance Paid Sick Time (for Exempt staff) Paid Time Off (available to all full-time, non-temporary employees) Reed Smith offers a challenging work environment, business casual dress code and a total compensation package that includes a competitive salary, flexible benefits program, tuition assistance, and generous 401(k) plan. Reed Smith is an Equal Opportunity Employer with Core Values of Integrity, Excellence, Teamwork & Respect, Innovation, and Impact. Reed Smith also provides reasonable accommodations in accordance with law, including in the application and interview process. Qualified candidates only. No search firms.
Job Title: Enterprise AI Architect - GenAI / Agentic AI / RAG / AI Governance Location: Plano, TX (Local candidates only. Hybrid, 3 days onsite per week required.) Duration: Contract - 12 months Pay Range: $73.67/hr (W2) Job ID: 412083 About BCforward BCforward is a leading global IT consulting and workforce solutions firm providing services and support to Fortune 500 and government clients. Founded in 1998, BCforward has grown with our customers needs into a full-service business solutions provider. With delivery centers and offices across North America and India, we take pride in building long-term relationships and delivering excellence through innovation, collaboration, and integrity. Job Description We are seeking an experienced Enterprise AI Architect - GenAI / Agentic AI / RAG / AI Governance to serve as a senior AI architecture leader responsible for defining enterprise patterns, standards, and decision frameworks that guide the adoption of AI across Global Technology. The ideal candidate will demonstrate strong experience in AI platforms, agentic systems, retrieval architectures, model integration, workflow automation, and enterprise AI governance, with a proven ability to translate rapidly evolving AI capabilities into practical, scalable, and governed enterprise solutions while partnering closely with CIO architecture teams, platform engineering, security, and risk. Responsibilities: Define enterprise AI architecture strategy, patterns, and reference architectures. Establish decision frameworks for AI platform selection, solution design, and deployment approaches. Develop governance models, standards, and guardrails for AI and agentic solutions. Drive consistency and reuse through enterprise AI patterns, templates, and guidance artifacts. Align AI architecture with enterprise security, risk, compliance, and control requirements. Define architecture patterns for enterprise AI agents, multi-agent systems, and workflow automation. Establish guidance for agent orchestration, planning, memory, tool invocation, and human oversight. Drive standards for deterministic, probabilistic, and hybrid automation models. Define integration patterns for agent-to-agent communication, tool usage, and enterprise workflows. Guide adoption of emerging AI interoperability standards and architectures, including MCP where applicable. Develop decision guidance for model selection, orchestration approaches, and AI solution architectures. Partner with platform teams to align enterprise AI capabilities with business and technology needs. Define patterns for RAG, vector databases, semantic retrieval, and enterprise knowledge architectures. Guide architecture decisions for AI-ready data access, grounding, and contextual retrieval. Guide architecture decisions involving AI Gateway, API Gateway, and MCP Gateway capabilities. Embed security through architecture patterns covering identity, access, data protection, and policy enforcement. Translate complex AI concepts into clear, actionable guidance for technical and business audiences. Communicate effectively with senior stakeholders on business value, risk, operating models, and technology choices. Act as a senior AI architecture leader driving alignment across multiple organizations and initiatives. Promote responsible AI adoption through practical governance and architectural guardrails. Required Skills & Qualifications: 15+ years in enterprise architecture, solution architecture, software engineering, or distributed systems design. 8+ years architecting AI/ML, NLP, or advanced analytics solutions. 2+ years designing enterprise GenAI, RAG, and agentic AI solutions. Strong knowledge of LLMs, RAG, embeddings, vector databases, evaluation frameworks, and agent-based architectures. Experience with enterprise AI platforms such as Microsoft Copilot Studio, Azure AI services, and Azure OpenAI or equivalents. Familiarity with AI orchestration frameworks, workflow automation, and enterprise integration patterns. Understanding of security, governance, privacy, and risk considerations for AI solutions. Proven ability to influence senior stakeholders and drive architecture decisions in regulated environments. Strong communication skills with the ability to simplify complex AI concepts and drive alignment across technical and business audiences. Preferred Skills: Experience with agentic AI, multi-agent systems, MCP, and emerging AI interoperability standards. Experience with Microsoft AI ecosystem capabilities including Copilot Studio, Azure AI Foundry, Azure OpenAI, and GitHub Copilot. Experience with AWS AI services including Amazon Bedrock, SageMaker, and AI application architectures. Knowledge of knowledge graphs, semantic search, vector databases, and enterprise retrieval architectures. Experience defining AI governance, model lifecycle management, and responsible AI practices. Experience operating in large-scale, highly regulated enterprise environments. Why BCforward? At BCforward, we believe in advancing lives and careers. When you join our team, you gain access to: Competitive compensation and benefits. Opportunities for growth with global clients. A supportive, inclusive culture that values innovation and people. Exposure to cutting-edge technologies and projects. About Our Commitment BCforward is an equal opportunity employer. We value diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, or veteran status. Interested? Apply Now! If this sounds like the right opportunity for you, please apply with your most recent resume.
11/13/2026
Full time
Job Title: Enterprise AI Architect - GenAI / Agentic AI / RAG / AI Governance Location: Plano, TX (Local candidates only. Hybrid, 3 days onsite per week required.) Duration: Contract - 12 months Pay Range: $73.67/hr (W2) Job ID: 412083 About BCforward BCforward is a leading global IT consulting and workforce solutions firm providing services and support to Fortune 500 and government clients. Founded in 1998, BCforward has grown with our customers needs into a full-service business solutions provider. With delivery centers and offices across North America and India, we take pride in building long-term relationships and delivering excellence through innovation, collaboration, and integrity. Job Description We are seeking an experienced Enterprise AI Architect - GenAI / Agentic AI / RAG / AI Governance to serve as a senior AI architecture leader responsible for defining enterprise patterns, standards, and decision frameworks that guide the adoption of AI across Global Technology. The ideal candidate will demonstrate strong experience in AI platforms, agentic systems, retrieval architectures, model integration, workflow automation, and enterprise AI governance, with a proven ability to translate rapidly evolving AI capabilities into practical, scalable, and governed enterprise solutions while partnering closely with CIO architecture teams, platform engineering, security, and risk. Responsibilities: Define enterprise AI architecture strategy, patterns, and reference architectures. Establish decision frameworks for AI platform selection, solution design, and deployment approaches. Develop governance models, standards, and guardrails for AI and agentic solutions. Drive consistency and reuse through enterprise AI patterns, templates, and guidance artifacts. Align AI architecture with enterprise security, risk, compliance, and control requirements. Define architecture patterns for enterprise AI agents, multi-agent systems, and workflow automation. Establish guidance for agent orchestration, planning, memory, tool invocation, and human oversight. Drive standards for deterministic, probabilistic, and hybrid automation models. Define integration patterns for agent-to-agent communication, tool usage, and enterprise workflows. Guide adoption of emerging AI interoperability standards and architectures, including MCP where applicable. Develop decision guidance for model selection, orchestration approaches, and AI solution architectures. Partner with platform teams to align enterprise AI capabilities with business and technology needs. Define patterns for RAG, vector databases, semantic retrieval, and enterprise knowledge architectures. Guide architecture decisions for AI-ready data access, grounding, and contextual retrieval. Guide architecture decisions involving AI Gateway, API Gateway, and MCP Gateway capabilities. Embed security through architecture patterns covering identity, access, data protection, and policy enforcement. Translate complex AI concepts into clear, actionable guidance for technical and business audiences. Communicate effectively with senior stakeholders on business value, risk, operating models, and technology choices. Act as a senior AI architecture leader driving alignment across multiple organizations and initiatives. Promote responsible AI adoption through practical governance and architectural guardrails. Required Skills & Qualifications: 15+ years in enterprise architecture, solution architecture, software engineering, or distributed systems design. 8+ years architecting AI/ML, NLP, or advanced analytics solutions. 2+ years designing enterprise GenAI, RAG, and agentic AI solutions. Strong knowledge of LLMs, RAG, embeddings, vector databases, evaluation frameworks, and agent-based architectures. Experience with enterprise AI platforms such as Microsoft Copilot Studio, Azure AI services, and Azure OpenAI or equivalents. Familiarity with AI orchestration frameworks, workflow automation, and enterprise integration patterns. Understanding of security, governance, privacy, and risk considerations for AI solutions. Proven ability to influence senior stakeholders and drive architecture decisions in regulated environments. Strong communication skills with the ability to simplify complex AI concepts and drive alignment across technical and business audiences. Preferred Skills: Experience with agentic AI, multi-agent systems, MCP, and emerging AI interoperability standards. Experience with Microsoft AI ecosystem capabilities including Copilot Studio, Azure AI Foundry, Azure OpenAI, and GitHub Copilot. Experience with AWS AI services including Amazon Bedrock, SageMaker, and AI application architectures. Knowledge of knowledge graphs, semantic search, vector databases, and enterprise retrieval architectures. Experience defining AI governance, model lifecycle management, and responsible AI practices. Experience operating in large-scale, highly regulated enterprise environments. Why BCforward? At BCforward, we believe in advancing lives and careers. When you join our team, you gain access to: Competitive compensation and benefits. Opportunities for growth with global clients. A supportive, inclusive culture that values innovation and people. Exposure to cutting-edge technologies and projects. About Our Commitment BCforward is an equal opportunity employer. We value diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, or veteran status. Interested? Apply Now! If this sounds like the right opportunity for you, please apply with your most recent resume.
Job Title: Enterprise Observability Architect - OpenTelemetry & AIOps Position Overview Drive enterprise-wide observability transformation by defining architecture strategies, establishing governance standards, and building unified monitoring ecosystems across complex technology environments. This role offers an opportunity to lead OpenTelemetry adoption, architect telemetry pipelines, integrate enterprise observability platforms, and advance proactive monitoring and AIOps capabilities. The position requires deep Infrastructure & Operations expertise, enterprise architecture experience, and the ability to collaborate with cross-functional technology teams and executive stakeholders. What You'll Do / Key Responsibilities Define enterprise observability strategy, standards, and governance. Architect and lead OpenTelemetry adoption across infrastructure and applications. Design telemetry pipelines for metrics, logs, traces, and events. Integrate Observe, Dynatrace, SolarWinds, Snowflake, and other monitoring platforms into a unified observability ecosystem. Establish service health, business service monitoring, SLOs, SLIs, and reliability KPIs. Drive observability transformation from reactive monitoring to proactive detection and predictive analytics. Develop architecture patterns for cloud, on-premises, hybrid, and Kubernetes/OpenShift environments. Partner with Infrastructure, Operations, Application, Network, Security, and Platform teams. Enable AI/AIOps use cases through telemetry standardization and data engineering practices. Lead root cause analysis improvements, incident reduction initiatives, and operational excellence programs. Provide technical leadership, roadmaps, governance, and executive-level recommendations. Required Qualifications Expert knowledge of OpenTelemetry architecture and instrumentation. Strong experience with Observe, Dynatrace, SolarWinds, Splunk, Datadog, or similar observability platforms. Deep understanding of Infrastructure & Operations, cloud platforms, Linux, Windows, Kubernetes/OpenShift, networking, and databases. Experience with telemetry data pipelines, APIs, automation, and observability architectures. Strong stakeholder engagement and executive communication skills. 12-18+ years of overall IT Infrastructure/Operations experience. 5+ years of observability/monitoring architecture experience. Preferred Qualifications Experience working in enterprise-scale environments. Fortune 500 enterprise experience preferred. What Makes HTC A Great Place To Build Your Future HTC Global Services wants you to join our team. Come build new things with us and advance your career. At HTC Global, you'll collaborate with experts, work alongside clients, and be part of high-performing teams driving success together. You'll have long-term opportunities to grow your career and develop skills in the latest emerging technologies. At HTC Global Services, our employees have access to a comprehensive benefits package. Benefits can include Group Health (Medical, Dental, and Vision), Paid Time Off, Paid Holidays, 401(k) matching, Group Life and Disability insurance, Professional Development opportunities, Wellness programs, and a variety of other perks. Our success as a company is built on inclusion and diversity. HTC Global Services is committed to providing a workplace free from discrimination and harassment, where every employee is treated with dignity and respect. We celebrate differences and believe that diverse cultures, perspectives, and skills drive innovation and success. HTC is an Equal Opportunity Employer and a proud National Minority Supplier. We seek to empower each individual, fostering an environment where everyone feels valued, included, and respected.
11/13/2026
Full time
Job Title: Enterprise Observability Architect - OpenTelemetry & AIOps Position Overview Drive enterprise-wide observability transformation by defining architecture strategies, establishing governance standards, and building unified monitoring ecosystems across complex technology environments. This role offers an opportunity to lead OpenTelemetry adoption, architect telemetry pipelines, integrate enterprise observability platforms, and advance proactive monitoring and AIOps capabilities. The position requires deep Infrastructure & Operations expertise, enterprise architecture experience, and the ability to collaborate with cross-functional technology teams and executive stakeholders. What You'll Do / Key Responsibilities Define enterprise observability strategy, standards, and governance. Architect and lead OpenTelemetry adoption across infrastructure and applications. Design telemetry pipelines for metrics, logs, traces, and events. Integrate Observe, Dynatrace, SolarWinds, Snowflake, and other monitoring platforms into a unified observability ecosystem. Establish service health, business service monitoring, SLOs, SLIs, and reliability KPIs. Drive observability transformation from reactive monitoring to proactive detection and predictive analytics. Develop architecture patterns for cloud, on-premises, hybrid, and Kubernetes/OpenShift environments. Partner with Infrastructure, Operations, Application, Network, Security, and Platform teams. Enable AI/AIOps use cases through telemetry standardization and data engineering practices. Lead root cause analysis improvements, incident reduction initiatives, and operational excellence programs. Provide technical leadership, roadmaps, governance, and executive-level recommendations. Required Qualifications Expert knowledge of OpenTelemetry architecture and instrumentation. Strong experience with Observe, Dynatrace, SolarWinds, Splunk, Datadog, or similar observability platforms. Deep understanding of Infrastructure & Operations, cloud platforms, Linux, Windows, Kubernetes/OpenShift, networking, and databases. Experience with telemetry data pipelines, APIs, automation, and observability architectures. Strong stakeholder engagement and executive communication skills. 12-18+ years of overall IT Infrastructure/Operations experience. 5+ years of observability/monitoring architecture experience. Preferred Qualifications Experience working in enterprise-scale environments. Fortune 500 enterprise experience preferred. What Makes HTC A Great Place To Build Your Future HTC Global Services wants you to join our team. Come build new things with us and advance your career. At HTC Global, you'll collaborate with experts, work alongside clients, and be part of high-performing teams driving success together. You'll have long-term opportunities to grow your career and develop skills in the latest emerging technologies. At HTC Global Services, our employees have access to a comprehensive benefits package. Benefits can include Group Health (Medical, Dental, and Vision), Paid Time Off, Paid Holidays, 401(k) matching, Group Life and Disability insurance, Professional Development opportunities, Wellness programs, and a variety of other perks. Our success as a company is built on inclusion and diversity. HTC Global Services is committed to providing a workplace free from discrimination and harassment, where every employee is treated with dignity and respect. We celebrate differences and believe that diverse cultures, perspectives, and skills drive innovation and success. HTC is an Equal Opportunity Employer and a proud National Minority Supplier. We seek to empower each individual, fostering an environment where everyone feels valued, included, and respected.
Intro Are you ready to explore a world of possibilities, both at work and during your time off? Join our American Airlines family, and you'll travel the world, grow your expertise and become the best version of you. As you embark on a new journey, you'll tackle challenges with flexibility and grace, learning new skills and advancing your career while having the time of your life. Feel free to enrich both your personal and work life and hop on board! Why you'll love this job As one diverse, high-performing team dedicated to technical excellence, you will focus relentlessly on delivering unrivaled digital products that drive a more reliable and profitable airline. AI domain encompasses disciplines and job families dedicated to the creation, implementation, and management of artificial intelligence technologies. This domain includes roles focused on the research, design, engineering, application, and governance of AI systems. Within the AI domain, professionals work on developing intelligent algorithms and data-driven solutions to solve complex problems and improve decision-making processes. The scope of AI covers various subfields, including natural language processing (NLP), reinforcement learning, and generative AI. What you'll do As noted above, this list is intended to reflect the current job but there may be additional essential functions (and certainly non-essential job functions) that are not referenced. Management will modify the job or require other tasks be performed whenever it is deemed appropriate to do so, observing, of course, any legal obligations including any collective bargaining obligations. Collaborate with leaders, business analysts, project managers, IT architects, technical leads and other developers, along with internal customers, to understand requirements and develop needs according to business requirements for AI solutions Maintain and enhance existing enterprise services, applications, and platforms using domain driven design and test-driven development Troubleshoot and debug complex issues; identify and implement solutions Create detailed project specifications, requirements, and estimates Research and implement new AI technologies to enhance current processes, security, and performance Work closely with software architects and technical leads to ensure decisions meet long-term enterprise growth needs Work on pioneering projects that harness the power of artificial intelligence to solve complex problems and create significant business value. Responsible for participating in all phases of the development process, following agile processes and test-driven development, and using object-oriented development tools to analyze, model, design, construct and test reusable objects. Partner with a diverse team of experts, leveraging cutting-edge technologies to build scalable and impactful AI solutions. All you'll need for success Minimum Qualifications- Education & Prior Job Experience Bachelor's degree in Computer Science, Computer Engineering, Technology, Information Systems (CIS/MIS), Engineering or related technical discipline, or equivalent experience/training 3+ years of full Software Development Life Cycle (SDLC) experience designing, developing, and implementing large-scale applications in hosted production environments 3+ years of professional, design, and open-source experience Preferred Qualifications- Education & Prior Job Experience Master's degree in Computer Science, Computer Engineering, Technology, Information Systems (CIS/MIS), Engineering or related technical discipline, or equivalent experience/training 5 years of full Software Development Life Cycle (SDLC) experience Prior experience designing and building agentic systems Prior experience developing and implementing AI solutions using Large-Language Models (LLMs) Airline or transport industry experience is a plus Skills, Licenses & Certifications Practical understanding of transformer architectures and how modern LLMs work Experience building agentic orchestration using frameworks such as Semantic Kernel, LangChain/LangGraph, Microsoft Copilot Studio, OpenAI/Anthropic tool-calling patterns, or equivalent internal frameworks Proficiency in prompt engineering: systematic prompt design, few-shot learning, chain-of-thought, and prompt optimization for foundation models Knowledge of vector databases (e.g., Pinecone, FAISS, Weaviate, Chroma) and RAG architecture patterns Experience with LLM evaluation methods, including LLM-as-a-judge, automated benchmarking, and regression testing for model outputs Proficiency in post-deployment model maintenance, including observability, monitoring, cost optimization, and drift detection Experience developing and implementing governance frameworks and controls for responsible AI Familiarity with AI-assisted development tools (e.g., GitHub Copilot, Cursor, Claude Code) is a plus Knowledge of experimentation and measurement: A/B testing, KPI instrumentation, and operational analytics Strong proficiency in Python; working knowledge of Java or another enterprise language Proficiency in object-oriented design techniques and principles Experience with cloud platforms (Azure, AWS, or GCP) and cloud-native development patterns Experience with CI/CD pipelines and DevOps toolchain: Git, GitHub, Jenkins, ADO Pipelines, or equivalent Experience with RESTful API design and integration patterns (JSON, microservices) Experience in Agile methodologies, such as SCRUM What you'll get Feel free to take advantage of all that American Airlines has to offer: Travel Perks: Ready to explore the world? You, your family and your friends can reach 365 destinations on more than 6,800 daily flights across our global network. Health Benefits: On day one, you'll have access to your health, dental, prescription and vision benefits to help you stay well. And that's just the start, we also offer virtual doctor visits, flexible spending accounts and more. Wellness Programs: We want you to be the best version of yourself - that's why our wellness programs provide you with all the right tools, resources and support you need. 401(k) Program: Available upon hire and, depending on the workgroup, employer contributions to your 401(k) program are available after one year. Additional Benefits: Other great benefits include our Member Assistance Program, pet insurance and discounts on hotels, cars, cruises and more Feel free to be yourself at American From the team members we hire to the customers we serve, inclusion and diversity are the foundation of the dynamic workforce at American Airlines. Our 20+ Team Member Resource Groups are focused on connecting our team members to our customers, suppliers, communities and shareholders, helping team members reach their full potential and creating an inclusive work environment to meet and exceed the needs of our diverse world. Are you ready to feel a tremendous sense of pride and satisfaction as you do your part to keep the largest airline in the world running smoothly as we care for people on life's journey? Feel free to be yourself at American.
11/13/2026
Full time
Intro Are you ready to explore a world of possibilities, both at work and during your time off? Join our American Airlines family, and you'll travel the world, grow your expertise and become the best version of you. As you embark on a new journey, you'll tackle challenges with flexibility and grace, learning new skills and advancing your career while having the time of your life. Feel free to enrich both your personal and work life and hop on board! Why you'll love this job As one diverse, high-performing team dedicated to technical excellence, you will focus relentlessly on delivering unrivaled digital products that drive a more reliable and profitable airline. AI domain encompasses disciplines and job families dedicated to the creation, implementation, and management of artificial intelligence technologies. This domain includes roles focused on the research, design, engineering, application, and governance of AI systems. Within the AI domain, professionals work on developing intelligent algorithms and data-driven solutions to solve complex problems and improve decision-making processes. The scope of AI covers various subfields, including natural language processing (NLP), reinforcement learning, and generative AI. What you'll do As noted above, this list is intended to reflect the current job but there may be additional essential functions (and certainly non-essential job functions) that are not referenced. Management will modify the job or require other tasks be performed whenever it is deemed appropriate to do so, observing, of course, any legal obligations including any collective bargaining obligations. Collaborate with leaders, business analysts, project managers, IT architects, technical leads and other developers, along with internal customers, to understand requirements and develop needs according to business requirements for AI solutions Maintain and enhance existing enterprise services, applications, and platforms using domain driven design and test-driven development Troubleshoot and debug complex issues; identify and implement solutions Create detailed project specifications, requirements, and estimates Research and implement new AI technologies to enhance current processes, security, and performance Work closely with software architects and technical leads to ensure decisions meet long-term enterprise growth needs Work on pioneering projects that harness the power of artificial intelligence to solve complex problems and create significant business value. Responsible for participating in all phases of the development process, following agile processes and test-driven development, and using object-oriented development tools to analyze, model, design, construct and test reusable objects. Partner with a diverse team of experts, leveraging cutting-edge technologies to build scalable and impactful AI solutions. All you'll need for success Minimum Qualifications- Education & Prior Job Experience Bachelor's degree in Computer Science, Computer Engineering, Technology, Information Systems (CIS/MIS), Engineering or related technical discipline, or equivalent experience/training 3+ years of full Software Development Life Cycle (SDLC) experience designing, developing, and implementing large-scale applications in hosted production environments 3+ years of professional, design, and open-source experience Preferred Qualifications- Education & Prior Job Experience Master's degree in Computer Science, Computer Engineering, Technology, Information Systems (CIS/MIS), Engineering or related technical discipline, or equivalent experience/training 5 years of full Software Development Life Cycle (SDLC) experience Prior experience designing and building agentic systems Prior experience developing and implementing AI solutions using Large-Language Models (LLMs) Airline or transport industry experience is a plus Skills, Licenses & Certifications Practical understanding of transformer architectures and how modern LLMs work Experience building agentic orchestration using frameworks such as Semantic Kernel, LangChain/LangGraph, Microsoft Copilot Studio, OpenAI/Anthropic tool-calling patterns, or equivalent internal frameworks Proficiency in prompt engineering: systematic prompt design, few-shot learning, chain-of-thought, and prompt optimization for foundation models Knowledge of vector databases (e.g., Pinecone, FAISS, Weaviate, Chroma) and RAG architecture patterns Experience with LLM evaluation methods, including LLM-as-a-judge, automated benchmarking, and regression testing for model outputs Proficiency in post-deployment model maintenance, including observability, monitoring, cost optimization, and drift detection Experience developing and implementing governance frameworks and controls for responsible AI Familiarity with AI-assisted development tools (e.g., GitHub Copilot, Cursor, Claude Code) is a plus Knowledge of experimentation and measurement: A/B testing, KPI instrumentation, and operational analytics Strong proficiency in Python; working knowledge of Java or another enterprise language Proficiency in object-oriented design techniques and principles Experience with cloud platforms (Azure, AWS, or GCP) and cloud-native development patterns Experience with CI/CD pipelines and DevOps toolchain: Git, GitHub, Jenkins, ADO Pipelines, or equivalent Experience with RESTful API design and integration patterns (JSON, microservices) Experience in Agile methodologies, such as SCRUM What you'll get Feel free to take advantage of all that American Airlines has to offer: Travel Perks: Ready to explore the world? You, your family and your friends can reach 365 destinations on more than 6,800 daily flights across our global network. Health Benefits: On day one, you'll have access to your health, dental, prescription and vision benefits to help you stay well. And that's just the start, we also offer virtual doctor visits, flexible spending accounts and more. Wellness Programs: We want you to be the best version of yourself - that's why our wellness programs provide you with all the right tools, resources and support you need. 401(k) Program: Available upon hire and, depending on the workgroup, employer contributions to your 401(k) program are available after one year. Additional Benefits: Other great benefits include our Member Assistance Program, pet insurance and discounts on hotels, cars, cruises and more Feel free to be yourself at American From the team members we hire to the customers we serve, inclusion and diversity are the foundation of the dynamic workforce at American Airlines. Our 20+ Team Member Resource Groups are focused on connecting our team members to our customers, suppliers, communities and shareholders, helping team members reach their full potential and creating an inclusive work environment to meet and exceed the needs of our diverse world. Are you ready to feel a tremendous sense of pride and satisfaction as you do your part to keep the largest airline in the world running smoothly as we care for people on life's journey? Feel free to be yourself at American.
This job is with S&P Global, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. About the Role: Grade Level (for internal use): 12 The Team: The Product Operations team drives operational excellence and strategic execution across S&P Global's Geoscience, Engineering and Upstream Data Science software portfolio, serving subsurface professionals worldwide with industry-leading platforms. Operating at the intersection of Product, Technology, Commercial, and Customer Success functions, the team values data-driven decision making, cross-functional collaboration, and customer-centric innovation. This highly visible team plays a critical role in the company's SaaS transformation journey while maintaining our position with the leadingas the trusted partner for energy industry professionals globally. Responsibilities and Impact: Product Portfolio Operations & Performance: Design and implement best-in-class operating cadence across the $100M+ software portfolio, including standardized development workflows, release governance, and comprehensive performance frameworks tracking ACV, ARR, NRR, churn, and feature-level ROI to guide executive decision-making Cross-Functional Alignment & Strategic Execution: Serve as the connective tissue between Product, Engineering, Commercial, and Customer Success teams, leading quarterly business reviews, driving accountability against portfolio OKRs, and ensuring alignment between product roadmaps, commercial timelines, and go-to-market execution SaaS Transformation Leadership: Support the critical transition from legacy desktop software to cloud-native SaaS platforms, partnering with Product Management and Engineering on release velocity, usage-based pricing models, platform scalability, and operational readiness for new platform launches Customer-Centric Feedback Integration: Create structured mechanisms to capture and prioritize insights from Technical Advisors, Customer Support, and Commercial teams, translating feedback into actionable product improvements that enhance customer experience, retention, and drive product-led growth initiatives Go-to-Market & Commercial Enablement: Operationalize product launches across global markets, ensure strong alignment between product positioning, pricing, and packaging strategies, and support deal qualification frameworks while enabling expansion into underpenetrated markets AI/Analytics Integration & Innovation: Drive scalable AI and advanced analytics integration across the multi-product portfolio, supporting data-driven product investment decisions and enabling next-generation capabilities for subsurface professionals worldwide What We're Looking For: Basic Required Qualifications: 8+ years of experience in Product Operations, Product Management, Strategy, or Business Operations roles Proven experience in enterprise software or SaaS environments with demonstrated ability to operate effectively in complex, cross-functional organizations spanning Product, Engineering, and Commercial teams Strong analytical and financial acumen, including expertise with SaaS metrics such as ACV, ARR, NRR, churn analysis, and unit economics to drive data-driven decision making Experience building and implementing operating models, executive dashboards, performance frameworks, and execution processes that drive organizational alignment and accountability Exceptional communication and presentation skills with executive-level presence, including ability to facilitate cross-functional meetings, lead quarterly business reviews, and influence stakeholders at all levels Experience with product portfolio management and go-to-market operations, including product launches, release governance, and commercial enablement activities Bachelor's degree in Business, Engineering, Computer Science, or related field, with Additional Preferred Qualifications: Experience in energy, geoscience, or engineering software markets with familiarity of subsurface workflows such as seismic interpretation, reservoir modeling, or production optimization Proven track record supporting desktop-to-SaaS platform transformations, including migration strategies, cloud-native architecture considerations, and change management for technical user bases Exposure to AI/ML-enabled products, advanced analytics platforms, or data science applications, particularly in technical or scientific software environments Background working with global teams and international customers, including experience with market expansion strategies and cross-cultural stakeholder management Compensation/Benefits Information: (This section is only applicable to US candidates) S&P Global states that the anticipated base salary range for this position is $110,000 to $149,000. Final base salary for this role will be based on the individual's geographic location, as well as experience level, skill set, training, licenses and certifications. In addition to base compensation, this role is eligible for an annual incentive plan. This role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please click here . Right to Work Requirements: This role is limited to persons with an indefinite right to work in the United States About S&P Global Energy At S&P Global Energy, our comprehensive view of global energy and commodities markets enables our customers to make superior decisions and create long-term, sustainable value. Our four core capabilities are: Platts for news and pricing; CERA for research and advisory; Horizons for energy expansion and sustainability solutions; and Events for industry collaboration. S&P Global Energy is a division of S&P Global (NYSE: SPGI). S&P Global enables businesses, governments, and individuals with trusted data, expertise, and technology to make decisions with conviction. We are Advancing Essential Intelligence through world-leading benchmarks, data, and insights that customers need in order to plan confidently, act decisively, and thrive economically in a rapidly changing global landscape. Learn more at . What's In It For You? Our Mission: Advancing Essential Intelligence. Our People: We're more than 35,000 strong worldwide-so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We're committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. Join us and help create the critical insights that truly make a difference. Our Values: Integrity, Discovery, Partnership Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you can take care of business. We care about our people. That's why we provide everything you-and your career-need to thrive at S&P Global. Our benefits include: Health & Wellness: Health care coverage designed for the mind and body. Flexible Downtime: Generous time off helps keep you energized for your time on. Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills. Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly Perks: It's not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the Basics: From retail discounts to referral incentive awards-small perks can make a big difference. For more information on benefits by country visit: Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. Recruitment Fraud Alert: If you receive an email from a domain or any other regionally based domains, it is a scam and should be reported to . S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, "pre-employment training" or for equipment/delivery of equipment . click apply for full job details
11/13/2026
Full time
This job is with S&P Global, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. About the Role: Grade Level (for internal use): 12 The Team: The Product Operations team drives operational excellence and strategic execution across S&P Global's Geoscience, Engineering and Upstream Data Science software portfolio, serving subsurface professionals worldwide with industry-leading platforms. Operating at the intersection of Product, Technology, Commercial, and Customer Success functions, the team values data-driven decision making, cross-functional collaboration, and customer-centric innovation. This highly visible team plays a critical role in the company's SaaS transformation journey while maintaining our position with the leadingas the trusted partner for energy industry professionals globally. Responsibilities and Impact: Product Portfolio Operations & Performance: Design and implement best-in-class operating cadence across the $100M+ software portfolio, including standardized development workflows, release governance, and comprehensive performance frameworks tracking ACV, ARR, NRR, churn, and feature-level ROI to guide executive decision-making Cross-Functional Alignment & Strategic Execution: Serve as the connective tissue between Product, Engineering, Commercial, and Customer Success teams, leading quarterly business reviews, driving accountability against portfolio OKRs, and ensuring alignment between product roadmaps, commercial timelines, and go-to-market execution SaaS Transformation Leadership: Support the critical transition from legacy desktop software to cloud-native SaaS platforms, partnering with Product Management and Engineering on release velocity, usage-based pricing models, platform scalability, and operational readiness for new platform launches Customer-Centric Feedback Integration: Create structured mechanisms to capture and prioritize insights from Technical Advisors, Customer Support, and Commercial teams, translating feedback into actionable product improvements that enhance customer experience, retention, and drive product-led growth initiatives Go-to-Market & Commercial Enablement: Operationalize product launches across global markets, ensure strong alignment between product positioning, pricing, and packaging strategies, and support deal qualification frameworks while enabling expansion into underpenetrated markets AI/Analytics Integration & Innovation: Drive scalable AI and advanced analytics integration across the multi-product portfolio, supporting data-driven product investment decisions and enabling next-generation capabilities for subsurface professionals worldwide What We're Looking For: Basic Required Qualifications: 8+ years of experience in Product Operations, Product Management, Strategy, or Business Operations roles Proven experience in enterprise software or SaaS environments with demonstrated ability to operate effectively in complex, cross-functional organizations spanning Product, Engineering, and Commercial teams Strong analytical and financial acumen, including expertise with SaaS metrics such as ACV, ARR, NRR, churn analysis, and unit economics to drive data-driven decision making Experience building and implementing operating models, executive dashboards, performance frameworks, and execution processes that drive organizational alignment and accountability Exceptional communication and presentation skills with executive-level presence, including ability to facilitate cross-functional meetings, lead quarterly business reviews, and influence stakeholders at all levels Experience with product portfolio management and go-to-market operations, including product launches, release governance, and commercial enablement activities Bachelor's degree in Business, Engineering, Computer Science, or related field, with Additional Preferred Qualifications: Experience in energy, geoscience, or engineering software markets with familiarity of subsurface workflows such as seismic interpretation, reservoir modeling, or production optimization Proven track record supporting desktop-to-SaaS platform transformations, including migration strategies, cloud-native architecture considerations, and change management for technical user bases Exposure to AI/ML-enabled products, advanced analytics platforms, or data science applications, particularly in technical or scientific software environments Background working with global teams and international customers, including experience with market expansion strategies and cross-cultural stakeholder management Compensation/Benefits Information: (This section is only applicable to US candidates) S&P Global states that the anticipated base salary range for this position is $110,000 to $149,000. Final base salary for this role will be based on the individual's geographic location, as well as experience level, skill set, training, licenses and certifications. In addition to base compensation, this role is eligible for an annual incentive plan. This role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please click here . Right to Work Requirements: This role is limited to persons with an indefinite right to work in the United States About S&P Global Energy At S&P Global Energy, our comprehensive view of global energy and commodities markets enables our customers to make superior decisions and create long-term, sustainable value. Our four core capabilities are: Platts for news and pricing; CERA for research and advisory; Horizons for energy expansion and sustainability solutions; and Events for industry collaboration. S&P Global Energy is a division of S&P Global (NYSE: SPGI). S&P Global enables businesses, governments, and individuals with trusted data, expertise, and technology to make decisions with conviction. We are Advancing Essential Intelligence through world-leading benchmarks, data, and insights that customers need in order to plan confidently, act decisively, and thrive economically in a rapidly changing global landscape. Learn more at . What's In It For You? Our Mission: Advancing Essential Intelligence. Our People: We're more than 35,000 strong worldwide-so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We're committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. Join us and help create the critical insights that truly make a difference. Our Values: Integrity, Discovery, Partnership Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you can take care of business. We care about our people. That's why we provide everything you-and your career-need to thrive at S&P Global. Our benefits include: Health & Wellness: Health care coverage designed for the mind and body. Flexible Downtime: Generous time off helps keep you energized for your time on. Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills. Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly Perks: It's not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the Basics: From retail discounts to referral incentive awards-small perks can make a big difference. For more information on benefits by country visit: Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. Recruitment Fraud Alert: If you receive an email from a domain or any other regionally based domains, it is a scam and should be reported to . S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, "pre-employment training" or for equipment/delivery of equipment . click apply for full job details
This job is with S&P Global, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. About the Role: Grade Level (for internal use): 13 Role Summary We are seeking a Technical Team Lead - AI, AWS, Java Full-Stack, Financial Platforms to lead the design, development, and delivery of index calculation and back testing platform. This role combines hands-on Java full-stack engineering, AWS cloud development, AI-assisted software delivery, and technical leadership across a financial technology platform. The Technical Team Lead will guide a team of engineers in building scalable backend services, modern user interfaces, financial calculation workflows, back testing capabilities, data integrations, automated testing frameworks, and AI-assisted QA/evaluation routines. The role requires strong technical judgment, practical leadership, and the ability to translate financial methodology requirements into reliable, auditable, and production-ready software. This is a hands-on leadership role. The successful candidate will be expected to define technical direction, mentor developers, review architecture and code, collaborate with business and quantitative stakeholders, and contribute directly to critical platform components. Key Responsibilities Technical Leadership Lead the engineering delivery of an AI-enabled financial platform for index calculation, options analytics, back testing, and workflow execution. Define technical architecture, implementation standards, coding practices, testing expectations, and delivery patterns for the engineering team. Guide developers through complex design decisions involving Java services, frontend architecture, AWS workflows, data integration, AI-assisted development, and calculation accuracy. Partner with product owners, quantitative analysts, QA teams, infrastructure teams, data teams, and business stakeholders to convert requirements into clear technical plans. Lead design reviews, code reviews, sprint technical planning, production readiness reviews, and technical risk assessments. Mentor engineers in Java full-stack development, cloud-native design, financial calculation systems, automated testing, and responsible use of AI-assisted engineering tools. Ensure the platform is scalable, secure, maintainable, observable, auditable, and aligned with financial methodology and operational requirements. Hands-On Java Full-Stack Development Design and develop backend services using Java, Spring Boot, REST APIs, and enterprise application patterns. Build platform components for index calculation, backtesting, data processing, workflow orchestration, exception handling, validation, and reporting. Implement financial calculation logic based on methodology specifications, including options-based strategies, rebalancing rules, pricing inputs, market calendars, and historical backtesting assumptions. Develop modern frontend applications using React, Angular, Vue, TypeScript, JavaScript, HTML, and CSS. Build user interfaces for index setup, backtest configuration, workflow monitoring, calculation review, validation results, exception management, dashboards, and reporting. Ensure strong integration between frontend applications, backend APIs, authentication flows, data services, and cloud workflows. AI-Assisted Engineering and Spec-Driven Development Apply Spec-Driven Development practices to convert financial methodology documents, business requirements, and technical specifications into testable software components. Use AI-assisted engineering workflows to support planning, code generation, refactoring, test creation, documentation, and quality review. Review AI-generated or AI-assisted code for correctness, maintainability, security, performance, test coverage, and alignment with platform standards. Help establish team practices for responsible AI-assisted development, including review checklists, validation gates, test coverage expectations, and documentation standards. Support AI-assisted QA and evaluation routines for generated code, calculation outputs, regression testing, and backtest validation. AWS, Data, and Platform Engineering Design and implement AWS-based platform components using services such as AWS Step Functions, Lambda, ECS/EKS, API Gateway, S3, CloudWatch, IAM, EventBridge, SQS/SNS, and AWS RDS. Build workflow orchestration for index calculations, backtest execution, data validation, exception handling, approvals, and operational monitoring. Integrate with data platforms including AWS RDS, cloud data platforms (such as Databricks, Snowflake, or Azure Synapse), data lakes, market data sources, reference data platforms, and analytical data pipelines. Ensure data lineage, audit trails, input/output traceability, logging, alerting, and operational controls are built into the platform. Support CI/CD, infrastructure automation, deployment validation, monitoring, and production support practices. Required Experience 12+ years of software engineering experience, with significant experience in Java full-stack development and enterprise platform delivery. 5+ years of technical leadership experience, including mentoring engineers, leading design discussions, reviewing code, and guiding delivery teams. Strong hands-on experience with Java, Spring Boot, REST APIs, microservices, relational databases, and backend service design. Hands-on frontend development experience using React, Angular, Vue, TypeScript, JavaScript, HTML, and CSS. Experience designing and delivering large-scale systems involving distributed services, workflow orchestration, data processing, APIs, and production operations. Experience with AWS cloud-native development, including compute, storage, orchestration, security, monitoring, logging, and managed databases. Strong understanding of automated testing, CI/CD, code quality, observability, secure development, and production readiness. Experience or strong interest in financial platforms, especially index calculation, options analytics, derivatives, equities, portfolio analytics, backtesting, risk systems, or capital markets technology. Ability to interpret detailed financial methodology specifications and translate them into reliable, testable, and auditable software designs. Exposure to GenAI engineering, AI-assisted coding, agentic development workflows, Claude Code, Claude Code CLI, Spec Kit, or Spec-Driven Development is highly desirable. Preferred Technical Stack Backend: Java, Spring Boot, REST APIs, microservices, JPA/Hibernate, Maven/Gradle, concurrency, batch processing, and enterprise integration patterns. Frontend: React, Angular, or Vue; TypeScript; JavaScript; HTML; CSS; reusable components; dashboards; forms; data grids; charts; and responsive UI design. Cloud: AWS Step Functions, Lambda, ECS/EKS, API Gateway, S3, CloudWatch, IAM, EventBridge, SQS/SNS, RDS, and cloud-native security patterns. Data Platforms: AWS RDS, cloud data platforms (such as Databricks, Snowflake, or Azure Synapse), relational databases, data pipelines, market data integration, reference data, and analytical data processing. AI Engineering: AI-assisted development, Spec-Driven Development, Claude Code, Claude Code CLI, Spec Kit, automated QA/evaluation routines, and human-reviewed generated code. DevOps and Quality: CI/CD, automated testing, integration testing, regression testing, performance testing, logging, monitoring, alerting, and production support. Financial Domain Knowledge The ideal candidate should have experience or strong working interest in financial systems involving calculation-heavy workflows. Relevant areas include: Index calculation methodologies, index levels, divisor logic, rebalancing, weighting, corporate actions, calendars, and daily calculation cycles. Options-based strategies such as covered call, put write, collar, volatility-based, delta-based, or rules-based options strategies. Backtesting concepts such as historical simulation, look-ahead bias prevention, survivorship bias, transaction assumptions, rebalance simulation, and reproducibility. Market data concepts including prices, option chains, strikes, expiries, implied volatility, rates, dividends, corporate actions, and reference data. Validation practices including golden datasets, tolerance checks, independent calculation verification, reconciliation, audit trails, and exception handling. Success Measures Leads the team in delivering a scalable, secure, and reliable index calculation and backtesting platform. Produces and guides high-quality Java full-stack implementation across backend services, frontend applications, APIs, workflows, and data integrations. Converts financial methodology specifications into tested, reproducible, and auditable platform logic. Establishes strong engineering practices for code quality, automated testing, observability, documentation, and production readiness. Uses AI-assisted development responsibly to improve delivery speed while maintaining human review, financial accuracy, and software quality. Builds strong collaboration across engineering, quantitative analysis, QA, infrastructure, product . click apply for full job details
11/13/2026
Full time
This job is with S&P Global, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. About the Role: Grade Level (for internal use): 13 Role Summary We are seeking a Technical Team Lead - AI, AWS, Java Full-Stack, Financial Platforms to lead the design, development, and delivery of index calculation and back testing platform. This role combines hands-on Java full-stack engineering, AWS cloud development, AI-assisted software delivery, and technical leadership across a financial technology platform. The Technical Team Lead will guide a team of engineers in building scalable backend services, modern user interfaces, financial calculation workflows, back testing capabilities, data integrations, automated testing frameworks, and AI-assisted QA/evaluation routines. The role requires strong technical judgment, practical leadership, and the ability to translate financial methodology requirements into reliable, auditable, and production-ready software. This is a hands-on leadership role. The successful candidate will be expected to define technical direction, mentor developers, review architecture and code, collaborate with business and quantitative stakeholders, and contribute directly to critical platform components. Key Responsibilities Technical Leadership Lead the engineering delivery of an AI-enabled financial platform for index calculation, options analytics, back testing, and workflow execution. Define technical architecture, implementation standards, coding practices, testing expectations, and delivery patterns for the engineering team. Guide developers through complex design decisions involving Java services, frontend architecture, AWS workflows, data integration, AI-assisted development, and calculation accuracy. Partner with product owners, quantitative analysts, QA teams, infrastructure teams, data teams, and business stakeholders to convert requirements into clear technical plans. Lead design reviews, code reviews, sprint technical planning, production readiness reviews, and technical risk assessments. Mentor engineers in Java full-stack development, cloud-native design, financial calculation systems, automated testing, and responsible use of AI-assisted engineering tools. Ensure the platform is scalable, secure, maintainable, observable, auditable, and aligned with financial methodology and operational requirements. Hands-On Java Full-Stack Development Design and develop backend services using Java, Spring Boot, REST APIs, and enterprise application patterns. Build platform components for index calculation, backtesting, data processing, workflow orchestration, exception handling, validation, and reporting. Implement financial calculation logic based on methodology specifications, including options-based strategies, rebalancing rules, pricing inputs, market calendars, and historical backtesting assumptions. Develop modern frontend applications using React, Angular, Vue, TypeScript, JavaScript, HTML, and CSS. Build user interfaces for index setup, backtest configuration, workflow monitoring, calculation review, validation results, exception management, dashboards, and reporting. Ensure strong integration between frontend applications, backend APIs, authentication flows, data services, and cloud workflows. AI-Assisted Engineering and Spec-Driven Development Apply Spec-Driven Development practices to convert financial methodology documents, business requirements, and technical specifications into testable software components. Use AI-assisted engineering workflows to support planning, code generation, refactoring, test creation, documentation, and quality review. Review AI-generated or AI-assisted code for correctness, maintainability, security, performance, test coverage, and alignment with platform standards. Help establish team practices for responsible AI-assisted development, including review checklists, validation gates, test coverage expectations, and documentation standards. Support AI-assisted QA and evaluation routines for generated code, calculation outputs, regression testing, and backtest validation. AWS, Data, and Platform Engineering Design and implement AWS-based platform components using services such as AWS Step Functions, Lambda, ECS/EKS, API Gateway, S3, CloudWatch, IAM, EventBridge, SQS/SNS, and AWS RDS. Build workflow orchestration for index calculations, backtest execution, data validation, exception handling, approvals, and operational monitoring. Integrate with data platforms including AWS RDS, cloud data platforms (such as Databricks, Snowflake, or Azure Synapse), data lakes, market data sources, reference data platforms, and analytical data pipelines. Ensure data lineage, audit trails, input/output traceability, logging, alerting, and operational controls are built into the platform. Support CI/CD, infrastructure automation, deployment validation, monitoring, and production support practices. Required Experience 12+ years of software engineering experience, with significant experience in Java full-stack development and enterprise platform delivery. 5+ years of technical leadership experience, including mentoring engineers, leading design discussions, reviewing code, and guiding delivery teams. Strong hands-on experience with Java, Spring Boot, REST APIs, microservices, relational databases, and backend service design. Hands-on frontend development experience using React, Angular, Vue, TypeScript, JavaScript, HTML, and CSS. Experience designing and delivering large-scale systems involving distributed services, workflow orchestration, data processing, APIs, and production operations. Experience with AWS cloud-native development, including compute, storage, orchestration, security, monitoring, logging, and managed databases. Strong understanding of automated testing, CI/CD, code quality, observability, secure development, and production readiness. Experience or strong interest in financial platforms, especially index calculation, options analytics, derivatives, equities, portfolio analytics, backtesting, risk systems, or capital markets technology. Ability to interpret detailed financial methodology specifications and translate them into reliable, testable, and auditable software designs. Exposure to GenAI engineering, AI-assisted coding, agentic development workflows, Claude Code, Claude Code CLI, Spec Kit, or Spec-Driven Development is highly desirable. Preferred Technical Stack Backend: Java, Spring Boot, REST APIs, microservices, JPA/Hibernate, Maven/Gradle, concurrency, batch processing, and enterprise integration patterns. Frontend: React, Angular, or Vue; TypeScript; JavaScript; HTML; CSS; reusable components; dashboards; forms; data grids; charts; and responsive UI design. Cloud: AWS Step Functions, Lambda, ECS/EKS, API Gateway, S3, CloudWatch, IAM, EventBridge, SQS/SNS, RDS, and cloud-native security patterns. Data Platforms: AWS RDS, cloud data platforms (such as Databricks, Snowflake, or Azure Synapse), relational databases, data pipelines, market data integration, reference data, and analytical data processing. AI Engineering: AI-assisted development, Spec-Driven Development, Claude Code, Claude Code CLI, Spec Kit, automated QA/evaluation routines, and human-reviewed generated code. DevOps and Quality: CI/CD, automated testing, integration testing, regression testing, performance testing, logging, monitoring, alerting, and production support. Financial Domain Knowledge The ideal candidate should have experience or strong working interest in financial systems involving calculation-heavy workflows. Relevant areas include: Index calculation methodologies, index levels, divisor logic, rebalancing, weighting, corporate actions, calendars, and daily calculation cycles. Options-based strategies such as covered call, put write, collar, volatility-based, delta-based, or rules-based options strategies. Backtesting concepts such as historical simulation, look-ahead bias prevention, survivorship bias, transaction assumptions, rebalance simulation, and reproducibility. Market data concepts including prices, option chains, strikes, expiries, implied volatility, rates, dividends, corporate actions, and reference data. Validation practices including golden datasets, tolerance checks, independent calculation verification, reconciliation, audit trails, and exception handling. Success Measures Leads the team in delivering a scalable, secure, and reliable index calculation and backtesting platform. Produces and guides high-quality Java full-stack implementation across backend services, frontend applications, APIs, workflows, and data integrations. Converts financial methodology specifications into tested, reproducible, and auditable platform logic. Establishes strong engineering practices for code quality, automated testing, observability, documentation, and production readiness. Uses AI-assisted development responsibly to improve delivery speed while maintaining human review, financial accuracy, and software quality. Builds strong collaboration across engineering, quantitative analysis, QA, infrastructure, product . click apply for full job details
Machine Learning Engineer 4 (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. Enterprise Platforms Technology (EPTech) comprises many of Capital One's most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices. Team: The Marketing and Messaging team is responsible for delivering hyper-personalized messages and experiences that will delight the customer, attract prospects and drive increasing business value. The team builds scalable platforms that deliver omnichannel messages in owned and paid Adtech channels. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Francisco, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
Machine Learning Engineer 4 (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. Enterprise Platforms Technology (EPTech) comprises many of Capital One's most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices. Team: The Marketing and Messaging team is responsible for delivering hyper-personalized messages and experiences that will delight the customer, attract prospects and drive increasing business value. The team builds scalable platforms that deliver omnichannel messages in owned and paid Adtech channels. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4 Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4 San Francisco, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 - Finance Tech Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. Finance Tech is responsible for transforming Capital One's financial engine into the most trusted, nimble, and insightful in the industry. Our core mission is to engineer outcomes that strategically enable the Finance organization and the broader Enterprise to remain efficient. This mission is driven by four technical and functional pillars: Forecasting & Resiliency, providing advanced decision support; Treasury & Trade managing sophisticated cash and investment lifecycles; and Accounting & Reporting, ensuring the integrity of our general ledger and regulatory commitments. Powering these pillars are our Data and Core capabilities, which manage the orchestration, sourcing, and pipelines for critical financial data products. By defining the next generation of financial technology, we ensure that every business process is backed by high fidelity tracking and reporting. Together, we are not just supporting the bottom line - we are building a strategic enabler that operates as a world class financial engine. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java This role is designated as a hybrid position. You are expected to adhere to Capital One's hybrid policy regarding required on-site presence at your designated office location. Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
Machine Learning Engineer 4 - Finance Tech Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. Finance Tech is responsible for transforming Capital One's financial engine into the most trusted, nimble, and insightful in the industry. Our core mission is to engineer outcomes that strategically enable the Finance organization and the broader Enterprise to remain efficient. This mission is driven by four technical and functional pillars: Forecasting & Resiliency, providing advanced decision support; Treasury & Trade managing sophisticated cash and investment lifecycles; and Accounting & Reporting, ensuring the integrity of our general ledger and regulatory commitments. Powering these pillars are our Data and Core capabilities, which manage the orchestration, sourcing, and pipelines for critical financial data products. By defining the next generation of financial technology, we ensure that every business process is backed by high fidelity tracking and reporting. Together, we are not just supporting the bottom line - we are building a strategic enabler that operates as a world class financial engine. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java This role is designated as a hybrid position. You are expected to adhere to Capital One's hybrid policy regarding required on-site presence at your designated office location. Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience optimizing ML algorithms, configurations, and infrastructure 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans. 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Machine Learning Engineer 4 McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
