Job Description Job Title: Azure Databricks Solution Architect/Lead Data Architect Job type: Contract position up to 12 months. Location: Hybrid - USA Consultant can sit anywhere in the USA. Travel locations include Chicago, Philadelphia, and Baltimore. Travel is occasional with all travel expenses covered. Quasent, Inc. () is looking for an experience Azure Databricks Solution Architect/Data Architect. Responsibilities: You will be responsible for the Architecture and design. Lead the Architecture and Technical Design of Enterprise-scale Data Platform. Own the end-to-end technical architecture of the data platform including ingestion layers, bronze and silver scd layers, data modelling, consumption channel integration, and real-time speed layer design. Define and govern architecture standards, design patterns, and technical guardrails across all delivery workstreams Lead technical design reviews and ensure alignment between functional requirements, source-to-target mappings, and technical implementation. Architect solutions using Azure Databricks, Delta Lake, Unity Catalog, ADLS, GEN2, and Azure Services. Evaluate and recommend technology decisions across the Azure and Databricks ecosystem - including Delta Lake, Unity Catalog, Mosaic AI, Databricks Apps, Azure AI Search, and Azure Data Lake Storage Gen2 Drive architecture for Databricks Genie AI/BI - defining the Genie space design, semantic layer approach, and self-service analytics enablement strategy. Lead the design and expansion of an agentic delivery framework - defining multi-agent architecture, orchestration patterns, LLM integration, and knowledge base design using Databricks Mosaic AI and Azure AI services technical leadership Serve as the technical escalation point for the delivery team - resolving complex data engineering, integration, and platform challenges Guide data engineers, functional SMEs, and report developers on technical approach and best practices on the Databricks platform Support downstream data integrations, including Oracle GoldenGate (OCG) replication, data views, and provisioning patterns. Review and approve technical designs, data models, and solution specifications before build. Provide architectural oversight on schema change impact, upstream dependency management, and data quality framework design Stakeholder and cross-program engagement. Engage with client architects to align on platform decisions, architectural governance, and technology approvals. Represent the technical position in cross-program forums spanning source systems, downstream channel teams, and enterprise platform teams. Support architecture decisions for consumption channel integrations including OGG replication, view design, and data provisioning patterns Required Skills and Qualifications: 10 plus years of experience in I.T. with strong expertise in data engineering and solution architecture. Strong hands on experience with Azure Databricks, PySpark, Spart, SQL, Delta Lake, and ADLS Gen2. Experience with Unity Catalog, data governance, and security Proven experience leading technical teams and enterprise architecture discussions. Preferred Skills: Databricks Genie AI/BI and semantic layer architecture. Databricks Mosaic AI, Agentic AI, LLM's, Azure AI search. Oracle GoldenGate (OOG)
11/14/2026
Full time
Job Description Job Title: Azure Databricks Solution Architect/Lead Data Architect Job type: Contract position up to 12 months. Location: Hybrid - USA Consultant can sit anywhere in the USA. Travel locations include Chicago, Philadelphia, and Baltimore. Travel is occasional with all travel expenses covered. Quasent, Inc. () is looking for an experience Azure Databricks Solution Architect/Data Architect. Responsibilities: You will be responsible for the Architecture and design. Lead the Architecture and Technical Design of Enterprise-scale Data Platform. Own the end-to-end technical architecture of the data platform including ingestion layers, bronze and silver scd layers, data modelling, consumption channel integration, and real-time speed layer design. Define and govern architecture standards, design patterns, and technical guardrails across all delivery workstreams Lead technical design reviews and ensure alignment between functional requirements, source-to-target mappings, and technical implementation. Architect solutions using Azure Databricks, Delta Lake, Unity Catalog, ADLS, GEN2, and Azure Services. Evaluate and recommend technology decisions across the Azure and Databricks ecosystem - including Delta Lake, Unity Catalog, Mosaic AI, Databricks Apps, Azure AI Search, and Azure Data Lake Storage Gen2 Drive architecture for Databricks Genie AI/BI - defining the Genie space design, semantic layer approach, and self-service analytics enablement strategy. Lead the design and expansion of an agentic delivery framework - defining multi-agent architecture, orchestration patterns, LLM integration, and knowledge base design using Databricks Mosaic AI and Azure AI services technical leadership Serve as the technical escalation point for the delivery team - resolving complex data engineering, integration, and platform challenges Guide data engineers, functional SMEs, and report developers on technical approach and best practices on the Databricks platform Support downstream data integrations, including Oracle GoldenGate (OCG) replication, data views, and provisioning patterns. Review and approve technical designs, data models, and solution specifications before build. Provide architectural oversight on schema change impact, upstream dependency management, and data quality framework design Stakeholder and cross-program engagement. Engage with client architects to align on platform decisions, architectural governance, and technology approvals. Represent the technical position in cross-program forums spanning source systems, downstream channel teams, and enterprise platform teams. Support architecture decisions for consumption channel integrations including OGG replication, view design, and data provisioning patterns Required Skills and Qualifications: 10 plus years of experience in I.T. with strong expertise in data engineering and solution architecture. Strong hands on experience with Azure Databricks, PySpark, Spart, SQL, Delta Lake, and ADLS Gen2. Experience with Unity Catalog, data governance, and security Proven experience leading technical teams and enterprise architecture discussions. Preferred Skills: Databricks Genie AI/BI and semantic layer architecture. Databricks Mosaic AI, Agentic AI, LLM's, Azure AI search. Oracle GoldenGate (OOG)
Job Description Title: AI Architect Location: Las Vegas, NV (Day 1 Onsite, 3 Days WFO - Hybrid). Exp: 10+ Yrs Skills: Google Cloud Service (Vertex AI, BigQuery, Cloud Functions), AI SDLC, AI Best Practices. Primary Skill: SDLC CI/CD, Google Cloud OS, Vertex AI Job Description: Job Requirements Key Responsibilities: Architect and design agentic AI systems tailored for CRM and BPM solutions including requirements to backlog, backlog to build and build to deploy phases of the SDLC Lead the development of autonomous agents capable of reasoning, learning, and collaborating across the test life cycle. Build and optimize AI pipelines using Google Cloud services (Vertex AI, BigQuery, Cloud Functions, etc.). Integrate agents with CI/CD pipelines, test management tools, and developer environments. Ensure seamless deployment and orchestration on AgentSpace, leveraging its capabilities for agent lifecycle management, communication, and scalability. Collaborate with cross-functional teams including QA, DevOps, and product engineering to align AI capabilities with business goals. Define and enforce best practices for agentic AI, including safety, interpretability, and performance monitoring. Stay ahead of emerging trends in LLMs, multi-agent systems, and autonomous software engineering. Required Qualifications Proven experience as an AI Architect, ML Engineer, or similar role with a focus on agentic or autonomous systems. Strong expertise in Google Cloud Platform and its AI/ML ecosystem. 2+ years of experience in building AI/ML solutions, with at least 1+ year focused on generative / Agentic AI. 3+ years experience developing or working with CRM and BPM solutions Familiarity with software testing tools (e.g., Selenium, TestNG, JUnit) and lifecycle processes. Experience deploying and managing agents on AgentSpace or similar platforms. Excellent problem-solving, communication, and leadership skills Primary Skills Google Cloud services (Vertex AI, BigQuery, Cloud Functions, etc.). AI SDLC AI Best Practices Communication Work Experience 10+ Years
11/14/2026
Full time
Job Description Title: AI Architect Location: Las Vegas, NV (Day 1 Onsite, 3 Days WFO - Hybrid). Exp: 10+ Yrs Skills: Google Cloud Service (Vertex AI, BigQuery, Cloud Functions), AI SDLC, AI Best Practices. Primary Skill: SDLC CI/CD, Google Cloud OS, Vertex AI Job Description: Job Requirements Key Responsibilities: Architect and design agentic AI systems tailored for CRM and BPM solutions including requirements to backlog, backlog to build and build to deploy phases of the SDLC Lead the development of autonomous agents capable of reasoning, learning, and collaborating across the test life cycle. Build and optimize AI pipelines using Google Cloud services (Vertex AI, BigQuery, Cloud Functions, etc.). Integrate agents with CI/CD pipelines, test management tools, and developer environments. Ensure seamless deployment and orchestration on AgentSpace, leveraging its capabilities for agent lifecycle management, communication, and scalability. Collaborate with cross-functional teams including QA, DevOps, and product engineering to align AI capabilities with business goals. Define and enforce best practices for agentic AI, including safety, interpretability, and performance monitoring. Stay ahead of emerging trends in LLMs, multi-agent systems, and autonomous software engineering. Required Qualifications Proven experience as an AI Architect, ML Engineer, or similar role with a focus on agentic or autonomous systems. Strong expertise in Google Cloud Platform and its AI/ML ecosystem. 2+ years of experience in building AI/ML solutions, with at least 1+ year focused on generative / Agentic AI. 3+ years experience developing or working with CRM and BPM solutions Familiarity with software testing tools (e.g., Selenium, TestNG, JUnit) and lifecycle processes. Experience deploying and managing agents on AgentSpace or similar platforms. Excellent problem-solving, communication, and leadership skills Primary Skills Google Cloud services (Vertex AI, BigQuery, Cloud Functions, etc.). AI SDLC AI Best Practices Communication Work Experience 10+ Years
Job Description AI Optimization Engineer Location: Charlotte, NC (Hybrid, 3 days on-site at Optimist Hall Location) or Remote within the U.S. (must be able to work EST hours) Compensation: $80 - $95/hour plus benefits Duration: 12-month contract with strong potential for extension or conversion to full-time employment Employment Requirements: W-2 only. No Corp-to-Corp or 1099 arrangements. Successful candidate must be able to work on W-2 without visa sponsorship both now and in the future. ABOUT THE ROLE Our Client is seeking an AI Optimization Engineer to develop and support the optimization engine at the core of their Capital Investment Planning & Prioritization Tool (CIPT). This tool empowers planning teams to make data-driven decisions about which capital investments to fund, when, and why, by transforming complex business rules into robust, explainable, and auditable optimization models. The role involves designing, building, testing, and maintaining advanced mathematical optimization models-primarily using Mixed-Integer Linear Programming (MILP)-and integrating predictive analytics and benefit measures into portfolio planning. You will work closely with data and ML engineers, leverage cloud-based solutions (primarily AWS), and utilize modern software development practices, including AI-enabled tools like GitHub Copilot and Spec-Driven Development. The ideal candidate combines strong optimization and software engineering fundamentals with a willingness to learn new AI-driven approaches, ensuring solutions are mathematically correct, reproducible, and transparent for planners, finance partners, and regulators. WHAT YOU'LL DO Translate complex capital planning business rules-including budget, resource, cash-flow, jurisdictional, and portfolio constraints-into mathematical optimization models. Formulate, implement, and tune Mixed-Integer Linear Programming (MILP) models using Python frameworks (e.g., Pyomo, PuLP, OR-Tools) and commercial/open-source solvers (e.g., Gurobi, CPLEX, HiGHS, CBC). Integrate predictive model outputs (e.g., Probability of Failure, Remaining Useful Life) and benefit measures (e.g., reliability, safety, financial, NPV) into optimization objectives for portfolio planning. Design, build, and maintain scenario optimization workflows, including scenario creation, copying, optimization across planning cycles, and deterministic run harnesses for reproducible results. Develop diagnostic and infeasibility analysis capabilities (e.g., constraint relaxation, irreducible infeasible subsets, clear error messages) to help planners understand optimization outcomes. Evaluate and recommend solvers and modeling approaches based on solution quality, run-time performance, licensing cost, and operational fit. Package and deploy optimization workloads as scalable cloud services (e.g., AWS Batch, Fargate, Lambda, Step Functions) with REST APIs, leveraging Infrastructure as Code tools (e.g., Terraform). Collaborate with data and ML engineers to integrate asset-health predictions and ensure seamless data flow into optimization models. Build automated test suites for optimization models, including unit tests for constraints, regression tests, reproducibility checks, and comparisons against historical results. Profile and tune model performance using reformulation, tighter bounds, decomposition, warm starts, and solver parameter tuning to meet run-time and scalability targets. Produce clear, explainable outputs for planners and stakeholders, including binding constraints, shadow prices, scenario comparisons, and investment selection rationale. Document model formulations, assumptions, and limitations for business owners, auditors, and future engineers. Contribute reusable optimization components, model templates, test harnesses, and engineering accelerators for broader team and organizational use. Utilize GitHub, GitHub Copilot, and AI agents to enhance software development, testing, and delivery processes; gain hands-on experience with agentic software engineering and automation workflows. Prepare, validate, and troubleshoot large input datasets and database integrations (e.g., PostgreSQL) for optimization models, ensuring data quality and version control. Participate in technical learning activities, communities of practice, hackathons, and innovation events to continuously expand cloud, AI, and optimization engineering skills. WHAT YOU BRING Associate's degree in Information Technology or related field required; Bachelor's or Master's in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or related field preferred. 5+ years of relevant work experience in optimization, software development, or decision-support applications. Hands-on experience designing, building, and supporting optimization models, especially Mixed-Integer Linear Programming (MILP) using frameworks like Pyomo, PuLP, OR-Tools, or Gurobi Python API. Proficiency with commercial or open-source solvers (e.g., Gurobi, CPLEX, HiGHS, CBC) and strong understanding of linear and integer programming, including advanced formulation techniques (e.g., binary selection variables, logical/indicator constraints, big-M, multi-period timing, precedence constraints). Experience modeling knapsack-style and resource-constrained selection or scheduling problems, multi-objective or weighted-objective optimization, and tradeoff analysis. Ability to diagnose and improve optimization models (e.g., infeasibility, unboundedness, performance tuning, solver settings, reformulation, bounds tightening, decomposition). Strong Python programming skills for optimization, data processing, and service development. Experience developing applications or services on AWS or similar cloud platforms, with familiarity in compute-intensive and batch workloads (e.g., AWS Batch, Fargate/ECS, Lambda, Step Functions, S3, RDS, SageMaker). Familiarity with Infrastructure as Code tools (e.g., Terraform) and modern application architectures (APIs, containers, serverless, event-driven, distributed systems). Experience with Git and GitHub for source control and collaborative development, and interest in AI-enabled development tools (e.g., GitHub Copilot, AI agents, Spec-Driven Development). Experience working with relational, NoSQL, or cloud-based databases (PostgreSQL preferred), including data modeling, validation, and troubleshooting application/data-access issues. Understanding of determinism and reproducibility in solver-based systems (e.g., MIP gaps, tolerances, threads, seeds), and familiarity with sensitivity analysis, duals, and shadow prices. Strong communication skills and ability to explain technical concepts and optimization results to business users, planners, and stakeholders. Experience with capital planning, portfolio optimization, asset management, or utility planning domains is a plus. Experience contributing to reusable software components, frameworks, templates, or shared engineering solutions is a plus. Participation in technical learning activities, communities of practice, hackathons, or innovation events is a plus. Willingness to expand cloud engineering and AI-enabled development skills as part of the role. Familiarity with financial evaluation concepts (e.g., present value, NPV, escalation, discounting) and predictive modeling outputs (e.g., probability of failure, remaining useful life, risk scoring) is a plus. Eight Eleven Group provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, national origin, age, sex, citizenship, disability, genetic information, gender, sexual orientation, gender identity, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state, and local laws.
11/14/2026
Full time
Job Description AI Optimization Engineer Location: Charlotte, NC (Hybrid, 3 days on-site at Optimist Hall Location) or Remote within the U.S. (must be able to work EST hours) Compensation: $80 - $95/hour plus benefits Duration: 12-month contract with strong potential for extension or conversion to full-time employment Employment Requirements: W-2 only. No Corp-to-Corp or 1099 arrangements. Successful candidate must be able to work on W-2 without visa sponsorship both now and in the future. ABOUT THE ROLE Our Client is seeking an AI Optimization Engineer to develop and support the optimization engine at the core of their Capital Investment Planning & Prioritization Tool (CIPT). This tool empowers planning teams to make data-driven decisions about which capital investments to fund, when, and why, by transforming complex business rules into robust, explainable, and auditable optimization models. The role involves designing, building, testing, and maintaining advanced mathematical optimization models-primarily using Mixed-Integer Linear Programming (MILP)-and integrating predictive analytics and benefit measures into portfolio planning. You will work closely with data and ML engineers, leverage cloud-based solutions (primarily AWS), and utilize modern software development practices, including AI-enabled tools like GitHub Copilot and Spec-Driven Development. The ideal candidate combines strong optimization and software engineering fundamentals with a willingness to learn new AI-driven approaches, ensuring solutions are mathematically correct, reproducible, and transparent for planners, finance partners, and regulators. WHAT YOU'LL DO Translate complex capital planning business rules-including budget, resource, cash-flow, jurisdictional, and portfolio constraints-into mathematical optimization models. Formulate, implement, and tune Mixed-Integer Linear Programming (MILP) models using Python frameworks (e.g., Pyomo, PuLP, OR-Tools) and commercial/open-source solvers (e.g., Gurobi, CPLEX, HiGHS, CBC). Integrate predictive model outputs (e.g., Probability of Failure, Remaining Useful Life) and benefit measures (e.g., reliability, safety, financial, NPV) into optimization objectives for portfolio planning. Design, build, and maintain scenario optimization workflows, including scenario creation, copying, optimization across planning cycles, and deterministic run harnesses for reproducible results. Develop diagnostic and infeasibility analysis capabilities (e.g., constraint relaxation, irreducible infeasible subsets, clear error messages) to help planners understand optimization outcomes. Evaluate and recommend solvers and modeling approaches based on solution quality, run-time performance, licensing cost, and operational fit. Package and deploy optimization workloads as scalable cloud services (e.g., AWS Batch, Fargate, Lambda, Step Functions) with REST APIs, leveraging Infrastructure as Code tools (e.g., Terraform). Collaborate with data and ML engineers to integrate asset-health predictions and ensure seamless data flow into optimization models. Build automated test suites for optimization models, including unit tests for constraints, regression tests, reproducibility checks, and comparisons against historical results. Profile and tune model performance using reformulation, tighter bounds, decomposition, warm starts, and solver parameter tuning to meet run-time and scalability targets. Produce clear, explainable outputs for planners and stakeholders, including binding constraints, shadow prices, scenario comparisons, and investment selection rationale. Document model formulations, assumptions, and limitations for business owners, auditors, and future engineers. Contribute reusable optimization components, model templates, test harnesses, and engineering accelerators for broader team and organizational use. Utilize GitHub, GitHub Copilot, and AI agents to enhance software development, testing, and delivery processes; gain hands-on experience with agentic software engineering and automation workflows. Prepare, validate, and troubleshoot large input datasets and database integrations (e.g., PostgreSQL) for optimization models, ensuring data quality and version control. Participate in technical learning activities, communities of practice, hackathons, and innovation events to continuously expand cloud, AI, and optimization engineering skills. WHAT YOU BRING Associate's degree in Information Technology or related field required; Bachelor's or Master's in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or related field preferred. 5+ years of relevant work experience in optimization, software development, or decision-support applications. Hands-on experience designing, building, and supporting optimization models, especially Mixed-Integer Linear Programming (MILP) using frameworks like Pyomo, PuLP, OR-Tools, or Gurobi Python API. Proficiency with commercial or open-source solvers (e.g., Gurobi, CPLEX, HiGHS, CBC) and strong understanding of linear and integer programming, including advanced formulation techniques (e.g., binary selection variables, logical/indicator constraints, big-M, multi-period timing, precedence constraints). Experience modeling knapsack-style and resource-constrained selection or scheduling problems, multi-objective or weighted-objective optimization, and tradeoff analysis. Ability to diagnose and improve optimization models (e.g., infeasibility, unboundedness, performance tuning, solver settings, reformulation, bounds tightening, decomposition). Strong Python programming skills for optimization, data processing, and service development. Experience developing applications or services on AWS or similar cloud platforms, with familiarity in compute-intensive and batch workloads (e.g., AWS Batch, Fargate/ECS, Lambda, Step Functions, S3, RDS, SageMaker). Familiarity with Infrastructure as Code tools (e.g., Terraform) and modern application architectures (APIs, containers, serverless, event-driven, distributed systems). Experience with Git and GitHub for source control and collaborative development, and interest in AI-enabled development tools (e.g., GitHub Copilot, AI agents, Spec-Driven Development). Experience working with relational, NoSQL, or cloud-based databases (PostgreSQL preferred), including data modeling, validation, and troubleshooting application/data-access issues. Understanding of determinism and reproducibility in solver-based systems (e.g., MIP gaps, tolerances, threads, seeds), and familiarity with sensitivity analysis, duals, and shadow prices. Strong communication skills and ability to explain technical concepts and optimization results to business users, planners, and stakeholders. Experience with capital planning, portfolio optimization, asset management, or utility planning domains is a plus. Experience contributing to reusable software components, frameworks, templates, or shared engineering solutions is a plus. Participation in technical learning activities, communities of practice, hackathons, or innovation events is a plus. Willingness to expand cloud engineering and AI-enabled development skills as part of the role. Familiarity with financial evaluation concepts (e.g., present value, NPV, escalation, discounting) and predictive modeling outputs (e.g., probability of failure, remaining useful life, risk scoring) is a plus. Eight Eleven Group provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, national origin, age, sex, citizenship, disability, genetic information, gender, sexual orientation, gender identity, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state, and local laws.
Job Description Role Summary We are seeking a senior, hands-on GECX Architect to design and implement secure, scalable customer experience solutions on Google Gemini Enterprise for Customer Experience platform. The ideal candidate will combine strong architecture design and coding expertise with deep Contact Center, Google GECX/CCAI, Conversational AI, Agentic AI, GenAI/LLM, and Google Cloud experience. This role requires an innovative architect who can build PoCs and accelerators, troubleshoot complex integrations, and take automation solutions from architecture through production implementation. The architect will analyze requirements, compare solution options, recommend the best approach, guide the team, and personally resolve critical design, development, integration, and platform issues. Key Responsibilities Architect end-to-end GECX solutions across voice, chat, web, mobile, and assisted-service journeys. Translate contact center needs into architecture, technical designs, integration patterns, and delivery plans. Compare Google-native, CCaaS, open-source, and third-party tools; recommend options based on fit, security, scalability, cost, and risk. Build and deploy Agentic Voice and Chat solutions using CX Agent Studio, Conversational Agents, Dialogflow CX, Vertex AI, Gemini, and GCP. Design and implement multi-turn conversations, prompts, orchestration, tool calls, fulfillment, context handling, grounding, and human-agent handoff. Design integrations with IVR, telephony, CCaaS, CRM, APIs, databases, and enterprise systems, including SIP/SIPREC, gRPC, and WebRTC where required. Implement GCP components such as Cloud Run, Cloud Functions, BigQuery, Cloud Storage, IAM, logging, monitoring, and data protection services. Working knowledge implementing Services, Components through GCP Stack like GCS, DLP Templates, Cloud Functions, Big Query etc. Working experience with collecting and reviewing reporting data/logs from Google Logs Explorer (Stack Driver), Google Big Query, Avaya, GTP, MS SQL. Lead hands-on coding, configuration, PoCs, troubleshooting, CI/CD, deployment, and production stabilization. Define AI evaluation for task success, response quality, grounding, hallucinations, guardrails, tool use, and agent trajectory. Guide teams, review designs and code, remove technical blockers, and ensure solutions reach production. Required Skills & Technology 12+ years in solution architecture and engineering, including enterprise contact center, conversational AI, or AI/ML delivery. Hands-on expertise in GECX / Customer Engagement Suite, Google CCAI, CX Agent Studio / Conversational Agents, Dialogflow CX, Vertex AI, Gemini, and GCP. Experience building Agentic Voice or Agentic Chat solutions using LLMs, orchestration, tool/function calling, grounding, guardrails, and enterprise integrations. Strong contact center knowledge: IVR, CTI, routing, queues, transfers, SIP, ANI/DNIS, DTMF, STT/TTS, and CRM/backend integration. Strong Python and/or Java skills, REST/JSON APIs, SQL, Git, CI/CD, cloud troubleshooting, IAM, and secure delivery. Ability to conduct structured tool assessments, make architecture decisions, lead cross-functional teams, and communicate with client stakeholders. Strong verbal and written communication skills. Ability to collaborate with onshore/offshore resources on functional/technical /process aspects. This is not a governance-only role. The architect must remain hands-on and own critical solutions through production. Preferred Qualifications Google Cloud certification, preferably Professional Cloud Architect or a role-relevant equivalent. Experience delivering large-scale CCaaS, contact center transformation, or production agentic AI programs. Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
11/14/2026
Full time
Job Description Role Summary We are seeking a senior, hands-on GECX Architect to design and implement secure, scalable customer experience solutions on Google Gemini Enterprise for Customer Experience platform. The ideal candidate will combine strong architecture design and coding expertise with deep Contact Center, Google GECX/CCAI, Conversational AI, Agentic AI, GenAI/LLM, and Google Cloud experience. This role requires an innovative architect who can build PoCs and accelerators, troubleshoot complex integrations, and take automation solutions from architecture through production implementation. The architect will analyze requirements, compare solution options, recommend the best approach, guide the team, and personally resolve critical design, development, integration, and platform issues. Key Responsibilities Architect end-to-end GECX solutions across voice, chat, web, mobile, and assisted-service journeys. Translate contact center needs into architecture, technical designs, integration patterns, and delivery plans. Compare Google-native, CCaaS, open-source, and third-party tools; recommend options based on fit, security, scalability, cost, and risk. Build and deploy Agentic Voice and Chat solutions using CX Agent Studio, Conversational Agents, Dialogflow CX, Vertex AI, Gemini, and GCP. Design and implement multi-turn conversations, prompts, orchestration, tool calls, fulfillment, context handling, grounding, and human-agent handoff. Design integrations with IVR, telephony, CCaaS, CRM, APIs, databases, and enterprise systems, including SIP/SIPREC, gRPC, and WebRTC where required. Implement GCP components such as Cloud Run, Cloud Functions, BigQuery, Cloud Storage, IAM, logging, monitoring, and data protection services. Working knowledge implementing Services, Components through GCP Stack like GCS, DLP Templates, Cloud Functions, Big Query etc. Working experience with collecting and reviewing reporting data/logs from Google Logs Explorer (Stack Driver), Google Big Query, Avaya, GTP, MS SQL. Lead hands-on coding, configuration, PoCs, troubleshooting, CI/CD, deployment, and production stabilization. Define AI evaluation for task success, response quality, grounding, hallucinations, guardrails, tool use, and agent trajectory. Guide teams, review designs and code, remove technical blockers, and ensure solutions reach production. Required Skills & Technology 12+ years in solution architecture and engineering, including enterprise contact center, conversational AI, or AI/ML delivery. Hands-on expertise in GECX / Customer Engagement Suite, Google CCAI, CX Agent Studio / Conversational Agents, Dialogflow CX, Vertex AI, Gemini, and GCP. Experience building Agentic Voice or Agentic Chat solutions using LLMs, orchestration, tool/function calling, grounding, guardrails, and enterprise integrations. Strong contact center knowledge: IVR, CTI, routing, queues, transfers, SIP, ANI/DNIS, DTMF, STT/TTS, and CRM/backend integration. Strong Python and/or Java skills, REST/JSON APIs, SQL, Git, CI/CD, cloud troubleshooting, IAM, and secure delivery. Ability to conduct structured tool assessments, make architecture decisions, lead cross-functional teams, and communicate with client stakeholders. Strong verbal and written communication skills. Ability to collaborate with onshore/offshore resources on functional/technical /process aspects. This is not a governance-only role. The architect must remain hands-on and own critical solutions through production. Preferred Qualifications Google Cloud certification, preferably Professional Cloud Architect or a role-relevant equivalent. Experience delivering large-scale CCaaS, contact center transformation, or production agentic AI programs. Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Job Description EazyML, () recognized by Gartner, specializes in Responsible AI. Our solutions enable proactive compliance and sustainable automation for enterprises adopting AI at scale. We're also associated with breakthrough startups like Amelia.ai, giving our team exposure to cutting-edge AI products at enterprise scale. About the Role We're looking for a Senior Technical Program Manager who will drive end-to-end program management for AI infrastructure deployments, AI Labs initiatives, AI field deployment programs, automation projects, and AI-driven operational transformation initiatives. The role requires a blend of program management leadership, technical acumen mainly in the AI, change management expertise, executive communication skills, and cross-functional coordination capabilities. Program Leadership & Governance Lead multiple concurrent AI programs and strategic initiatives across Agentic /GenAI, solutions. Define program objectives, scope, schedules, milestones, dependencies, and success criteria. Establish and maintain governance structures, steering committees, executive reviews, and stakeholder communication plans. Develop program roadmaps aligned with customers strategic priorities and growth objectives. Drive Foundation AI projects from kickoff through development to deployment and stabilization Support the customer to translate strategy into executable roadmaps with clear milestones, risks, dependencies, and success metrics Develop project plans consistent with business goals and requirements for algorithm performance Establish and maintain program governance, including planning cadences, status reporting, decision forums, and executive communication Bring together key stakeholders to facilitate timely and lasting decision-making Partner with the extended team on availability constraints, capacity forecasting, deadlines etc Partner with the broader team to continuously improve the development process to enable execution of projects in an organized, methodical, and predictable manner. Identify and manage project risks and issues, ensuring mitigations are in place to reduce potential impacts. Facilitate cross-functional communication across teams for awareness and understanding. Understanding of technical issues to facilitate resolution of project blockers is a plus Proactively identify risks, dependencies, and technical blockers and drive cross-functional resolution with urgency. Lead escalation management and executive communications for high-priority issues. Ensure mitigation strategies are implemented and tracked to closure. QUALIFICATIONS: 10+ years of industry experience in program or project management, preferably involving AI/ML, data platforms or large-scale systems Experience working with AI or applied ML teams Familiarity with agile methodologies, sprint planning, backlog grooming processes Data-driven approach to strategic planning, comfortable reviewing metrics and identifying ways to measure program success Familiarity with AI/ML concepts (e.g., model training, inference, data pipelines, evaluation, experimentation), hands-on coding experience is not required Clear, confident communicator who can bridge deeply technical teams and business stakeholders Proven ability to influence without authority and drive alignment across diverse teams Experience working with research teams Background in consumer technology, platforms, or data-driven products Experience organizing projects using Jira or similar platforms Cross-Functional Leadership Collaborate with: Solutions Architects Engineering Integration Center Operations Delivery Teams Product Management Leadership Facilitate alignment across technical and business stakeholders. Resolve conflicts, remove roadblocks, and drive accountability across programs. Resource & Capacity Planning Coordinate resource demand planning across AI project portfolios. Forecast staffing needs and identify capability gaps. Support workforce planning and bench-strength development initiatives. Contribute to the PMO's strategic vision to improve organizational readiness for future AI growth. AI Enablement & Continuous Improvement Support AI training, certification, and capability development programs. Drive adoption of best practices, standards, automation opportunities, and operational efficiencies. Identify opportunities to leverage AI technologies to improve delivery performance and customer experience. Champion continuous improvement initiatives focused on scalability, quality, and delivery excellence. Behaviors and Competencies Communication: Can effectively communicate complex ideas and information to diverse audiences, facilitate effective communication between others, and mentor others in effective communication. Interpersonal Skills: Can communicate effectively, build relationships, resolve conflicts, influence others, and support others in developing their interpersonal skills in major situations. Follow-Up: Can take ownership of tasks, collaborate with others in managing follow-ups, and drive results through effective task completion. Collaboration: Can take ownership of team initiatives, foster a collaborative environment, and ensure that all team members feel valued and heard. Problem-Solving: Can proactively identify and take ownership of complex problem-solving initiatives, initiate preventative measures, collaborate with others to find solutions, and drive successful outcomes. Time Management: Can manage time effectively, accurately estimate the time required for specific tasks, balance multiple tasks, and help others in improving their time management skills. Organization: Can oversee complex projects with multiple moving parts, ensure team alignment with organizational systems, and adapt to changing priorities. Digital Acumen: Can take ownership of complex digital initiatives, collaborate with others, and drive digital results. Leadership: Can take ownership of complex team initiatives, collaborate with others in decision-making processes, and drive team performance.
11/14/2026
Full time
Job Description EazyML, () recognized by Gartner, specializes in Responsible AI. Our solutions enable proactive compliance and sustainable automation for enterprises adopting AI at scale. We're also associated with breakthrough startups like Amelia.ai, giving our team exposure to cutting-edge AI products at enterprise scale. About the Role We're looking for a Senior Technical Program Manager who will drive end-to-end program management for AI infrastructure deployments, AI Labs initiatives, AI field deployment programs, automation projects, and AI-driven operational transformation initiatives. The role requires a blend of program management leadership, technical acumen mainly in the AI, change management expertise, executive communication skills, and cross-functional coordination capabilities. Program Leadership & Governance Lead multiple concurrent AI programs and strategic initiatives across Agentic /GenAI, solutions. Define program objectives, scope, schedules, milestones, dependencies, and success criteria. Establish and maintain governance structures, steering committees, executive reviews, and stakeholder communication plans. Develop program roadmaps aligned with customers strategic priorities and growth objectives. Drive Foundation AI projects from kickoff through development to deployment and stabilization Support the customer to translate strategy into executable roadmaps with clear milestones, risks, dependencies, and success metrics Develop project plans consistent with business goals and requirements for algorithm performance Establish and maintain program governance, including planning cadences, status reporting, decision forums, and executive communication Bring together key stakeholders to facilitate timely and lasting decision-making Partner with the extended team on availability constraints, capacity forecasting, deadlines etc Partner with the broader team to continuously improve the development process to enable execution of projects in an organized, methodical, and predictable manner. Identify and manage project risks and issues, ensuring mitigations are in place to reduce potential impacts. Facilitate cross-functional communication across teams for awareness and understanding. Understanding of technical issues to facilitate resolution of project blockers is a plus Proactively identify risks, dependencies, and technical blockers and drive cross-functional resolution with urgency. Lead escalation management and executive communications for high-priority issues. Ensure mitigation strategies are implemented and tracked to closure. QUALIFICATIONS: 10+ years of industry experience in program or project management, preferably involving AI/ML, data platforms or large-scale systems Experience working with AI or applied ML teams Familiarity with agile methodologies, sprint planning, backlog grooming processes Data-driven approach to strategic planning, comfortable reviewing metrics and identifying ways to measure program success Familiarity with AI/ML concepts (e.g., model training, inference, data pipelines, evaluation, experimentation), hands-on coding experience is not required Clear, confident communicator who can bridge deeply technical teams and business stakeholders Proven ability to influence without authority and drive alignment across diverse teams Experience working with research teams Background in consumer technology, platforms, or data-driven products Experience organizing projects using Jira or similar platforms Cross-Functional Leadership Collaborate with: Solutions Architects Engineering Integration Center Operations Delivery Teams Product Management Leadership Facilitate alignment across technical and business stakeholders. Resolve conflicts, remove roadblocks, and drive accountability across programs. Resource & Capacity Planning Coordinate resource demand planning across AI project portfolios. Forecast staffing needs and identify capability gaps. Support workforce planning and bench-strength development initiatives. Contribute to the PMO's strategic vision to improve organizational readiness for future AI growth. AI Enablement & Continuous Improvement Support AI training, certification, and capability development programs. Drive adoption of best practices, standards, automation opportunities, and operational efficiencies. Identify opportunities to leverage AI technologies to improve delivery performance and customer experience. Champion continuous improvement initiatives focused on scalability, quality, and delivery excellence. Behaviors and Competencies Communication: Can effectively communicate complex ideas and information to diverse audiences, facilitate effective communication between others, and mentor others in effective communication. Interpersonal Skills: Can communicate effectively, build relationships, resolve conflicts, influence others, and support others in developing their interpersonal skills in major situations. Follow-Up: Can take ownership of tasks, collaborate with others in managing follow-ups, and drive results through effective task completion. Collaboration: Can take ownership of team initiatives, foster a collaborative environment, and ensure that all team members feel valued and heard. Problem-Solving: Can proactively identify and take ownership of complex problem-solving initiatives, initiate preventative measures, collaborate with others to find solutions, and drive successful outcomes. Time Management: Can manage time effectively, accurately estimate the time required for specific tasks, balance multiple tasks, and help others in improving their time management skills. Organization: Can oversee complex projects with multiple moving parts, ensure team alignment with organizational systems, and adapt to changing priorities. Digital Acumen: Can take ownership of complex digital initiatives, collaborate with others, and drive digital results. Leadership: Can take ownership of complex team initiatives, collaborate with others in decision-making processes, and drive team performance.
Job Description Our client, a leader in FinTech , is looking to hire a Staff Design Technologist . This is a hybrid role that will be onsite 3x per week in San Diego, CA. This role is a 6-month W2 contract opportunity with benefits & paid holidays! As a Staff Design Technologist , you will lead the technical direction for the development of working prototypes for conversational and agentic AI experiences, building the systems and practices that drive efficient and scalable delivery across both Design and Engineering. Lead large, cross-functional initiatives and set design technology strategy, developing efficient design-to-code handoff processes Build and maintain scalable prototyping frameworks , closing any gaps in process, tooling, data, and team structure Define design system standards, component usage guidelines, and implementation patterns to drive consistency and enable faster deployment of user-facing features Partner with Product Design, Engineering, and Data Science to solve complex use cases Mentor designers and engineers on using data, analytics, research, and technology to improve design outcomes Required Skills & Experience 8+ years of experience as a Design Technologist, UX/UI Engineer, Front-End Engineer, or related field Experience integrating agentic AI, NLU, or LLMs into functional prototypes Expert proficiency in React, TypeScript, HTML, CSS, JavaScript, following WCAG 2.2 AA Experience with Figma, design tokens, Code Connect, or similar design-development integration tools Desired Skills & Experience Bachelor's Degree in Computer Science, UX Design, Product Design, Human-Computer Interaction, or a related field Prior experience in SaaS, FinTech, Financial Services, Banking, or related industries highly valued! Motion Recruitment Partners is an Equal Opportunity Employer, including disability/vets. All applicants must be currently authorized to work on a full-time basis in the country for which they are applying, and no sponsorship is currently available. Employment is subject to the successful completion of a pre-employment screening. Accommodation will be provided in all parts of the hiring process as required under Motion Recruitment Employment Accommodation policy. Applicants need to make their needs known in advance.
11/14/2026
Full time
Job Description Our client, a leader in FinTech , is looking to hire a Staff Design Technologist . This is a hybrid role that will be onsite 3x per week in San Diego, CA. This role is a 6-month W2 contract opportunity with benefits & paid holidays! As a Staff Design Technologist , you will lead the technical direction for the development of working prototypes for conversational and agentic AI experiences, building the systems and practices that drive efficient and scalable delivery across both Design and Engineering. Lead large, cross-functional initiatives and set design technology strategy, developing efficient design-to-code handoff processes Build and maintain scalable prototyping frameworks , closing any gaps in process, tooling, data, and team structure Define design system standards, component usage guidelines, and implementation patterns to drive consistency and enable faster deployment of user-facing features Partner with Product Design, Engineering, and Data Science to solve complex use cases Mentor designers and engineers on using data, analytics, research, and technology to improve design outcomes Required Skills & Experience 8+ years of experience as a Design Technologist, UX/UI Engineer, Front-End Engineer, or related field Experience integrating agentic AI, NLU, or LLMs into functional prototypes Expert proficiency in React, TypeScript, HTML, CSS, JavaScript, following WCAG 2.2 AA Experience with Figma, design tokens, Code Connect, or similar design-development integration tools Desired Skills & Experience Bachelor's Degree in Computer Science, UX Design, Product Design, Human-Computer Interaction, or a related field Prior experience in SaaS, FinTech, Financial Services, Banking, or related industries highly valued! Motion Recruitment Partners is an Equal Opportunity Employer, including disability/vets. All applicants must be currently authorized to work on a full-time basis in the country for which they are applying, and no sponsorship is currently available. Employment is subject to the successful completion of a pre-employment screening. Accommodation will be provided in all parts of the hiring process as required under Motion Recruitment Employment Accommodation policy. Applicants need to make their needs known in advance.
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 Job Title: Cloud Solutions Architect / Cloud Engineer /Application Architect- AI Agentic, Integration & Architecture Location: New York, NY (Hybrid - 3 Days Onsite, 2 Days Remote) Duration: Long Term Contract Certification/Experience: Cloud certification and additional relevant certification Position Summary We are seeking a Senior Cloud Solutions Architect / Cloud Engineer/Application Architect with deep expertise in AI agentic architecture, enterprise integration, and architecture standards. This hands-on role designs agent-based and AI-enabled solutions, defines integration patterns, publishes application architecture standards, and helps establish an Architecture Center of Excellence (COE). The architect will work in Azure, AWS, and hybrid environments. 1. AI Agentic Architecture -Design reference architectures for agentic AI: multi-agent orchestration, tool calling, RAG, and human-in-the-loop controls. - Define secure patterns for integrating agents with enterprise systems and APIs (e.g., MCP, event-driven triggers). - Establish guardrails for agent identity, access, auditability, observability, evaluation, and cost. 2. Integration Architecture - Design and govern API-led, event-driven, and messaging integration patterns, including API lifecycle and gateway strategy. - Define integration patterns for legacy, SaaS, and cloud-native systems. 3. Standards & Architecture COE - Develop, publish, and maintain application, integration, API, and AI architecture standards and reference architectures. - Help establish and operate the COE: charter, governance forums, design reviews, training, and playbooks. - Define COE and standards-adoption metrics in coordination with AI IT adoption tracking. 4. Modernization, Security & Collaboration - Guide application modernization and cloud design on Azure, AWS, and hybrid environments. - Align designs with NIST (incl. AI RMF), CIS, ISO 27001, and security requirements. - Partner with product, engineering, DevOps, and Cybersecurity teams; communicate clearly to business and technical stakeholders. Qualifications 10+ years of application/enterprise architecture experience, including cloud-native design on Azure and/or AWS. Experience delivering AI/LLM or agentic solutions in an enterprise. Experience authoring standards and operating an architecture COE or review board. Strong integration/API expertise and executive-level communication
11/14/2026
Full time
Job Description Job Title: Cloud Solutions Architect / Cloud Engineer /Application Architect- AI Agentic, Integration & Architecture Location: New York, NY (Hybrid - 3 Days Onsite, 2 Days Remote) Duration: Long Term Contract Certification/Experience: Cloud certification and additional relevant certification Position Summary We are seeking a Senior Cloud Solutions Architect / Cloud Engineer/Application Architect with deep expertise in AI agentic architecture, enterprise integration, and architecture standards. This hands-on role designs agent-based and AI-enabled solutions, defines integration patterns, publishes application architecture standards, and helps establish an Architecture Center of Excellence (COE). The architect will work in Azure, AWS, and hybrid environments. 1. AI Agentic Architecture -Design reference architectures for agentic AI: multi-agent orchestration, tool calling, RAG, and human-in-the-loop controls. - Define secure patterns for integrating agents with enterprise systems and APIs (e.g., MCP, event-driven triggers). - Establish guardrails for agent identity, access, auditability, observability, evaluation, and cost. 2. Integration Architecture - Design and govern API-led, event-driven, and messaging integration patterns, including API lifecycle and gateway strategy. - Define integration patterns for legacy, SaaS, and cloud-native systems. 3. Standards & Architecture COE - Develop, publish, and maintain application, integration, API, and AI architecture standards and reference architectures. - Help establish and operate the COE: charter, governance forums, design reviews, training, and playbooks. - Define COE and standards-adoption metrics in coordination with AI IT adoption tracking. 4. Modernization, Security & Collaboration - Guide application modernization and cloud design on Azure, AWS, and hybrid environments. - Align designs with NIST (incl. AI RMF), CIS, ISO 27001, and security requirements. - Partner with product, engineering, DevOps, and Cybersecurity teams; communicate clearly to business and technical stakeholders. Qualifications 10+ years of application/enterprise architecture experience, including cloud-native design on Azure and/or AWS. Experience delivering AI/LLM or agentic solutions in an enterprise. Experience authoring standards and operating an architecture COE or review board. Strong integration/API expertise and executive-level communication
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 End Client: Metropolitan Transportation Authority (MTA) Job Title: Senior AI & Cloud Solutions Architect Duration: 12 months + Extension Location: New York, NY (Hybrid - 3 Days Onsite, 2 Days Remote) Number of Hours: 37.5 Hours a week Interview Type: Webcam or In-Person Ceipal ID: MTA_AI122_MA Job Code: 6122-1 Scope of Project: The MTA is seeking a Senior Cloud Solutions Architect / Cloud Engineer/Application Architect with deep expertise in AI agentic architecture, enterprise integration, and architecture standards. This hands-on role designs agent-based and AI-enabled solutions, defines integration patterns, publishes application architecture standards, and helps establish an Architecture Center of Excellence (COE). The architect will work in Azure, AWS, and hybrid environments. Responsibilities: 1. AI Agentic Architecture Design reference architectures for agentic AI: multi-agent orchestration, tool calling, RAG, and human-in-the-loop controls. Define secure patterns for integrating agents with enterprise systems and APIs (e.g., MCP, event-driven triggers). Establish guardrails for agent identity, access, auditability, observability, evaluation, and cost. 2. Integration Architecture Design and govern API-led, event-driven, and messaging integration patterns, including API lifecycle and gateway strategy. Define integration patterns for legacy, SaaS, and cloud-native systems. 3. Standards & Architecture COE Develop, publish, and maintain application, integration, API, and AI architecture standards and reference architectures. Help establish and operate the COE: charter, governance forums, design reviews, training, and playbooks. Define COE and standards-adoption metrics in coordination with AI IT adoption tracking. 4. Modernization, Security & Collaboration Guide application modernization and cloud design on Azure, AWS, and hybrid environments. Align designs with NIST (incl. AI RMF), CIS, ISO 27001, and MTA security requirements. Partner with product, engineering, DevOps, and Cybersecurity teams; communicate clearly to business and technical stakeholders. Required/Preferred Skills: 10+ years of application/enterprise architecture experience, including cloud-native design on Azure and/or AWS. Experience delivering AI/LLM or agentic solutions in an enterprise. Experience authoring standards and operating an architecture COE or review board. Strong integration/API expertise and executive-level communication. Cloud certification and additional relevant certification preferred. Expertise in agentic AI architecture, multi-agent orchestration, tool calling, RAG, and human-in-the-loop controls. Experience with enterprise systems and APIs, MCP, and event-driven triggers. Knowledge of API-led, event-driven, and messaging integration patterns, API lifecycle, and gateway strategy. Experience with legacy, SaaS, and cloud-native integration. Experience developing application, integration, API, and AI architecture standards and reference architectures. Experience establishing and operating an Architecture Center of Excellence (COE), including governance forums, design reviews, training, and playbooks. Knowledge of Azure, AWS, hybrid cloud environments, NIST AI RMF, CIS, ISO 27001, and enterprise security requirements. V Group Inc. is a NJ-based IT Services and Products Company with its business strategically categorized in various Business Units including Public Sector, Enterprise Solutions, Professional Services, Ecommerce, Projects, and Products. Within Public Sector business unit, we cater IT Professional Services to Federal, State and Local. We have multiple awards/ contracts with 30+ states, including but not limited to NY, CA, FL, GA, MD, MI, NC, OH, OR, CO, CT, TN, PA, TX, VA, NM, VT, and WA. If you are considering applying for a position with V Group, or in partnering with us on a position, please feel free to contact me for any questions you may have regarding our services and the advantages we can offer you as a consultant. Please share my contact information with others working in Information Technology. Website: LinkedIn: -group/ Facebook: Twitter:
11/14/2026
Full time
Job Description End Client: Metropolitan Transportation Authority (MTA) Job Title: Senior AI & Cloud Solutions Architect Duration: 12 months + Extension Location: New York, NY (Hybrid - 3 Days Onsite, 2 Days Remote) Number of Hours: 37.5 Hours a week Interview Type: Webcam or In-Person Ceipal ID: MTA_AI122_MA Job Code: 6122-1 Scope of Project: The MTA is seeking a Senior Cloud Solutions Architect / Cloud Engineer/Application Architect with deep expertise in AI agentic architecture, enterprise integration, and architecture standards. This hands-on role designs agent-based and AI-enabled solutions, defines integration patterns, publishes application architecture standards, and helps establish an Architecture Center of Excellence (COE). The architect will work in Azure, AWS, and hybrid environments. Responsibilities: 1. AI Agentic Architecture Design reference architectures for agentic AI: multi-agent orchestration, tool calling, RAG, and human-in-the-loop controls. Define secure patterns for integrating agents with enterprise systems and APIs (e.g., MCP, event-driven triggers). Establish guardrails for agent identity, access, auditability, observability, evaluation, and cost. 2. Integration Architecture Design and govern API-led, event-driven, and messaging integration patterns, including API lifecycle and gateway strategy. Define integration patterns for legacy, SaaS, and cloud-native systems. 3. Standards & Architecture COE Develop, publish, and maintain application, integration, API, and AI architecture standards and reference architectures. Help establish and operate the COE: charter, governance forums, design reviews, training, and playbooks. Define COE and standards-adoption metrics in coordination with AI IT adoption tracking. 4. Modernization, Security & Collaboration Guide application modernization and cloud design on Azure, AWS, and hybrid environments. Align designs with NIST (incl. AI RMF), CIS, ISO 27001, and MTA security requirements. Partner with product, engineering, DevOps, and Cybersecurity teams; communicate clearly to business and technical stakeholders. Required/Preferred Skills: 10+ years of application/enterprise architecture experience, including cloud-native design on Azure and/or AWS. Experience delivering AI/LLM or agentic solutions in an enterprise. Experience authoring standards and operating an architecture COE or review board. Strong integration/API expertise and executive-level communication. Cloud certification and additional relevant certification preferred. Expertise in agentic AI architecture, multi-agent orchestration, tool calling, RAG, and human-in-the-loop controls. Experience with enterprise systems and APIs, MCP, and event-driven triggers. Knowledge of API-led, event-driven, and messaging integration patterns, API lifecycle, and gateway strategy. Experience with legacy, SaaS, and cloud-native integration. Experience developing application, integration, API, and AI architecture standards and reference architectures. Experience establishing and operating an Architecture Center of Excellence (COE), including governance forums, design reviews, training, and playbooks. Knowledge of Azure, AWS, hybrid cloud environments, NIST AI RMF, CIS, ISO 27001, and enterprise security requirements. V Group Inc. is a NJ-based IT Services and Products Company with its business strategically categorized in various Business Units including Public Sector, Enterprise Solutions, Professional Services, Ecommerce, Projects, and Products. Within Public Sector business unit, we cater IT Professional Services to Federal, State and Local. We have multiple awards/ contracts with 30+ states, including but not limited to NY, CA, FL, GA, MD, MI, NC, OH, OR, CO, CT, TN, PA, TX, VA, NM, VT, and WA. If you are considering applying for a position with V Group, or in partnering with us on a position, please feel free to contact me for any questions you may have regarding our services and the advantages we can offer you as a consultant. Please share my contact information with others working in Information Technology. Website: LinkedIn: -group/ Facebook: Twitter:
Job Description Job Title: GenAI Architect Location: New York City, NY (Onsite/Local Candidates Preferred) Experience: 10+ Years Visa: Open to All Visa Types Job Summary: We are seeking an experienced GenAI Architect with 10+ years of overall experience to design, architect, and lead the delivery of enterprise-grade Generative AI solutions. The ideal candidate will have strong expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI workflows, and cloud-based AI architectures. The candidate will be responsible for translating business requirements into scalable, secure, and production-ready AI solutions while collaborating closely with business stakeholders, data scientists, and engineering teams. Key Responsibilities: Design and architect enterprise-grade Generative AI solutions leveraging LLMs, RAG pipelines, and agentic AI frameworks. Lead the development and implementation of scalable AI applications and intelligent automation solutions. Architect end-to-end RAG solutions, including document ingestion, chunking, embedding generation, vector databases, retrieval, and response generation. Design and implement agentic workflows using tools, APIs, orchestration frameworks, and multi-agent architectures. Evaluate and integrate LLM models from providers such as OpenAI, Anthropic, Google, and open-source ecosystems. Leverage cloud platforms such as AWS, Azure, or GCP to build and deploy enterprise AI solutions. Establish best practices for prompt engineering, context management, model evaluation, performance optimization, and LLM observability. Ensure AI solutions meet enterprise requirements for security, scalability, governance, compliance, and responsible AI. Collaborate with business stakeholders and technical teams to identify AI opportunities and translate business use cases into technical architectures. Provide technical leadership, architecture guidance, and mentorship to engineering teams throughout the development lifecycle. Required Technical Skills: 10+ years of overall experience in software engineering, solution architecture, AI/ML, or related technology domains. Strong hands-on experience designing and implementing Generative AI and LLM-based applications. Extensive experience with RAG architecture, vector databases, embeddings, semantic search, and knowledge retrieval systems. Strong understanding of Agentic AI, AI agents, multi-agent systems, and tool/function calling. Experience with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar. Proficiency in Python and experience developing enterprise-grade applications and APIs. Experience working with LLM providers such as OpenAI, Azure OpenAI, Anthropic, Gemini, or open-source LLMs. Strong experience with at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform. Knowledge of vector databases such as Pinecone, Azure AI Search, FAISS, Weaviate, Milvus, or Chroma. Understanding of LLMOps, model deployment, monitoring, evaluation, and optimization. Experience with enterprise security, data privacy, access controls, and responsible AI practices. Preferred Qualifications: Experience architecting and delivering enterprise-scale GenAI solutions from concept to production. Knowledge of Kubernetes, Docker, microservices, and CI/CD pipelines. Experience with fine-tuning, model customization, and prompt optimization. Familiarity with AI governance, guardrails, hallucination mitigation, and responsible AI implementation. Excellent communication, stakeholder management, and technical leadership skills.
11/14/2026
Full time
Job Description Job Title: GenAI Architect Location: New York City, NY (Onsite/Local Candidates Preferred) Experience: 10+ Years Visa: Open to All Visa Types Job Summary: We are seeking an experienced GenAI Architect with 10+ years of overall experience to design, architect, and lead the delivery of enterprise-grade Generative AI solutions. The ideal candidate will have strong expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI workflows, and cloud-based AI architectures. The candidate will be responsible for translating business requirements into scalable, secure, and production-ready AI solutions while collaborating closely with business stakeholders, data scientists, and engineering teams. Key Responsibilities: Design and architect enterprise-grade Generative AI solutions leveraging LLMs, RAG pipelines, and agentic AI frameworks. Lead the development and implementation of scalable AI applications and intelligent automation solutions. Architect end-to-end RAG solutions, including document ingestion, chunking, embedding generation, vector databases, retrieval, and response generation. Design and implement agentic workflows using tools, APIs, orchestration frameworks, and multi-agent architectures. Evaluate and integrate LLM models from providers such as OpenAI, Anthropic, Google, and open-source ecosystems. Leverage cloud platforms such as AWS, Azure, or GCP to build and deploy enterprise AI solutions. Establish best practices for prompt engineering, context management, model evaluation, performance optimization, and LLM observability. Ensure AI solutions meet enterprise requirements for security, scalability, governance, compliance, and responsible AI. Collaborate with business stakeholders and technical teams to identify AI opportunities and translate business use cases into technical architectures. Provide technical leadership, architecture guidance, and mentorship to engineering teams throughout the development lifecycle. Required Technical Skills: 10+ years of overall experience in software engineering, solution architecture, AI/ML, or related technology domains. Strong hands-on experience designing and implementing Generative AI and LLM-based applications. Extensive experience with RAG architecture, vector databases, embeddings, semantic search, and knowledge retrieval systems. Strong understanding of Agentic AI, AI agents, multi-agent systems, and tool/function calling. Experience with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar. Proficiency in Python and experience developing enterprise-grade applications and APIs. Experience working with LLM providers such as OpenAI, Azure OpenAI, Anthropic, Gemini, or open-source LLMs. Strong experience with at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform. Knowledge of vector databases such as Pinecone, Azure AI Search, FAISS, Weaviate, Milvus, or Chroma. Understanding of LLMOps, model deployment, monitoring, evaluation, and optimization. Experience with enterprise security, data privacy, access controls, and responsible AI practices. Preferred Qualifications: Experience architecting and delivering enterprise-scale GenAI solutions from concept to production. Knowledge of Kubernetes, Docker, microservices, and CI/CD pipelines. Experience with fine-tuning, model customization, and prompt optimization. Familiarity with AI governance, guardrails, hallucination mitigation, and responsible AI implementation. Excellent communication, stakeholder management, and technical leadership skills.
Job Description .Net Lead Developer Job Location: Fort Mill, SC / New York Employment Type: Full Time Experience: 12-15 Years Salary - $135K (SC) $145K (NY) About the Role We are looking for a highly skilled .NET Lead Developer with strong experience in enterprise application development, AWS cloud-native technologies, and modern AI/GenAI solutions. The ideal candidate will provide technical leadership while designing and developing scalable .NET applications and cloud-based solutions for the Financial Services and Wealth Management domain. The role requires strong hands-on expertise in .NET Core, C#, AWS, Angular, APIs, microservices, and AI-assisted development, along with the ability to lead technical initiatives, mentor developers, and collaborate with business and technology stakeholders. Responsibilities • Lead the design, development, and delivery of scalable enterprise applications using .NET Core, C#, and Angular. • Design and implement cloud-native solutions on AWS, leveraging services such as Lambda, ECS/EKS, S3, API Gateway, CloudWatch, RDS, and other AWS services. • Lead the development of REST APIs, microservices, and distributed applications following scalable architecture and design principles. • Drive the adoption and integration of AI/GenAI and Agentic AI tools to improve application capabilities, engineering productivity, and automation. • Collaborate with Product Owners, Architects, QA teams, and business stakeholders to translate requirements into technical solutions. • Provide technical leadership, conduct code reviews, establish development best practices, and mentor junior and mid-level developers. • Participate in architecture discussions, performance tuning, production support, and technical troubleshooting. • Ensure applications meet enterprise standards for security, scalability, performance, reliability, and maintainability. • Contribute to AWS cloud modernization and application transformation initiatives within the Financial Services domain. Qualifications • 8+ years of overall software development experience, with strong experience in .NET technologies. • Proven experience as a Technical Lead / Lead Developer in enterprise application development. • 3+ years of hands-on experience with AWS cloud technologies. • Strong experience in Financial Services, Banking, Wealth Management, or related financial technology domains. • Strong hands-on experience with Angular and modern UI development. • Experience working with AI copilots, GenAI, Agentic AI frameworks, LLM-based applications, or AI-assisted development tools. • AWS or Microsoft certifications are preferred. Required Skills • Strong expertise in .NET Core / ASP.NET Core and C#. • Strong hands-on experience with AWS Cloud Services, including Lambda, ECS/EKS, S3, API Gateway, CloudWatch, RDS, IAM, and related services. • Strong experience designing and developing REST APIs and microservices. • Strong frontend development experience using Angular. • Hands-on experience with SQL Server, database design, and performance optimization. • Experience with AI/GenAI technologies, Agentic AI tools, LLM integrations, or AI-assisted software development platforms. • Strong understanding of cloud-native architecture, distributed systems, and scalable application design. • Experience with CI/CD pipelines, DevOps practices, Git, and cloud deployment automation. • Strong understanding of application security, performance, scalability, and reliability. • Excellent communication, stakeholder management, problem-solving, and technical leadership skills. Preferred Skills Strong experience in Wealth Management / Financial Services / Banking applications and platforms. Experience with AWS Bedrock or other enterprise GenAI services. Exposure to RAG, prompt engineering, LLM integrations, AI agents, or Agentic AI frameworks. Experience with event-driven architecture and messaging systems such as SQS, SNS, Kafka, or EventBridge. Experience with Docker and Kubernetes/EKS. Experience with AWS application modernization and migration initiatives. Familiarity with Agile/Scrum methodologies and working with distributed engineering teams.
11/14/2026
Full time
Job Description .Net Lead Developer Job Location: Fort Mill, SC / New York Employment Type: Full Time Experience: 12-15 Years Salary - $135K (SC) $145K (NY) About the Role We are looking for a highly skilled .NET Lead Developer with strong experience in enterprise application development, AWS cloud-native technologies, and modern AI/GenAI solutions. The ideal candidate will provide technical leadership while designing and developing scalable .NET applications and cloud-based solutions for the Financial Services and Wealth Management domain. The role requires strong hands-on expertise in .NET Core, C#, AWS, Angular, APIs, microservices, and AI-assisted development, along with the ability to lead technical initiatives, mentor developers, and collaborate with business and technology stakeholders. Responsibilities • Lead the design, development, and delivery of scalable enterprise applications using .NET Core, C#, and Angular. • Design and implement cloud-native solutions on AWS, leveraging services such as Lambda, ECS/EKS, S3, API Gateway, CloudWatch, RDS, and other AWS services. • Lead the development of REST APIs, microservices, and distributed applications following scalable architecture and design principles. • Drive the adoption and integration of AI/GenAI and Agentic AI tools to improve application capabilities, engineering productivity, and automation. • Collaborate with Product Owners, Architects, QA teams, and business stakeholders to translate requirements into technical solutions. • Provide technical leadership, conduct code reviews, establish development best practices, and mentor junior and mid-level developers. • Participate in architecture discussions, performance tuning, production support, and technical troubleshooting. • Ensure applications meet enterprise standards for security, scalability, performance, reliability, and maintainability. • Contribute to AWS cloud modernization and application transformation initiatives within the Financial Services domain. Qualifications • 8+ years of overall software development experience, with strong experience in .NET technologies. • Proven experience as a Technical Lead / Lead Developer in enterprise application development. • 3+ years of hands-on experience with AWS cloud technologies. • Strong experience in Financial Services, Banking, Wealth Management, or related financial technology domains. • Strong hands-on experience with Angular and modern UI development. • Experience working with AI copilots, GenAI, Agentic AI frameworks, LLM-based applications, or AI-assisted development tools. • AWS or Microsoft certifications are preferred. Required Skills • Strong expertise in .NET Core / ASP.NET Core and C#. • Strong hands-on experience with AWS Cloud Services, including Lambda, ECS/EKS, S3, API Gateway, CloudWatch, RDS, IAM, and related services. • Strong experience designing and developing REST APIs and microservices. • Strong frontend development experience using Angular. • Hands-on experience with SQL Server, database design, and performance optimization. • Experience with AI/GenAI technologies, Agentic AI tools, LLM integrations, or AI-assisted software development platforms. • Strong understanding of cloud-native architecture, distributed systems, and scalable application design. • Experience with CI/CD pipelines, DevOps practices, Git, and cloud deployment automation. • Strong understanding of application security, performance, scalability, and reliability. • Excellent communication, stakeholder management, problem-solving, and technical leadership skills. Preferred Skills Strong experience in Wealth Management / Financial Services / Banking applications and platforms. Experience with AWS Bedrock or other enterprise GenAI services. Exposure to RAG, prompt engineering, LLM integrations, AI agents, or Agentic AI frameworks. Experience with event-driven architecture and messaging systems such as SQS, SNS, Kafka, or EventBridge. Experience with Docker and Kubernetes/EKS. Experience with AWS application modernization and migration initiatives. Familiarity with Agile/Scrum methodologies and working with distributed engineering teams.
Job Description AI ML Engineer Intern - Winter / Spring 2027 (Master's or PhD) Salary: $25 - 30/ hr About Akoncagua AI Akoncagua AI builds domain-specialized AI systems for technically demanding industries. Our work includes LLMs, multimodal AI, agentic automation, RAG, evaluation, and production AI infrastructure. We are seeking an AI Automation Engineer Intern to help build secure, reliable AI agents and automated workflows for accounting and enterprise finance. What you'll work on Build and improve LLM agent workflows for document intake, classification, and transaction coding Develop document-intelligence pipelines for invoices, receipts, contracts, and financial statements Implement retrieval over accounting policies, vendor records, and historical transactions Write evaluation harnesses that measure extraction accuracy, classification quality, and end-to-end workflow outcomes Add tracing and observability for prompts, tool calls, failures, latency, and cost Integrate agents with accounting platforms, databases, and internal APIs Required qualifications Currently enrolled in a Master's or PhD program in Computer Science, AI/ML, or a related technical field, or equivalent practical experience Strong Python skills, plus solid fundamentals in data structures, debugging, and testing Experience building LLM-based applications, whether through coursework, research, personal projects, or internships Familiarity with at least one agent framework such as LangGraph, AutoGen/AG2, Semantic Kernel, or the OpenAI Agents SDK Working knowledge of RAG and vector databases Comfortable with Docker and version control in a collaborative codebase Preferred qualifications Experience with MCP or similar tool-integration standards Experience with n8n, Zapier, Make, or event-driven automation Exposure to FastAPI, PostgreSQL, pgvector, or Kubernetes Interest in or exposure to accounting concepts such as double-entry bookkeeping, journal entries, reconciliations, or approval controls Awareness of prompt-injection risks, least-privilege design, and secrets management Strong understanding of multi-GPU Linux server environments, with hands-on experience configuring, managing, and effectively utilizing GPU resources. Open-source contributions or publications at AI conferences How we work We care about researchers and engineers who understand and can defend the design decisions in their code. AI coding tools are welcome here, but you should be able to explain why a system works the way it does, what evidence supports it, and where it breaks. Our work connects model research with the systems required to run it. You will have room to explore new ideas, but you will also be expected to build working implementations, measure them carefully, and communicate their limitations clearly.
11/14/2026
Full time
Job Description AI ML Engineer Intern - Winter / Spring 2027 (Master's or PhD) Salary: $25 - 30/ hr About Akoncagua AI Akoncagua AI builds domain-specialized AI systems for technically demanding industries. Our work includes LLMs, multimodal AI, agentic automation, RAG, evaluation, and production AI infrastructure. We are seeking an AI Automation Engineer Intern to help build secure, reliable AI agents and automated workflows for accounting and enterprise finance. What you'll work on Build and improve LLM agent workflows for document intake, classification, and transaction coding Develop document-intelligence pipelines for invoices, receipts, contracts, and financial statements Implement retrieval over accounting policies, vendor records, and historical transactions Write evaluation harnesses that measure extraction accuracy, classification quality, and end-to-end workflow outcomes Add tracing and observability for prompts, tool calls, failures, latency, and cost Integrate agents with accounting platforms, databases, and internal APIs Required qualifications Currently enrolled in a Master's or PhD program in Computer Science, AI/ML, or a related technical field, or equivalent practical experience Strong Python skills, plus solid fundamentals in data structures, debugging, and testing Experience building LLM-based applications, whether through coursework, research, personal projects, or internships Familiarity with at least one agent framework such as LangGraph, AutoGen/AG2, Semantic Kernel, or the OpenAI Agents SDK Working knowledge of RAG and vector databases Comfortable with Docker and version control in a collaborative codebase Preferred qualifications Experience with MCP or similar tool-integration standards Experience with n8n, Zapier, Make, or event-driven automation Exposure to FastAPI, PostgreSQL, pgvector, or Kubernetes Interest in or exposure to accounting concepts such as double-entry bookkeeping, journal entries, reconciliations, or approval controls Awareness of prompt-injection risks, least-privilege design, and secrets management Strong understanding of multi-GPU Linux server environments, with hands-on experience configuring, managing, and effectively utilizing GPU resources. Open-source contributions or publications at AI conferences How we work We care about researchers and engineers who understand and can defend the design decisions in their code. AI coding tools are welcome here, but you should be able to explain why a system works the way it does, what evidence supports it, and where it breaks. Our work connects model research with the systems required to run it. You will have room to explore new ideas, but you will also be expected to build working implementations, measure them carefully, and communicate their limitations clearly.
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.
Job Description Intellibus Consulting is a boutique engineering and AI transformation firm that builds mission-critical platforms for global financial institutions. We operate at the intersection of engineering excellence, business outcomes, and executive-level delivery. At Intellibus, our leaders are hands-on builders who understand technology deeply, engage confidently with senior executives, and take ownership of client success. We believe successful technology transformation requires leaders who can connect business strategy, architecture, engineering, and execution Job Description We are looking for exceptional Forward Deployed Engineers with deep hands-on software engineering expertise, particularly in Java, backend engineering, full-stack development, microservices, and distributed systems. This is a highly technical, client-facing engineering role that requires someone who can move seamlessly between architecture, software development, solution delivery, and executive-level client engagement. You will work directly with client engineering teams, technology leaders, and business stakeholders to understand complex challenges, design technical solutions, and lead the development and implementation of enterprise-grade platforms. Beyond engineering delivery, you will play an important role in expanding strategic client relationships by identifying technology opportunities, recommending solutions, demonstrating technical capabilities, and helping grow existing accounts. We are specifically looking for engineers who have worked in technology consulting or professional services environments and are comfortable taking ownership of both technical delivery and client relationships. Key Responsibilities Hands-on Software Engineering & Architecture Design, develop, and deliver scalable enterprise applications using Java and modern software engineering technologies. Demonstrate deep hands-on expertise in Java, Spring Boot, Spring Framework, REST APIs, and backend application development. Build complex microservices-based architectures, distributed systems, and event-driven applications. Develop full-stack solutions with strong backend capabilities and practical frontend development experience. Work across the entire software development lifecycle, from architecture and design through coding, testing, deployment, and production support. Lead technical implementation while remaining actively involved in writing and reviewing code. Develop reusable components, APIs, integrations, and enterprise application frameworks. Troubleshoot performance bottlenecks, scalability challenges, concurrency issues, and complex production defects. Backend, Frontend & Full-Stack Development Build backend services using Java, Spring Boot, Hibernate, JPA, and related technologies. Design and implement RESTful APIs, microservices, and enterprise integrations. Develop frontend applications using React, JavaScript, TypeScript, HTML, and CSS. Integrate frontend applications with backend services and enterprise platforms. Work with relational and NoSQL databases, including PostgreSQL, Oracle, MongoDB, or similar technologies. Implement authentication, authorization, security, and API integration patterns. Ensure application performance, maintainability, reliability, and scalability. Microservices & Cloud-Native Engineering Design and implement microservices architectures and distributed application platforms. Work with messaging and event-streaming technologies such as Apache Kafka. Build asynchronous processing, event-driven integrations, and resilient distributed services. Apply design patterns for service discovery, fault tolerance, circuit breakers, and distributed transactions. Deploy and operate applications on AWS, Azure, or GCP. Work with Docker, Kubernetes, CI/CD pipelines, and infrastructure automation. Apply observability practices using logging, monitoring, tracing, and performance management tools. Understand cloud-native architecture, scalability, availability, and system reliability. AI & Agentic Engineering Explore and implement AI-powered enterprise applications and intelligent workflows. Integrate LLMs and AI capabilities into existing enterprise applications and platforms. Develop AI agents, tool-calling workflows, and agent orchestration capabilities. Work with retrieval-augmented generation (RAG), vector databases, and enterprise data integrations. Identify opportunities to apply AI and automation to solve client business and technology challenges. Build practical prototypes and take successful AI solutions through production implementation. Client Consulting & Strategic Account Growth Work directly with client CTOs, CIOs, engineering leaders, architects, and business stakeholders. Understand client technology environments, business priorities, and strategic challenges. Translate business problems into technical solutions and actionable engineering roadmaps. Lead technical discovery sessions, architecture discussions, solution demonstrations, and client workshops. Identify opportunities for platform modernization, application development, cloud transformation, and AI adoption. Help expand existing client engagements by identifying new projects, engineering opportunities, and areas where Intellibus can add value. Build trusted relationships with client stakeholders and contribute to long-term account growth. Prepare technical proposals, solution presentations, architecture diagrams, and executive-level materials. Collaborate with leadership and account teams to shape new opportunities and support business development. Required Technical Expertise Java & Backend Engineering Extensive hands-on experience with Java and Spring Boot. Strong understanding of OOP, multithreading, concurrency, collections, JVM fundamentals, and performance optimization. Experience with REST APIs, Hibernate, JPA, and enterprise application development. Strong knowledge of backend architecture and enterprise integration patterns. Full-Stack Development Experience building frontend applications using React, JavaScript, and TypeScript. Ability to independently work across backend and frontend components. Strong understanding of API integration and application architecture. Microservices & Distributed Systems Deep experience designing and implementing microservices architectures. Strong knowledge of Kafka, event-driven systems, messaging, and distributed computing. Understanding of scalability, resiliency, fault tolerance, and high-availability architecture. Cloud & DevOps Experience with AWS, Azure, or GCP. Hands-on experience with Docker, Kubernetes, CI/CD, and cloud-native deployments. Familiarity with Terraform or other infrastructure-as-code tools is preferred. AI & Modern Engineering Exposure to LLM integrations, generative AI, AI agents, and agentic workflows. Experience integrating AI capabilities into enterprise software is highly desirable. Required Consulting & Client Engagement Experience Previous experience working for a technology consulting firm, systems integrator, or professional services organization is mandatory. Demonstrated experience delivering technology solutions for external enterprise clients. Ability to manage multiple technical stakeholders and work across different client environments. Strong executive communication and presentation skills. Ability to identify additional technology opportunities and contribute to account expansion. Comfortable operating in fast-paced consulting environments where priorities and client requirements can evolve. Qualifications Bachelor's or Master's degree in Computer Science, Engineering, or a related technical discipline, or equivalent practical experience. Significant professional software engineering experience, ideally 8+ years. Extensive hands-on Java and backend engineering experience. Proven experience building enterprise-grade microservices and distributed systems. Full-stack development experience with modern frontend frameworks. Previous consulting or professional services experience is mandatory. Experience working in financial services, banking, fintech, or other regulated industries is strongly preferred. What Success Looks Like You can independently design, code, and deliver complex enterprise applications. You bring deep technical expertise in Java, backend engineering, full-stack development, and microservices. You can engage with client engineering teams and senior executives with equal confidence. You identify opportunities to solve broader client challenges beyond the immediate assignment. You help strengthen client relationships and contribute to expanding strategic accounts. You take ownership of solutions from initial discovery through architecture, implementation, and production deployment. Who Should Apply? We are looking for engineers who are not limited to writing code against predefined requirements. . click apply for full job details
11/14/2026
Full time
Job Description Intellibus Consulting is a boutique engineering and AI transformation firm that builds mission-critical platforms for global financial institutions. We operate at the intersection of engineering excellence, business outcomes, and executive-level delivery. At Intellibus, our leaders are hands-on builders who understand technology deeply, engage confidently with senior executives, and take ownership of client success. We believe successful technology transformation requires leaders who can connect business strategy, architecture, engineering, and execution Job Description We are looking for exceptional Forward Deployed Engineers with deep hands-on software engineering expertise, particularly in Java, backend engineering, full-stack development, microservices, and distributed systems. This is a highly technical, client-facing engineering role that requires someone who can move seamlessly between architecture, software development, solution delivery, and executive-level client engagement. You will work directly with client engineering teams, technology leaders, and business stakeholders to understand complex challenges, design technical solutions, and lead the development and implementation of enterprise-grade platforms. Beyond engineering delivery, you will play an important role in expanding strategic client relationships by identifying technology opportunities, recommending solutions, demonstrating technical capabilities, and helping grow existing accounts. We are specifically looking for engineers who have worked in technology consulting or professional services environments and are comfortable taking ownership of both technical delivery and client relationships. Key Responsibilities Hands-on Software Engineering & Architecture Design, develop, and deliver scalable enterprise applications using Java and modern software engineering technologies. Demonstrate deep hands-on expertise in Java, Spring Boot, Spring Framework, REST APIs, and backend application development. Build complex microservices-based architectures, distributed systems, and event-driven applications. Develop full-stack solutions with strong backend capabilities and practical frontend development experience. Work across the entire software development lifecycle, from architecture and design through coding, testing, deployment, and production support. Lead technical implementation while remaining actively involved in writing and reviewing code. Develop reusable components, APIs, integrations, and enterprise application frameworks. Troubleshoot performance bottlenecks, scalability challenges, concurrency issues, and complex production defects. Backend, Frontend & Full-Stack Development Build backend services using Java, Spring Boot, Hibernate, JPA, and related technologies. Design and implement RESTful APIs, microservices, and enterprise integrations. Develop frontend applications using React, JavaScript, TypeScript, HTML, and CSS. Integrate frontend applications with backend services and enterprise platforms. Work with relational and NoSQL databases, including PostgreSQL, Oracle, MongoDB, or similar technologies. Implement authentication, authorization, security, and API integration patterns. Ensure application performance, maintainability, reliability, and scalability. Microservices & Cloud-Native Engineering Design and implement microservices architectures and distributed application platforms. Work with messaging and event-streaming technologies such as Apache Kafka. Build asynchronous processing, event-driven integrations, and resilient distributed services. Apply design patterns for service discovery, fault tolerance, circuit breakers, and distributed transactions. Deploy and operate applications on AWS, Azure, or GCP. Work with Docker, Kubernetes, CI/CD pipelines, and infrastructure automation. Apply observability practices using logging, monitoring, tracing, and performance management tools. Understand cloud-native architecture, scalability, availability, and system reliability. AI & Agentic Engineering Explore and implement AI-powered enterprise applications and intelligent workflows. Integrate LLMs and AI capabilities into existing enterprise applications and platforms. Develop AI agents, tool-calling workflows, and agent orchestration capabilities. Work with retrieval-augmented generation (RAG), vector databases, and enterprise data integrations. Identify opportunities to apply AI and automation to solve client business and technology challenges. Build practical prototypes and take successful AI solutions through production implementation. Client Consulting & Strategic Account Growth Work directly with client CTOs, CIOs, engineering leaders, architects, and business stakeholders. Understand client technology environments, business priorities, and strategic challenges. Translate business problems into technical solutions and actionable engineering roadmaps. Lead technical discovery sessions, architecture discussions, solution demonstrations, and client workshops. Identify opportunities for platform modernization, application development, cloud transformation, and AI adoption. Help expand existing client engagements by identifying new projects, engineering opportunities, and areas where Intellibus can add value. Build trusted relationships with client stakeholders and contribute to long-term account growth. Prepare technical proposals, solution presentations, architecture diagrams, and executive-level materials. Collaborate with leadership and account teams to shape new opportunities and support business development. Required Technical Expertise Java & Backend Engineering Extensive hands-on experience with Java and Spring Boot. Strong understanding of OOP, multithreading, concurrency, collections, JVM fundamentals, and performance optimization. Experience with REST APIs, Hibernate, JPA, and enterprise application development. Strong knowledge of backend architecture and enterprise integration patterns. Full-Stack Development Experience building frontend applications using React, JavaScript, and TypeScript. Ability to independently work across backend and frontend components. Strong understanding of API integration and application architecture. Microservices & Distributed Systems Deep experience designing and implementing microservices architectures. Strong knowledge of Kafka, event-driven systems, messaging, and distributed computing. Understanding of scalability, resiliency, fault tolerance, and high-availability architecture. Cloud & DevOps Experience with AWS, Azure, or GCP. Hands-on experience with Docker, Kubernetes, CI/CD, and cloud-native deployments. Familiarity with Terraform or other infrastructure-as-code tools is preferred. AI & Modern Engineering Exposure to LLM integrations, generative AI, AI agents, and agentic workflows. Experience integrating AI capabilities into enterprise software is highly desirable. Required Consulting & Client Engagement Experience Previous experience working for a technology consulting firm, systems integrator, or professional services organization is mandatory. Demonstrated experience delivering technology solutions for external enterprise clients. Ability to manage multiple technical stakeholders and work across different client environments. Strong executive communication and presentation skills. Ability to identify additional technology opportunities and contribute to account expansion. Comfortable operating in fast-paced consulting environments where priorities and client requirements can evolve. Qualifications Bachelor's or Master's degree in Computer Science, Engineering, or a related technical discipline, or equivalent practical experience. Significant professional software engineering experience, ideally 8+ years. Extensive hands-on Java and backend engineering experience. Proven experience building enterprise-grade microservices and distributed systems. Full-stack development experience with modern frontend frameworks. Previous consulting or professional services experience is mandatory. Experience working in financial services, banking, fintech, or other regulated industries is strongly preferred. What Success Looks Like You can independently design, code, and deliver complex enterprise applications. You bring deep technical expertise in Java, backend engineering, full-stack development, and microservices. You can engage with client engineering teams and senior executives with equal confidence. You identify opportunities to solve broader client challenges beyond the immediate assignment. You help strengthen client relationships and contribute to expanding strategic accounts. You take ownership of solutions from initial discovery through architecture, implementation, and production deployment. Who Should Apply? We are looking for engineers who are not limited to writing code against predefined requirements. . click apply for full job details
Job Description Job Title / Role: Enterprise Architect Key Skills: Enterprise Architecture, TOGAF, Agentic AI Architecture, Cloud Architecture Experience: 15+ Location: San Deigo CA Shift: General Mode: Remote We at Coforge are seeking "Enterprise Architect" with the following skill set: Key Responsibilities The Enterprise Architect is a senior consulting leader and trusted technology advisor who connects client business strategy with executable transformation, shapes commercially viable opportunities, and governs architecture outcomes across complex global ecosystems. Act as the trusted technology and AI advisor for assigned accounts, build C-suite relationships, lead discovery and maturity assessments, and provide independent, outcome-focused recommendations. Partner with account and sales leaders on account plans, opportunity identification, deal shaping, proposals and executive presentations while maintaining advisory integrity and ensuring appropriate AI interventions are included. Lead architecture and AI solutioning for strategic pursuits and transformation programmes, ensuring alignment with business objectives, enterprise principles and measurable value. Mentor Solution Architects, assure architecture and design quality, and provide senior technical leadership to resolve critical client and delivery issues. Architecture Development Define and maintain enterprise architecture principles, standards, reference architectures, reusable building blocks and governance across business, data, application and technology domains. Assess business strategy, operating models and the technology estate; develop capability maps, value streams, baseline and target architectures, transition states and pragmatic roadmaps. Apply a tailored method such as TOGAF ADM or Zachman framework, where appropriate, to organise viewpoints, assure completeness and maintain traceability. Translate target architectures into investment priorities, transformation increments, adoption plans and measurable benefits, KPIs and business outcomes. Develop enterprise and solution architectures for modernisation, cloud, integration, data and AI platforms, balancing reuse, interoperability, security, scalability, resilience, sustainability and cost. Guide build, buy and partner decisions, vendor and platform selection, and multi-vendor ecosystem integration while managing lock-in, sovereignty and regulatory considerations. Design for federated, multi-geography enterprises and global delivery models, recognising local regulations, organisational constraints and cultural differences. AI Expertise Architect enterprise AI, GenAI and Agentic AI solutions, including model and data integration, prompt orchestration, evaluation and AI operations for intelligent & autonomous enterprise. Define AI strategies, operating models, platform roadmaps, reference architectures and reusable patterns that convert business opportunities into executable transformation plans. Embed responsible AI, model governance, security, privacy, observability, resilience and cost controls into solution design and delivery. Guide AI solutions from proof of concept to secure, scalable production deployment with clear evaluation criteria and measurable business outcomes. Mentor architects and engineering teams in AI architecture, design, evaluation and client-facing technical leadership. Advisory Advise executives on technology strategy, operating-model implications and transformation priorities, including high-value AI opportunities. Lead discovery sessions, executive workshops, maturity assessments and option analyses that convert strategic objectives into practical investment roadmaps and value propositions. Present concise decision papers covering business value, investment choices, risks and trade-offs; challenge assumptions constructively and build executive alignment. Track market, industry and technology developments and adapt recommendations as client needs, regulations and ecosystem conditions evolve. Technology Ownership Own architecture outcomes for assigned accounts, domains and programmes, including strategic options, target-state decisions and delivery alignment. Lead Architecture Review Board activities and governance gates; maintain decision records, architecture contracts and traceability, and manage compliance, exceptions and waivers. Ensure target architectures are translated into funded and executable portfolios, with adoption, conformance, benefits and outcome tracking through delivery. Provide portfolio assurance across dependencies, interoperability, cyber risk, data sovereignty, regulatory compliance, resilience, technical debt and lifecycle health. Lead selected innovation initiatives and continuously improve EA effectiveness, maturity, methods and governance. Collaboration Influence without direct authority across client, SI, partner and vendor organisations, aligning business, sales, product, data, security, engineering and delivery leaders. Facilitate cross-domain and cross-cultural workshops, reconcile competing concerns, document trade-offs and secure agreement on principles, target states and priorities. Convert architecture commitments into executable delivery plans across distributed global teams while balancing strategic alignment, feasibility and stakeholder needs. Develop reusable consulting assets, industry viewpoints, reference architectures and accelerators, and contribute to the architecture community and thought leadership. Qualifications Bachelor's or Master's degree in Computer Science, Information Technology or a related discipline. 15+ years of technology experience, including 6-8+ years in enterprise or solution architecture within a global SI, leading consultancy or complex multinational enterprise. Demonstrated success leading executive advisory engagements, transformation programmes, technology account planning and strategic pursuits from discovery through delivery and value realisation. Strong architecture experience across distributed systems, integration, APIs, microservices, cloud, data, security, DevOps, resilience and performance engineering. Hands-on understanding of AI/ML platforms, GenAI and Agentic AI patterns, enterprise data foundations, model integration, RAG, evaluation, AI operations and responsible AI. Proficiency in TOGAF ADM and enterprise modelling; familiarity with LeanIX or similar EA tools, multi-vendor ecosystems and vendor/platform selection is desirable. Strong commercial judgement covering business value, investment options, total cost of ownership, deal economics, risk and architecture trade-offs. Excellent executive communication, storytelling, facilitation, negotiation and stakeholder-management skills, with proven ability to influence globally distributed teams without direct authority. Understanding of cyber security, privacy, regulatory compliance, data governance, sovereignty, operational resilience and sustainability. Preferred: TOGAF or equivalent EA certification; Agile/DevOps experience; and industry knowledge in Financial Services, Insurance, Travel and Transport, or other large-scale enterprise sectors.
11/14/2026
Full time
Job Description Job Title / Role: Enterprise Architect Key Skills: Enterprise Architecture, TOGAF, Agentic AI Architecture, Cloud Architecture Experience: 15+ Location: San Deigo CA Shift: General Mode: Remote We at Coforge are seeking "Enterprise Architect" with the following skill set: Key Responsibilities The Enterprise Architect is a senior consulting leader and trusted technology advisor who connects client business strategy with executable transformation, shapes commercially viable opportunities, and governs architecture outcomes across complex global ecosystems. Act as the trusted technology and AI advisor for assigned accounts, build C-suite relationships, lead discovery and maturity assessments, and provide independent, outcome-focused recommendations. Partner with account and sales leaders on account plans, opportunity identification, deal shaping, proposals and executive presentations while maintaining advisory integrity and ensuring appropriate AI interventions are included. Lead architecture and AI solutioning for strategic pursuits and transformation programmes, ensuring alignment with business objectives, enterprise principles and measurable value. Mentor Solution Architects, assure architecture and design quality, and provide senior technical leadership to resolve critical client and delivery issues. Architecture Development Define and maintain enterprise architecture principles, standards, reference architectures, reusable building blocks and governance across business, data, application and technology domains. Assess business strategy, operating models and the technology estate; develop capability maps, value streams, baseline and target architectures, transition states and pragmatic roadmaps. Apply a tailored method such as TOGAF ADM or Zachman framework, where appropriate, to organise viewpoints, assure completeness and maintain traceability. Translate target architectures into investment priorities, transformation increments, adoption plans and measurable benefits, KPIs and business outcomes. Develop enterprise and solution architectures for modernisation, cloud, integration, data and AI platforms, balancing reuse, interoperability, security, scalability, resilience, sustainability and cost. Guide build, buy and partner decisions, vendor and platform selection, and multi-vendor ecosystem integration while managing lock-in, sovereignty and regulatory considerations. Design for federated, multi-geography enterprises and global delivery models, recognising local regulations, organisational constraints and cultural differences. AI Expertise Architect enterprise AI, GenAI and Agentic AI solutions, including model and data integration, prompt orchestration, evaluation and AI operations for intelligent & autonomous enterprise. Define AI strategies, operating models, platform roadmaps, reference architectures and reusable patterns that convert business opportunities into executable transformation plans. Embed responsible AI, model governance, security, privacy, observability, resilience and cost controls into solution design and delivery. Guide AI solutions from proof of concept to secure, scalable production deployment with clear evaluation criteria and measurable business outcomes. Mentor architects and engineering teams in AI architecture, design, evaluation and client-facing technical leadership. Advisory Advise executives on technology strategy, operating-model implications and transformation priorities, including high-value AI opportunities. Lead discovery sessions, executive workshops, maturity assessments and option analyses that convert strategic objectives into practical investment roadmaps and value propositions. Present concise decision papers covering business value, investment choices, risks and trade-offs; challenge assumptions constructively and build executive alignment. Track market, industry and technology developments and adapt recommendations as client needs, regulations and ecosystem conditions evolve. Technology Ownership Own architecture outcomes for assigned accounts, domains and programmes, including strategic options, target-state decisions and delivery alignment. Lead Architecture Review Board activities and governance gates; maintain decision records, architecture contracts and traceability, and manage compliance, exceptions and waivers. Ensure target architectures are translated into funded and executable portfolios, with adoption, conformance, benefits and outcome tracking through delivery. Provide portfolio assurance across dependencies, interoperability, cyber risk, data sovereignty, regulatory compliance, resilience, technical debt and lifecycle health. Lead selected innovation initiatives and continuously improve EA effectiveness, maturity, methods and governance. Collaboration Influence without direct authority across client, SI, partner and vendor organisations, aligning business, sales, product, data, security, engineering and delivery leaders. Facilitate cross-domain and cross-cultural workshops, reconcile competing concerns, document trade-offs and secure agreement on principles, target states and priorities. Convert architecture commitments into executable delivery plans across distributed global teams while balancing strategic alignment, feasibility and stakeholder needs. Develop reusable consulting assets, industry viewpoints, reference architectures and accelerators, and contribute to the architecture community and thought leadership. Qualifications Bachelor's or Master's degree in Computer Science, Information Technology or a related discipline. 15+ years of technology experience, including 6-8+ years in enterprise or solution architecture within a global SI, leading consultancy or complex multinational enterprise. Demonstrated success leading executive advisory engagements, transformation programmes, technology account planning and strategic pursuits from discovery through delivery and value realisation. Strong architecture experience across distributed systems, integration, APIs, microservices, cloud, data, security, DevOps, resilience and performance engineering. Hands-on understanding of AI/ML platforms, GenAI and Agentic AI patterns, enterprise data foundations, model integration, RAG, evaluation, AI operations and responsible AI. Proficiency in TOGAF ADM and enterprise modelling; familiarity with LeanIX or similar EA tools, multi-vendor ecosystems and vendor/platform selection is desirable. Strong commercial judgement covering business value, investment options, total cost of ownership, deal economics, risk and architecture trade-offs. Excellent executive communication, storytelling, facilitation, negotiation and stakeholder-management skills, with proven ability to influence globally distributed teams without direct authority. Understanding of cyber security, privacy, regulatory compliance, data governance, sovereignty, operational resilience and sustainability. Preferred: TOGAF or equivalent EA certification; Agile/DevOps experience; and industry knowledge in Financial Services, Insurance, Travel and Transport, or other large-scale enterprise sectors.
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 .
Job Description About Quantiphi: Quantiphi is an award-winning, AI-First digital engineering and consulting company focused on delivering high-impact Services and Solutions that help organizations solve what truly matters. We partner with enterprises to reimagine their businesses through intelligent, scalable, and transformative AI driving measurable outcomes at the very core of their operations. Since our founding in 2013, Quantiphi has tackled some of the world's most complex business challenges by combining deep industry expertise, disciplined cloud and data engineering practices, and cutting-edge applied AI research. Our work is rooted in delivering accelerated, quantifiable business value, not just technology for technology's sake. Headquartered in Boston, Quantiphi is a global organization with 4,000+ professionals serving clients across key industry verticals, including BFSI, Healthcare & Life Sciences, CPG, MFG, TME etc. As an Elite and Premier partner to leading cloud and AI platforms such as NVIDIA, Google Cloud, AWS, and Snowflake, we build and deliver enterprise-grade AI services and solutions that create real-world impact. We've been recognized with: 21x Google Cloud Partner of the Year awards in the last 8 years. 3x AWS AI/ML award wins. 3x NVIDIA Partner of the Year titles. 2x Snowflake Partner of the Year awards. We have also garnered top analyst recognitions from Gartner, ISG, and Everest Group. We offer first-in-class industry solutions across Healthcare, Financial Services, Consumer Goods, Manufacturing, and more, powered by cutting-edge Generative AI and Agentic AI accelerators. We have been certified as a Great Place to Work for the third year in a row- 2021, 2022, 2023. Be part of a trailblazing team that's shaping the future of AI, ML, and cloud innovation. Your next big opportunity starts here! For more details, visit: Website or LinkedIn Page. Preferred Location: Charlotte, NC Experience Level: 10+ Years of Experience Role purpose: Design, develop and harden a Universal Gateway that connects conversational AI agents to enterprise applications. The Gateway will manage conversation state, enforce business rules, execute authorized backend operations and return the data and guidance needed by the conversational agent. Key responsibilities: Design and implement Gateway APIs used by Google CXAS agents, including session initialization, journey resolution, state transitions and business-operation execution. Implement an external state engine covering current journey, active state, required information, pending actions, customer confirmation and completion status. Define versioned journey configurations, transition rules, policies and state-specific response guidance. Ensure the Gateway validates actions proposed by an agent against current state, identity, authorization and business rules. Develop adapters for customer backend systems using approved API contracts. Implement timeouts, retries, idempotency, concurrency controls and recovery from partial failures. Persist session state and audit records with appropriate isolation, retention and protection of customer data. Implement authentication, authorization, secrets management and service-to-service security. Provide correlated traces showing the incoming request, policy decision, state before and after, backend operation and response. Integrate automated tests and AgentCert evidence into the development workflow. Package and deploy services to the agreed Google Cloud environment, including Cloud Run where selected. Produce API documentation, architecture decisions, operational runbooks and handover material. Required skills: Strong production backend development experience in Python, Java preferably FastAPI or an equivalent framework. REST APIs, OpenAPI specifications, JSON Schema and typed request/response validation. Practical experience implementing workflow engines, finite-state machines or business-process orchestration. Distributed systems concepts: Concurrency, retries, timeouts and transaction boundaries. Experience with persistent data stores and session management. Google Cloud delivery experience, including IAM, containerized services, logging, monitoring and secrets management. Enterprise API integration and automated unit, integration and contract testing. Understanding of LLM tool calling and the distinction between model-generated intent and authorized business execution. Git, code reviews and CI/CD. Preferred skills: Telecom billing & background, customer service or service-restoration processes. Integration with Google CXAS or another conversational AI platform. Agent evaluation, failure injection, load testing and observability. Experience replacing synthetic adapters with enterprise backend integrations. What is in it for you: Be part of the fastest-growing AI-first digital transformation and engineering company in the world Be a leader of an energetic team of highly dynamic and talented individuals Exposure to working with fortune 500 companies and innovative market disruptors Exposure to the latest technologies related to artificial intelligence and machine learning, data and cloud
11/14/2026
Full time
Job Description About Quantiphi: Quantiphi is an award-winning, AI-First digital engineering and consulting company focused on delivering high-impact Services and Solutions that help organizations solve what truly matters. We partner with enterprises to reimagine their businesses through intelligent, scalable, and transformative AI driving measurable outcomes at the very core of their operations. Since our founding in 2013, Quantiphi has tackled some of the world's most complex business challenges by combining deep industry expertise, disciplined cloud and data engineering practices, and cutting-edge applied AI research. Our work is rooted in delivering accelerated, quantifiable business value, not just technology for technology's sake. Headquartered in Boston, Quantiphi is a global organization with 4,000+ professionals serving clients across key industry verticals, including BFSI, Healthcare & Life Sciences, CPG, MFG, TME etc. As an Elite and Premier partner to leading cloud and AI platforms such as NVIDIA, Google Cloud, AWS, and Snowflake, we build and deliver enterprise-grade AI services and solutions that create real-world impact. We've been recognized with: 21x Google Cloud Partner of the Year awards in the last 8 years. 3x AWS AI/ML award wins. 3x NVIDIA Partner of the Year titles. 2x Snowflake Partner of the Year awards. We have also garnered top analyst recognitions from Gartner, ISG, and Everest Group. We offer first-in-class industry solutions across Healthcare, Financial Services, Consumer Goods, Manufacturing, and more, powered by cutting-edge Generative AI and Agentic AI accelerators. We have been certified as a Great Place to Work for the third year in a row- 2021, 2022, 2023. Be part of a trailblazing team that's shaping the future of AI, ML, and cloud innovation. Your next big opportunity starts here! For more details, visit: Website or LinkedIn Page. Preferred Location: Charlotte, NC Experience Level: 10+ Years of Experience Role purpose: Design, develop and harden a Universal Gateway that connects conversational AI agents to enterprise applications. The Gateway will manage conversation state, enforce business rules, execute authorized backend operations and return the data and guidance needed by the conversational agent. Key responsibilities: Design and implement Gateway APIs used by Google CXAS agents, including session initialization, journey resolution, state transitions and business-operation execution. Implement an external state engine covering current journey, active state, required information, pending actions, customer confirmation and completion status. Define versioned journey configurations, transition rules, policies and state-specific response guidance. Ensure the Gateway validates actions proposed by an agent against current state, identity, authorization and business rules. Develop adapters for customer backend systems using approved API contracts. Implement timeouts, retries, idempotency, concurrency controls and recovery from partial failures. Persist session state and audit records with appropriate isolation, retention and protection of customer data. Implement authentication, authorization, secrets management and service-to-service security. Provide correlated traces showing the incoming request, policy decision, state before and after, backend operation and response. Integrate automated tests and AgentCert evidence into the development workflow. Package and deploy services to the agreed Google Cloud environment, including Cloud Run where selected. Produce API documentation, architecture decisions, operational runbooks and handover material. Required skills: Strong production backend development experience in Python, Java preferably FastAPI or an equivalent framework. REST APIs, OpenAPI specifications, JSON Schema and typed request/response validation. Practical experience implementing workflow engines, finite-state machines or business-process orchestration. Distributed systems concepts: Concurrency, retries, timeouts and transaction boundaries. Experience with persistent data stores and session management. Google Cloud delivery experience, including IAM, containerized services, logging, monitoring and secrets management. Enterprise API integration and automated unit, integration and contract testing. Understanding of LLM tool calling and the distinction between model-generated intent and authorized business execution. Git, code reviews and CI/CD. Preferred skills: Telecom billing & background, customer service or service-restoration processes. Integration with Google CXAS or another conversational AI platform. Agent evaluation, failure injection, load testing and observability. Experience replacing synthetic adapters with enterprise backend integrations. What is in it for you: Be part of the fastest-growing AI-first digital transformation and engineering company in the world Be a leader of an energetic team of highly dynamic and talented individuals Exposure to working with fortune 500 companies and innovative market disruptors Exposure to the latest technologies related to artificial intelligence and machine learning, data and cloud
Job Description Software Engineer $180- $250,000 Python & Event Driven Architectures New York Albert Bow have partnered with an AI platform, that are transforming how investment professionals work! Their clients span private equity, investment banking, private credit, and alternative asset management. They've built an "intelligent deal workspace" that helps dealmakers accelerate sourcing, due diligence, portfolio monitoring, and investor relations through agentic AI. The Role As a Backend Software Engineer, you'll be responsible for building the server-side architecture that powers their platform. You'll work directly with their Client Success, Product, and Engineering teams to develop robust, scalable solutions that handle the demanding workflows of institutional investors. Key Responsibilities Server-side architecture: Design and implement backend logic for data processing, integration workflows, and agentic AI orchestration Database design & optimization: Create and maintain efficient database schemas (MongoDB, Redis) with a focus on data integrity and security API development: Build and maintain RESTful APIs that enable seamless communication between frontend, backend, and third-party integrations (Datasite, Grata, etc.) What You Bring Advanced Python proficiency with production-grade code quality RESTful API development experience designing, building, and maintaining APIs MongoDB and Redis expertise - comfortable working with both document and in-memory data stores Distributed systems & multi-threading knowledge - strong experience with event driven architectures, Rabbit MQ, Kafka, Pub Sub. Interest in LLMs and generative AI - familiarity with how language models are integrated into applications Problem-solving ability and collaborative mindset in a fast-paced environment Location: New York, NY (Hybrid - 3 days/week in office) Up to $250,000 + bonus structure
11/14/2026
Full time
Job Description Software Engineer $180- $250,000 Python & Event Driven Architectures New York Albert Bow have partnered with an AI platform, that are transforming how investment professionals work! Their clients span private equity, investment banking, private credit, and alternative asset management. They've built an "intelligent deal workspace" that helps dealmakers accelerate sourcing, due diligence, portfolio monitoring, and investor relations through agentic AI. The Role As a Backend Software Engineer, you'll be responsible for building the server-side architecture that powers their platform. You'll work directly with their Client Success, Product, and Engineering teams to develop robust, scalable solutions that handle the demanding workflows of institutional investors. Key Responsibilities Server-side architecture: Design and implement backend logic for data processing, integration workflows, and agentic AI orchestration Database design & optimization: Create and maintain efficient database schemas (MongoDB, Redis) with a focus on data integrity and security API development: Build and maintain RESTful APIs that enable seamless communication between frontend, backend, and third-party integrations (Datasite, Grata, etc.) What You Bring Advanced Python proficiency with production-grade code quality RESTful API development experience designing, building, and maintaining APIs MongoDB and Redis expertise - comfortable working with both document and in-memory data stores Distributed systems & multi-threading knowledge - strong experience with event driven architectures, Rabbit MQ, Kafka, Pub Sub. Interest in LLMs and generative AI - familiarity with how language models are integrated into applications Problem-solving ability and collaborative mindset in a fast-paced environment Location: New York, NY (Hybrid - 3 days/week in office) Up to $250,000 + bonus structure
McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. Role Overview The Lead Business Strategic Insights role partners closely with leaders across Commercial Strategy & Innovation (CSI) to develop data-driven solutions that accelerate business growth, enhance customer outcomes, and bring innovative products to market. This individual will leverage advanced analytics, artificial intelligence, machine learning, and business insights to solve complex challenges, uncover opportunities, and drive strategic decision-making across the organization. This role will participate throughout the full solution lifecycle, from ideation and proof of concept through production deployment and business adoption. Success in this position requires a combination of analytical expertise, business acumen, technical proficiency, and stakeholder influence. Key Responsibilities Accelerate AI-enabled decision-making by partnering with data governance, product, and technology teams to leverage governed data assets, semantic layers, and AI/LLM technologies that enable business users to access trusted insights more efficiently. Design and develop heuristics, optimization models, and advanced analytics solutions across customer, product, and operational domains to improve business outcomes. Utilize qualitative and quantitative data to identify opportunities, develop hypotheses, pilot proof-of-concept solutions, and scale successful models across the enterprise. Apply data science and analytical methodologies to identify market trends, process improvement opportunities, strategic synergies, and actionable business recommendations. Support digital data acquisition and integration strategies while building scalable data pipelines that complement existing enterprise data assets. Leverage CSI's data infrastructure to develop next-generation analytical models focused on customer value creation, margin expansion, and operational efficiencies. Drive experimentation and causal learning through pilots, A/B testing, and other measurement methodologies to quantify business impact and improve decision-making. Break down complex business challenges into scalable workstreams and collaborate across functional teams to drive solution adoption and implementation. Develop and deploy scalable Python-based APIs and data products that integrate with enterprise applications and business systems. Build and scale AI agents that enable business users to interact with data using natural language, uncover insights, identify opportunities, and make faster, more informed decisions. Present findings, recommendations, and business cases to senior leaders and cross-functional stakeholders. Minimum Requirements Bachelor's degree in Business, Data Science, Computer Science, Statistics, Engineering, Mathematics, or a related field, or equivalent experience. Typically requires 7+ years of relevant professional experience in analytics, data science, business intelligence, strategy, or a related discipline. Critical Skills 5+ years of experience in analytics, data science, business intelligence, or a related field. Proven experience leveraging analytics to drive measurable business value and strategic outcomes. Strong understanding of software engineering principles and API development used to commercialize analytical products and solutions. Advanced communication, presentation, and stakeholder management skills. Hands-on experience with Python, including libraries such as Pandas, Scikit-learn, NumPy, and related tools. Advanced SQL skills with experience querying and manipulating large, complex datasets. Strong understanding of machine learning techniques, including clustering, regression, anomaly detection, forecasting, classification, deep learning, and time series analysis. Experience working with cloud-based data platforms and modern analytics ecosystems. Experience building, deploying, or leveraging AI and generative AI solutions within business environments. Preferred Qualifications Experience working in healthcare, distribution, pharmaceutical, or supply chain environments. Experience with experimental design, causal inference, and business impact measurement. Familiarity with modern AI frameworks, large language models (LLMs), and agentic AI solutions. Experience building scalable data products and deploying machine learning models into production environments. Demonstrated success influencing business decisions through analytics and strategic insights. Additional Skills Passion for using data to solve complex business problems. Strong business acumen and strategic thinking capabilities. Ability to balance technical depth with business priorities. Self-starter with a continuous improvement mindset. Strong collaboration and relationship-building skills across functions and leadership levels. This role is a hybrid position. The selected candidate is expected to work on-site at our Las Colinas office a minimum of two (2) days per week, with the remaining days worked remotely. Specific in-office days may be designated based on team needs and business priorities. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $136,300 - $227,100 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson's (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: . McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson's full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) or (Canada) . Resumes or CVs submitted to this email box will not be accepted. Join us at McKesson!
11/14/2026
Full time
McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. Role Overview The Lead Business Strategic Insights role partners closely with leaders across Commercial Strategy & Innovation (CSI) to develop data-driven solutions that accelerate business growth, enhance customer outcomes, and bring innovative products to market. This individual will leverage advanced analytics, artificial intelligence, machine learning, and business insights to solve complex challenges, uncover opportunities, and drive strategic decision-making across the organization. This role will participate throughout the full solution lifecycle, from ideation and proof of concept through production deployment and business adoption. Success in this position requires a combination of analytical expertise, business acumen, technical proficiency, and stakeholder influence. Key Responsibilities Accelerate AI-enabled decision-making by partnering with data governance, product, and technology teams to leverage governed data assets, semantic layers, and AI/LLM technologies that enable business users to access trusted insights more efficiently. Design and develop heuristics, optimization models, and advanced analytics solutions across customer, product, and operational domains to improve business outcomes. Utilize qualitative and quantitative data to identify opportunities, develop hypotheses, pilot proof-of-concept solutions, and scale successful models across the enterprise. Apply data science and analytical methodologies to identify market trends, process improvement opportunities, strategic synergies, and actionable business recommendations. Support digital data acquisition and integration strategies while building scalable data pipelines that complement existing enterprise data assets. Leverage CSI's data infrastructure to develop next-generation analytical models focused on customer value creation, margin expansion, and operational efficiencies. Drive experimentation and causal learning through pilots, A/B testing, and other measurement methodologies to quantify business impact and improve decision-making. Break down complex business challenges into scalable workstreams and collaborate across functional teams to drive solution adoption and implementation. Develop and deploy scalable Python-based APIs and data products that integrate with enterprise applications and business systems. Build and scale AI agents that enable business users to interact with data using natural language, uncover insights, identify opportunities, and make faster, more informed decisions. Present findings, recommendations, and business cases to senior leaders and cross-functional stakeholders. Minimum Requirements Bachelor's degree in Business, Data Science, Computer Science, Statistics, Engineering, Mathematics, or a related field, or equivalent experience. Typically requires 7+ years of relevant professional experience in analytics, data science, business intelligence, strategy, or a related discipline. Critical Skills 5+ years of experience in analytics, data science, business intelligence, or a related field. Proven experience leveraging analytics to drive measurable business value and strategic outcomes. Strong understanding of software engineering principles and API development used to commercialize analytical products and solutions. Advanced communication, presentation, and stakeholder management skills. Hands-on experience with Python, including libraries such as Pandas, Scikit-learn, NumPy, and related tools. Advanced SQL skills with experience querying and manipulating large, complex datasets. Strong understanding of machine learning techniques, including clustering, regression, anomaly detection, forecasting, classification, deep learning, and time series analysis. Experience working with cloud-based data platforms and modern analytics ecosystems. Experience building, deploying, or leveraging AI and generative AI solutions within business environments. Preferred Qualifications Experience working in healthcare, distribution, pharmaceutical, or supply chain environments. Experience with experimental design, causal inference, and business impact measurement. Familiarity with modern AI frameworks, large language models (LLMs), and agentic AI solutions. Experience building scalable data products and deploying machine learning models into production environments. Demonstrated success influencing business decisions through analytics and strategic insights. Additional Skills Passion for using data to solve complex business problems. Strong business acumen and strategic thinking capabilities. Ability to balance technical depth with business priorities. Self-starter with a continuous improvement mindset. Strong collaboration and relationship-building skills across functions and leadership levels. This role is a hybrid position. The selected candidate is expected to work on-site at our Las Colinas office a minimum of two (2) days per week, with the remaining days worked remotely. Specific in-office days may be designated based on team needs and business priorities. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $136,300 - $227,100 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson's (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: . McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson's full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) or (Canada) . Resumes or CVs submitted to this email box will not be accepted. Join us at McKesson!
