138 jobs found

Job Description Role: Senior Python Engineer - Agentic AI Job Location: NYC, NY Duration: 6-12+ months Visa Type:- No OPT/CPT/H1B Required Skills Must Have 12-15+ years of software engineering experience Strong hands-on Python development Strong hands-on Agentic AI / Generative AI experience Experience developing LLM-based applications and AI agents Experience with agent orchestration and tool/function calling Strong API integration experience Strong Git/GitHub experience Experience building enterprise-scale production applications Strong debugging and problem-solving skills Agentic AI / GenAI LLMs AI Agents Agentic workflows Multi-agent systems RAG Prompt engineering Tool/function calling Agent orchestration Structured outputs Context/memory management LLM evaluation and observability AI guardrails Python Python 3.x FastAPI / Flask Pydantic AsyncIO REST APIs Microservices Automated testing Git CI/CD Preferred Security Experience Application Security Vulnerability Management SAST / SCA / Container Security Snyk JFrog Xray CodeQL Dependabot Trivy Semgrep GitHub Advanced Security Preferred Cloud & Engineering Experience AWS / Azure / GCP Docker Kubernetes GitHub Actions Jenkins Airflow or similar orchestration tools SQL / NoSQL Bash/Shell Thanks & Regards, Alok Kumar TALENDICA 44, Saratoga Lane, Monroe Township, NJ 08831

Job Description Role : AI Tech Lead / AI Architect (Full Time/FTE) Location :Newark, NJ Experience : 8 to 14 years Work Model: Hybrid (3 days in a week from office) Primary Skill: Generative AI delivery pods, Azure OpenAI / AI Foundry,Production experience with Azur AI, deployed and AI Agent in production , LLM application patterns ,Python (FastAPI, AsyncIO), Docker Secondary Skill: open source models About the Role We are seeking a hands-on AI Tech Lead to lead one or more Generative AI delivery pods for a financial-services client. The role sits between our Senior AI Engineers and the Engagement Manager. You own the technical direction and day-to-day delivery of your pod: you design the architecture, review the work and unblock it, and you are the technical voice with client architects, platform and security teams. You turn business asks into designs, plans and estimates, and you are accountable for what goes to production. Key Responsibilities Core Technical Competencies Generative AI & LLMs: Hands-on depth in LLM application patterns (RAG, hybrid search and re-ranking, agents and tools/MCP, structured outputs) and evaluation/observability tooling (RAGAS, LangSmith, Langfuse or similar). Azure AI Platform: Production experience with Azure OpenAI / AI Foundry, AI Search, Cosmos DB, Functions / App Service, Key Vault, private networking and Entra ID / managed identity. AWS experience is acceptable with a clear path to Azure. Responsible AI & Security: Content filters and guardrails, prompt-injection and data-leakage risks, PII handling, access control and audit logging in a regulated (financial services) environment. Backend & DevOps: Strong Python (FastAPI, AsyncIO), Docker, Terraform, CI/CD and environment promotion (dev / UAT / prod) with rollback. Communication: Clear written and spoken communication with technical and non-technical stakeholders. Technical Leadership & Architecture Solution Architecture: Own the architecture for GenAI applications (RAG, agentic workflows, document intelligence, evaluation and guardrails) on Azure: Azure OpenAI / AI Foundry, AI Search, Cosmos DB, Functions / App Service, APIM or an AI gateway. Engineering Standards: Set and enforce branching and PR reviews, testing, IaC (Terraform), CI/CD (GitHub Actions), observability, security and cost practices. Trade-off Decisions: Make and document the calls on model choice and routing, retrieval design, latency and cost, and build versus buy, so the team and the client can follow them. Evaluation & Guardrails: Build evaluation in from the start: golden datasets, regression gates on every prompt or code change, LLM-as-judge where it fits, content filters and human review for high-risk outputs. Production Readiness: Run release readiness: UAT support, release notes, rollback plans and production hand-off. People, Delivery & Client Leadership Delivery Ownership: Estimate, plan and track delivery; surface risks and dependencies early (environments, access, client approvals) and drive them to closure. Client Technical Lead: Act as the senior technical point of contact with client architects, platform, security and governance teams; lead design walkthroughs, demos and technical decisions. Scoping & Communication: Translate vague business asks into scoped solutions and phased plans, push back with options when a request is not feasible, and work with the Engagement Manager on scope, staffing and status. Required Experience and Qualifications Overall Professional Experience: 8-12 years in software or data/ML engineering, with progressive technical leadership. AI/ML & GenAI Experience: 3+ years building and shipping Generative AI applications to production. Team Leadership: At least 2 years leading engineers: allocation, reviews, mentoring and delivery accountability. Preferred Experience & Education Financial services or asset-management domain experience. AI gateway / API management (APIM, Kong), model routing and cost control; document intelligence and OCR (Azure Document Intelligence / Content Understanding). Working knowledge of React for chat and operations UIs.

Job Description Job Title: Engineer Sr Location: Seattle, WA 98101 Duration: 6 Months Job Type: Temporary Assignment Work Type: Onsite Shift Timings: 08:00 AM To 05:00 PM Pay Rate: $60.00-$60.00/HR Overview: TekWissen is a global workforce management provider headquartered in Ann Arbor, Michigan that offers strategic talent solutions to our clients world-wide. The below job opportunity is to one of Our clients Who is a fashion specialty retailer founded on a simple idea: offer each customer the best possible service, quality, value, and selection. We are looking for an individual to provide specialized Information Technology support for our strategic business partners within the client Corporate Center. Job Description: About the Role: Client relies on Microsoft Entra ID and SailPoint Identity Security Cloud (ISC) to manage access for employees, partners, and contractors across a hybrid, multi-cloud environment. We're hiring an Identity Operations Engineer to keep that machinery running - resolving joiner, mover, and leaver (JML) requests, access requests, and provisioning issues across our identity platforms - and to build the automation that eliminates repeat work. This is a hands-on operations role, not an architecture role. Most of your time is spent working the identity ticket queue, troubleshooting provisioning and sync failures, and executing lifecycle changes accurately and on time. The rest is spent finding the tickets and manual steps that shouldn't exist and automating them away with PowerShell, Microsoft Graph, SailPoint ISC APIs, and workflow tooling. You'll work closely with Identity Architecture, HR, IT Service Management, application owners, and Security Operations, and you'll be the person the business relies on when access doesn't work the way it should. It's a strong fit for an engineer who enjoys solving real access problems for real people and has a bias toward scripting the fix instead of repeating it. A Day in the Life: Identity Lifecycle Operations (Joiner / Mover / Leaver): Fulfill and resolve joiner, mover, and leaver requests from the ITSM queue within SLA - account creation, baseline and role-based access assignment, access changes for transfers and promotions, and timely, complete deprovisioning for terminations, contractors, and leaves of absence. Operate SailPoint ISC day to day - process access requests, investigate and remediate provisioning failures, monitor aggregations and identity refreshes, correct identity attribute and source-data issues, and manage role and access profile assignments. Administer Microsoft Entra ID - users, groups (including dynamic membership), license assignment, enterprise application role assignments, guest accounts, and Lifecycle Workflows and Entitlement Management access package requests. Troubleshoot HR-to-identity provisioning and hybrid sync issues - attribute mismatches, duplicate or conflicting accounts, and Entra Connect / Cloud Sync errors between Entra ID and on-premises Active Directory. Handle privileged and elevated access requests - Privileged Identity Management (PIM) eligible assignments, role-assignable and privileged groups - with the required approvals, justification, and audit trail. Support application access - SSO (SAML/OIDC) assignments, SCIM provisioning errors, and onboarding of applications and connectors to established patterns defined by Identity Architecture. Run access certification and access review campaigns operationally - launch, monitor, send reminders, and execute revocations - and produce audit evidence for internal and external audits (e.g., SOX, PCI). Perform ongoing account hygiene - orphaned, dormant, and stale accounts, guest cleanup, service account inventory, and reconciliation between Entra, SailPoint, and Active Directory. Automation & Continuous Improvement: Build and maintain automation for lifecycle and access tasks using PowerShell, Microsoft Graph API / Graph PowerShell SDK, Python, and SailPoint ISC APIs, workflows, and rules. Create event-driven and scheduled workflows using tools such as Azure Automation, Logic Apps, Power Automate, or Azure Functions - including ITSM ticket integration for auto-fulfillment, status updates, and closure. Analyze ticket volume, SLA performance, and recurring failure patterns to identify the highest-value automation opportunities, and track results (tickets eliminated, time saved, error reduction). Treat automation as production code - source control, peer review, testing, logging, and error handling - so that scripts and workflows are repeatable, supportable, and safe to run against live identities. Use AI tooling to speed up scripting, log and error analysis, troubleshooting, and documentation. Across the role: Write and maintain runbooks, SOPs, and knowledge base articles so that common identity issues can be resolved consistently by the broader support organization. Serve as an escalation point for the service desk and application teams, and partner with Identity Architecture to feed operational findings back into design and standards. Partner with HR/HRIS, IT Service Management, and Security Operations to improve source-data quality, lifecycle timing, and the identity signals available for threat detection. Participate in incident response and escalation coverage for identity-related issues, including after-hours support as needed. You Own This If You Have: Bachelor's or master's degree in Computer Science, Cybersecurity, Information Technology, or equivalent education and experience. 3+ years in identity and access management, IAM operations, or systems/security engineering, including hands-on work with joiner/mover/leaver processes. Hands-on experience with Microsoft Entra ID - user, group, and application administration, plus working knowledge of Conditional Access, PIM, and Entra ID Governance features (Lifecycle Workflows, Entitlement Management, Access Reviews). Hands-on experience operating an enterprise IGA platform - SailPoint ISC / IdentityNow preferred; comparable experience with other IGA tools is considered - including access requests, provisioning, source connectors, and troubleshooting failed provisioning. Proven scripting and automation skills - PowerShell and Microsoft Graph API / Graph PowerShell SDK required; Python and REST API integration experience strongly valued. Working knowledge of authentication and provisioning protocols - SAML, OAuth 2.0, OIDC, SCIM - sufficient to troubleshoot SSO and provisioning issues. Experience with hybrid identity - on-premises Active Directory, Entra Connect / Cloud Sync - and troubleshooting synchronization and attribute issues. Experience working in an ITSM ticketing environment (e.g., ServiceNow), managing queues against SLAs, and documenting work to audit standards. Strong troubleshooting and problem-solving skills, attention to detail, and clear communication with both technical and non-technical partners. Nice to Have: Certifications: Microsoft SC-300 (Identity and Access Administrator), SailPoint ISC certification, AZ-500, Security+, or CISSP. Experience building ITSM-integrated automation (e.g., ServiceNow to SailPoint or Entra fulfillment workflows). Experience with low-code/no-code automation (Power Automate, Logic Apps) and infrastructure-as-code or configuration-as-code (Terraform, Bicep). Familiarity with HRIS-driven provisioning (e.g., Workday) and source-of-truth data quality issues. Familiarity with privileged access management (e.g., BeyondTrust) and how PAM and PIM complement each other. Experience supporting audit and compliance requirements (SOX, PCI) for access controls and evidence collection. Exposure to identity threat detection and response (ITDR) and feeding identity signals into SIEM/SOAR. Large-scale retail, ecommerce, or other high-transaction enterprise experience. TekWissen Group is an equal opportunity employer supporting workforce diversity.

Job Description Top-Tier Investment Management Firm in Midtown, Manhattan is seeking an Associate, AI Engineer for their growing team! We are seeking a hands-on AI Engineer to develop and deploy AI-driven applications for a growing financial services organization. The ideal candidate will have strong Python development skills and experience building production-ready solutions using large language models (LLMs), retrieval-augmented generation (RAG), and modern AI technologies. Responsibilities: Design, build, and deploy AI applications that improve business processes, research, and data analysis. Develop generative AI tools utilizing LLMs, RAG, semantic search, and document processing. Build scalable Python applications and integrate AI solutions with internal systems and databases. Implement and optimize embeddings, vector databases, and data pipelines. Collaborate with business stakeholders to identify opportunities and deliver practical AI solutions. Ensure applications meet performance, security, and reliability standards. Qualifications: 3-5+ years of experience in AI/ML engineering or software development. Strong Python programming skills and experience deploying AI applications into production. Hands-on experience with LLMs, RAG, prompt engineering, and AI APIs (OpenAI, Anthropic, or similar). Experience with SQL, PostgreSQL, and vector databases such as pgvector, Qdrant, or Weaviate. Knowledge of data pipelines, document processing, and structured/unstructured datasets. Strong problem-solving skills and ability to work directly with business stakeholders. Bachelor's degree in Computer Science, Engineering, or a related field. Experience in financial services, fintech, or investment management. Familiarity with Azure, workflow automation, and AI governance.

Job Description This role is primarily focused on data engineering, transformation frameworks, orchestration, and system integrations. While the team builds applications on top of their platform, dedicated application engineering resources lead full-stack UI development. This position will focus on building and maintaining reliable data pipelines, implementing business logic, and supporting scalable data solutions that power those applications. The ideal candidate has strong hands-on experience with modern cloud data platforms (Snowflake and/or Databricks), transformation tooling (dbt), and orchestration frameworks (Airflow or similar). This individual works effectively in a business-aligned environment, partnering with investment and operations teams to deliver secure and scalable data solutions. Primary Responsibilities Credit Data Warehouse Architecture & Development (40%) Build and enhance scalable data models within Snowflake (and/or Databricks where applicable) across landing, integration, and presentation layers, following established architectural patterns. Develop and maintain transformation logic using dbt, ensuring modular, testable, and well-documented models Optimize SQL performance and warehouse resource usage for large-scale financial datasets Implement data quality checks, validation rules, and audit controls Contribute to metadata-driven approaches that support flexible integrations and reporting needs. Support lineage, governance, and maintainability of CDW assets through documentation and adherence to engineering standards. Design data models optimized for reporting and BI consumption, partnering closely with the Credit IQ (Power BI) team to ensure scalable semantic layers and performant analytics Workflow Orchestration & Pipeline Engineering (25%) Build and support data pipelines orchestrated through Airflow Develop and maintain DAGs/workflows for ingestion, transformation, external extracts, and API integrations. Support improvements to pipeline reliability, monitoring, and error handling in production environments. Collaborate with DevOps to ensure CI/CD alignment and production stability Support modernization of legacy orchestration processes into Airflow-based frameworks Integrations & Data Products (20%) Build and support integrations with external vendors, fund administrators, trustees, and internal systems. Build scalable export frameworks (SFTP, API, file-based extracts) driven by configuration and metadata Support data consumption by internal applications and analytics tools Collaborate with application engineering teams to provide well-structured datasets and data interfaces for application use. Applied AI & Intelligent Data Use Cases (10%) Support AI-enabled workflows by preparing structured and unstructured data for retrieval and analysis use cases Assist in enabling retrieval-based workflows leveraging CDW datasets where applicable Ensure AI-related datasets follow security and governance standards Cross-Functional Collaboration & Technical Leadership (5%) Participate in code reviews and provide guidance to junior and offshore contributors Coordinate assigned work with offshore resources to ensure clarity of requirements and timely delivery Work with investment and operations teams to translate business workflows into scalable data solutions Promote clear documentation and adherence to engineering best practices Requirements Education & Certificates Bachelor's degree, required Concentration in computer science, engineering, or a related quantitative field, preferred Master's degree preferred Professional Experience Minimum of 6 years of overall relevant technical experience, required Experience in data engineering, platform engineering, or backend-focused software engineering roles, required Strong hands-on experience designing and operating solutions in Snowflake and/or Databricks (or comparable modern cloud data warehouse/lakehouse platforms) Experience building and deploying data platforms in Azure and/or AWS cloud environments Strong experience writing and optimizing SQL for analytical and financial datasets Hands-on experience with dbt for transformation management, testing, and modular model development Experience developing and supporting Airflow-based orchestration pipelines (or equivalent), including workflow design and monitoring Experience building and maintaining enterprise-grade data pipelines across ingestion, transformation, and presentation layers Experience integrating enterprise systems via APIs, file-based transfers (SFTP), or event-driven workflows Exposure to financial services, alternative asset management, or credit products strongly preferred Experience collaborating with offshore or distributed engineering teams preferred Experience supporting reporting and BI environments (e.g., Power BI), including building reporting-friendly data models and optimizing warehouse performance for analytics workloads Python experience for pipeline tooling, automation, and integration services Experience with Azure services (e.g., Azure Data Factory, Azure Storage, Azure AD) and/or AWS services (e.g., S3, IAM, Lambda, ECS) Experience building or supporting data services consumed by applications Exposure to applied AI or LLM-enabled workflows in a production setting Familiarity with Power BI or comparable BI/reporting tools and semantic modeling concepts Strong SQL and analytical data modeling skills Snowflake and/or Databricks fundamentals, including performance and cost considerations dbt framework design and transformation best practices Airflow (or equivalent) orchestration and production support experience Azure and/or AWS cloud-native data architecture API integration and service-oriented data patterns Data quality, lineage, governance, and audit controls Competencies & Attributes Strong problem-solving and analytical skills Ability to translate business workflows into scalable data solutions Clear communication with both technical and non-technical stakeholders Understanding of BI/reporting architecture, semantic modeling, and analytics performance

Job Description Title : AI Architect Location : Nutley, NJ or NY Duration : 12+ Months Rate : OPEN Visa Status : Any In-Person Interview : No Relevant Experience (in Yrs.) : 5+ Detailed Job Description: We are seeking an experienced AI Architect to design, architect, and lead the implementation of enterprise-scale Artificial Intelligence (AI), Machine Learning (ML), Generative AI, and Agentic AI solutions. The ideal candidate will have strong expertise in AI architecture, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), multi-agent systems, cloud AI platforms, and enterprise application integration. The AI Architect will collaborate with business stakeholders, data scientists, ML engineers, software developers, security teams, and enterprise architects to translate business requirements into scalable, secure, reliable, and cost-effective AI solutions. Key Responsibilities Define enterprise AI architecture, reference architectures, technical standards, and implementation roadmaps. Design and implement Generative AI solutions using LLMs, prompt engineering, RAG, embeddings, vector databases, and semantic search. Architect AI agents and multi-agent workflows using frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, or equivalent technologies. Evaluate and integrate foundation models from OpenAI, Azure OpenAI, AWS Bedrock, Google Vertex AI, Anthropic, and other AI platforms. Design scalable AI services and integrations using Python, REST APIs, microservices, and event-driven architectures. Build enterprise knowledge retrieval solutions using vector databases and enterprise data sources. Define MLOps and LLMOps practices covering model deployment, CI/CD, automated evaluation, monitoring, versioning, and lifecycle management. Establish AI security and governance standards, including responsible AI, data privacy, access control, model risk management, and regulatory compliance. Optimize AI solutions for performance, latency, scalability, token consumption, and cloud operating costs. Collaborate with business and technical teams to identify AI use cases, conduct proof of concepts, and transition successful solutions into production. Establish evaluation frameworks to measure model accuracy, hallucination rates, relevance, reliability, and business outcomes. Mentor AI/ML engineers and provide technical leadership throughout solution design, development, deployment, and operations. Thanks, and Regards Prasanna Kumar Senior Talent Acquisition Lead Ascii Group LLC Email: Phone: +1 / Ext 112

Job Description Rate: $60-65/hr C2C Position Overview: The Senior AI/ML Data Platform Engineer will lead the architecture, development, and continuous improvement of shared enterprise data products and AI-enabled data services. The role focuses on scalable data platforms, real-time streaming, data quality, governance, API design, and integration of AI/ML capabilities into data workflows. Key Requirements: 10+ years of experience in data engineering, ML engineering, or data platform development, including 2+ years designing or operating production data products or data services. Bachelor's degree in Computer Science, Data Science, Engineering, or a related field; master's degree preferred. Expert-level SQL and strong Python programming skills. Experience with AWS, Azure, or GCP data platforms, including Amazon Redshift, AWS Glue, Azure Synapse, Azure Data Factory, BigQuery, Dataflow, Databricks, or Snowflake. Production experience with Apache Kafka, Amazon Kinesis, Apache Flink, or Spark Structured Streaming. Strong understanding of data modeling and architecture patterns, including data vault, lakehouse, and data mesh. Experience with data quality frameworks, data catalogs, data lineage, API design, data contracts, and event-driven architectures. Experience integrating ML models into data pipelines or developing AI-powered data services. Experience with data access controls, attribute-level masking, audit logging, and governance. Strong architectural leadership, technical documentation, mentoring, and cross-team collaboration skills. Preferred Experience: Data mesh, federated data architecture, and enterprise data product initiatives. LLM applications for text-to-SQL, document extraction, semantic search, and automated enrichment. Government, public sector, or highly regulated environments. Data privacy and security requirements, including PII protection, CJIS, HIPAA, and IRS Publication 1075, where applicable. NIST AI Risk Management Framework and responsible AI practices. Data platform FinOps, cloud cost attribution, storage tiering, and query optimization.

This job is with Braze, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. At Braze, we have found our people. We're a genuinely approachable, exceptionally kind, and intensely passionate crew. We seek to ignite that passion by setting high standards, championing teamwork, and creating work-life harmony as we collectively navigate rapid growth on a global scale while striving for greater equity and opportunity - inside and outside our organization. To flourish here, you must be prepared to set a high bar for yourself and those around you. There is always a way to contribute: Acting with autonomy, having accountability and being open to new perspectives are essential to our continued success. Our deep curiosity to learn and our eagerness to share diverse passions with others gives us balance and injects a one-of-a-kind vibrancy into our culture. If you are driven to solve exhilarating challenges and have a bias toward action in the face of change, you will be empowered to make a real impact here, with a sharp and passionate team at your back. If Braze sounds like a place where you can thrive, we can't wait to meet you. WHAT YOU'LL DO We're looking for a Senior Lead Systems Engineer who's passionate about building the next generation of enterprise technology through automation, software engineering, AI, and intelligent integrations. In this role, you'll architect scalable solutions that connect the systems powering Braze while helping redefine how employees interact with IT through conversational experiences, automation, and self-service. You'll lead complex technical initiatives from concept through delivery, building integrations that span platforms such as Slack, Okta, Workday, Atlassian, GitHub, Google Workspace, and other critical business systems. You'll partner closely with Security, Infrastructure, Product, and IT teams to build reliable, scalable solutions that reduce operational overhead and improve the employee experience. This role goes beyond traditional system engineering. We're looking for someone who enjoys solving business problems through software, APIs, automation, and AI. You'll help shape our long-term strategy around enterprise integrations, intelligent workflows, and agentic experiences that enable employees to get work done faster and more intuitively. You'll be part of a team that values reliability, resiliency, scalability, extensibility, and thoughtful engineering. We operate with a shared sense of ownership, continuously look for opportunities to automate manual work, and embrace emerging technologies that allow us to scale efficiently while delivering exceptional internal experiences. If you enjoy designing enterprise architecture, building integrations, and leveraging AI to modernize how organizations operate, we'd love to meet you. You'll lead initiatives that shape the future of enterprise technology at Braze, including: Enterprise Automation & AI: Design and build intelligent automation that streamlines business processes across enterprise platforms. Leverage AI, agentic workflows, and modern integration patterns to reduce manual effort, improve operational efficiency, and enhance employee productivity Enterprise Integrations: Design and develop scalable integrations across platforms including Slack, Okta, Workday, Atlassian, GitHub, Google Workspace, and other SaaS applications. Build APIs, middleware, and event-driven workflows that create seamless employee experiences Conversational IT & Self-Service: Help evolve how employees interact with IT by building conversational interfaces and self-service experiences that reduce reliance on traditional ticket-based workflows while improving service delivery and employee satisfaction Enterprise Platform Architecture: Design scalable, resilient solutions that improve how enterprise platforms communicate and operate together. Evaluate architecture decisions with long-term maintainability, extensibility, and operational excellence in mind AI Platform Enablement: Evaluate, pilot, and implement emerging AI technologies, large language models, MCP integrations, and agent frameworks that enable intelligent automation across enterprise systems while establishing best practices for responsible adoption Automation & Developer Experience: Build reusable automation frameworks, integration services, and internal tooling that accelerate delivery, reduce operational toil, and improve the maintainability of enterprise platforms Governance & Operational Excellence: Partner with Security, Compliance, and Infrastructure teams to ensure enterprise solutions meet governance requirements while maintaining simplicity, scalability, and operational maturity. Document architecture, implementation decisions, and operational processes following governance and compliance standards Innovation & Emerging Technology: Continuously research emerging technologies, integration capabilities, and AI advancements that can improve scalability, reduce operational complexity, and create new opportunities for automation Strategy & Technical Leadership: Contribute to enterprise platform strategy and long-term technical roadmaps. Provide technical leadership on complex initiatives while mentoring engineers on automation, integration, and software engineering best practices WHO YOU ARE 8+ years of experience designing enterprise-scale integrations and automation across modern SaaS environments Strong software engineering background with experience building APIs, integrations, automation, or platform services Proficient in one or more programming languages such as Python, Go, TypeScript, or JavaScript Experienced working with REST APIs, webhooks, OAuth, SCIM, GraphQL, and modern authentication standards Familiar with enterprise platforms such as Okta, Workday, Slack, Atlassian, GitHub, Google Workspace, or similar SaaS ecosystems Skilled in designing scalable architectures that balance business requirements, security, and operational simplicity Experienced collaborating across engineering, security, infrastructure, and business teams to deliver impactful technical solutions Passionate about leveraging AI, automation, and software engineering to solve operational challenges Curious, collaborative, and motivated by continuous improvement and thoughtful systems design Bonus: Experience implementing AI agents, MCP integrations, LLM-powered workflows, or enterprise AI platforms Experience with Terraform, Infrastructure as Code, or cloud automation tooling Experience with event-driven architectures, message queues, or serverless technologies Experience integrating Workday, Okta, Atlassian Cloud, Slack Platform, GitHub Enterprise, or Google Workspace APIs Familiarity with cloud platforms such as AWS, GCP, or Azure Experience building internal developer platforms or enterprise integration frameworks Experience supporting high-growth SaaS organizations with complex enterprise technology environments For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $116,000 and $182,000/year with an expected On Target Earnings (OTE) between $129,000 and $202,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company. WHAT WE OFFER Braze benefits vary by location, and we encourage you to review our specific benefits offerings for each country at here . More details on benefits plans will be provided if you receive an offer of employment. From offering comprehensive benefits to fostering hybrid ways of working, we've got you covered so you can prioritize work-life harmony. Braze offers benefits such as: Competitive compensation that may include equity Retirement and Employee Stock Purchase Plans Flexible paid time off Comprehensive benefit plans covering medical, dental, vision, life, and disability Family services that include fertility benefits and equal paid parental leave Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend A curated in-office employee experience, designed to foster community, team connections, and innovation Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching Employee Resource Groups that provide supportive communities within Braze Collaborative, transparent, and fun culture recognized as a Great Place to Work ABOUT BRAZE Braze is the leading customer engagement platform that empowers brands to Be Absolutely Engaging Braze helps brands deliver great customer experiences that drive value both for consumers and for their businesses. Built on a foundation of composable intelligence, BrazeAI allows marketers to combine and activate AI agents, models . click apply for full job details

Job Description Job Description Job Title: AI Engineer Location-Type: Conshohocken, PA Start Date: July 2026 Duration: 6 months Compensation Range: $75-80/hr Benefits: Eligible for Health, Dental, Vision, and 401K Visa Sponsorship: Not eligible for visa sponsorship Job Description: The client is seeking an AI Engineer to design, build, and deploy LLM-based solutions, autonomous agents, and AI orchestration workflows that enhance how the organization consumes data and reporting insights. Job Summary •Integrate AI-generated insights, narratives, and analysis into existing Power BI reports and dashboards. •Build domain-specific AI agents that support internal teams, including automating first-pass analysis of service tickets. •Implement agent memory, context management, RAG retrieval strategies, and orchestration patterns to support scalable AI architecture. •Design and deploy reusable AI components, skills, and agent frameworks that can be leveraged across multiple teams. •Contribute to the design and deployment of Model Context Protocol (MCP) servers and integrations to expose enterprise data to AI systems. •Maintain and evolve the existing Power BI report portfolio, including semantic models, DAX measures, and Power Query transformations. •Ensure AI integrations comply with enterprise data governance, privacy, security, and access control standards. Minimum Requirements: •2 years of hands-on production AI engineering experience, including building LLM applications and AI agents. •Proven experience with RAG architectures, agent frameworks, prompt orchestration, and token optimization. •Strong Python and SQL skills with demonstrated ability to design scalable, reusable AI architecture. •Proven Power BI development experience, including semantic modeling, DAX, and Power Query. •Ability to work autonomously, manage a mixed AI/BI backlog, and communicate clearly with non-technical stakeholders. Preferred Qualifications: •Experience with ServiceNow or other enterprise platforms such as Salesforce or Dynamics 365, and system integration patterns. •Experience implementing AI governance, guardrails, and responsible-AI practices including monitoring and evaluation. •Experience reducing LLM costs and token usage at scale. •Familiarity with the Microsoft data platform, including Fabric, Synapse, and Purview. •Experience embedding AI-generated narratives or insights directly into BI reporting tools. •Experience building AI frameworks adopted across multiple business teams.

Job Description Job Description Why Keyrus, Why Now! Keyrus is an international group of 3,000 experts across 30 countries, built on a single conviction: AI does not transform businesses. Architected intelligence does. For more than 30 years, we have helped organizations build the data foundations that power intelligent systems. Today, we go further by designing and operationalizing intelligence that delivers measurable business value. Building AI capabilities is only part of the challenge. Real transformation happens when those capabilities work within existing business systems, data environments, workflows, and processes. At Keyrus, you'll work closely with clients to turn AI opportunities into production-ready solutions, connecting engineering expertise with real business needs. Technology amplifies. Keyrus culture differentiates. Industrial discipline connects the two. Role details • Location: United States (Remote) • Contract: Permanent, full-time What you'll architect As a Forward Deployed AI Engineer, you'll work directly with clients to take AI solutions from technical discovery through implementation, deployment, and adoption. You'll combine hands-on software engineering, enterprise integrations, cloud technologies, and AI capabilities to deliver solutions that work in real client environments. Your focus goes beyond writing code. You'll understand client challenges, define implementation plans, coordinate technical teams, and deliver measurable business results. Your responsibilities • Lead technical discovery with clients to understand their systems, data, workflows, and integration requirements. • Translate business needs and approved architectures into practical implementation plans. • Develop production-ready solutions integrating APIs, enterprise applications, cloud services, data platforms, and AI technologies. • Collaborate with AI Engineers, Architects, and Data Engineers to resolve technical challenges and deliver integrated solutions. • Own technical deployment and rollout within the agreed scope, ensuring reliable production performance. • Work closely with client teams to troubleshoot issues, support adoption, and improve implemented solutions. • Monitor performance, costs, and business outcomes while documenting reusable engineering practices. • Turn successful implementations into reusable Keyrus assets, including integration patterns, deployment practices, technical documentation, and implementation guidance for future engagements. Who you are You are a hands-on engineer with a strong consulting mindset who enjoys solving complex business and technical challenges. You develop production-quality code, understand enterprise integrations, and adapt solutions to real-world constraints. You are comfortable working directly with clients, managing evolving requirements, and taking ownership of technical delivery. You combine strong engineering skills with excellent communication, problem-solving, and collaboration. What you bring Experience • 5+ years of professional experience in software engineering, cloud engineering, enterprise integration, or related technical delivery roles. • Hands-on experience developing, integrating, and deploying production software or AI-enabled solutions. • Experience building and maintaining backend services, APIs, and enterprise integrations. • Experience working with cloud platforms, deployment processes, and production environments. • Ability to translate business requirements into technical implementation plans. • Strong client-facing consulting experience, including communicating technical decisions and working with business stakeholders. Technical skills • Strong programming skills in Python, TypeScript/JavaScript, Java, C#, or similar languages. • Experience with REST APIs, backend services, authentication, and enterprise integrations. • Hands-on experience with AWS, Azure, or Google Cloud. • Knowledge of Git, CI/CD, testing, containers, and production monitoring. • Familiarity with LLM APIs, RAG, AI agents, and GenAI application integration. • Understanding of application security, system reliability, and cloud deployment practices. Nice to have • Experience developing production GenAI applications or agentic workflows. • Familiarity with LangGraph, MCP, OpenAI, Anthropic, or similar technologies. • Experience with Kubernetes, Docker, or infrastructure as code. • Background in backend, full-stack, data, or cloud engineering. • Experience delivering solutions in regulated or complex enterprise environments. • Previous experience in consulting, professional services, or client-embedded engineering roles. What makes you successful • You turn complex challenges into practical solutions. • You take ownership of technical delivery and integration. • You communicate clearly and collaborate effectively with clients and teams. • You deliver reliable solutions that create measurable business value. WHAT WE OFFER (KUS) A stimulating environment where you will be able to surpass yourself and discover new horizons. A strong culture of innovation and entrepreneurship. Health insurance for you and your family members. 401K plan. Monthly Wellness Allowance. 4 weeks of paid vacation; Language courses (French & English) Access to continuing education (in-house, conferences, events, courses, certifications, etc.) The expected base compensation for this position ranges from $135,000 to $155,000 USD, depending on experience, skills, location, and internal equity. This salary range is provided as a guideline and may be adjusted for the selected candidate. About Keyrus At Keyrus, we help organizations move from experimental to industrialized AI, from isolated agents to orchestrated systems, and from insight to execution. As Architects of Intelligence, we design the Operating System of the intelligent enterprise, embedding intelligence into business processes so that it creates sustainable, measurable value. Powered by our proprietary Human Orchestrated Model (HOM), we architect reliable: • Intelligence Foundations • Human in Command governance • Performance Steering With over 30 years of expertise and 3,000 experts across 30 countries, we build adaptive, resilient intelligent environments where technology amplifies human capability and performance compounds over time. AI does not transform businesses. Architected intelligence does. For more information:

This job is with Braze, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. At Braze, we have found our people. We're a genuinely approachable, exceptionally kind, and intensely passionate crew. We seek to ignite that passion by setting high standards, championing teamwork, and creating work-life harmony as we collectively navigate rapid growth on a global scale while striving for greater equity and opportunity - inside and outside our organization. To flourish here, you must be prepared to set a high bar for yourself and those around you. There is always a way to contribute: Acting with autonomy, having accountability and being open to new perspectives are essential to our continued success. Our deep curiosity to learn and our eagerness to share diverse passions with others gives us balance and injects a one-of-a-kind vibrancy into our culture. If you are driven to solve exhilarating challenges and have a bias toward action in the face of change, you will be empowered to make a real impact here, with a sharp and passionate team at your back. If Braze sounds like a place where you can thrive, we can't wait to meet you. WHAT YOU'LL DO We're looking for a Senior Lead Systems Engineer who's passionate about building the next generation of enterprise technology through automation, software engineering, AI, and intelligent integrations. In this role, you'll architect scalable solutions that connect the systems powering Braze while helping redefine how employees interact with IT through conversational experiences, automation, and self-service. You'll lead complex technical initiatives from concept through delivery, building integrations that span platforms such as Slack, Okta, Workday, Atlassian, GitHub, Google Workspace, and other critical business systems. You'll partner closely with Security, Infrastructure, Product, and IT teams to build reliable, scalable solutions that reduce operational overhead and improve the employee experience. This role goes beyond traditional system engineering. We're looking for someone who enjoys solving business problems through software, APIs, automation, and AI. You'll help shape our long-term strategy around enterprise integrations, intelligent workflows, and agentic experiences that enable employees to get work done faster and more intuitively. You'll be part of a team that values reliability, resiliency, scalability, extensibility, and thoughtful engineering. We operate with a shared sense of ownership, continuously look for opportunities to automate manual work, and embrace emerging technologies that allow us to scale efficiently while delivering exceptional internal experiences. If you enjoy designing enterprise architecture, building integrations, and leveraging AI to modernize how organizations operate, we'd love to meet you. You'll lead initiatives that shape the future of enterprise technology at Braze, including: Enterprise Automation & AI: Design and build intelligent automation that streamlines business processes across enterprise platforms. Leverage AI, agentic workflows, and modern integration patterns to reduce manual effort, improve operational efficiency, and enhance employee productivity Enterprise Integrations: Design and develop scalable integrations across platforms including Slack, Okta, Workday, Atlassian, GitHub, Google Workspace, and other SaaS applications. Build APIs, middleware, and event-driven workflows that create seamless employee experiences Conversational IT & Self-Service: Help evolve how employees interact with IT by building conversational interfaces and self-service experiences that reduce reliance on traditional ticket-based workflows while improving service delivery and employee satisfaction Enterprise Platform Architecture: Design scalable, resilient solutions that improve how enterprise platforms communicate and operate together. Evaluate architecture decisions with long-term maintainability, extensibility, and operational excellence in mind AI Platform Enablement: Evaluate, pilot, and implement emerging AI technologies, large language models, MCP integrations, and agent frameworks that enable intelligent automation across enterprise systems while establishing best practices for responsible adoption Automation & Developer Experience: Build reusable automation frameworks, integration services, and internal tooling that accelerate delivery, reduce operational toil, and improve the maintainability of enterprise platforms Governance & Operational Excellence: Partner with Security, Compliance, and Infrastructure teams to ensure enterprise solutions meet governance requirements while maintaining simplicity, scalability, and operational maturity. Document architecture, implementation decisions, and operational processes following governance and compliance standards Innovation & Emerging Technology: Continuously research emerging technologies, integration capabilities, and AI advancements that can improve scalability, reduce operational complexity, and create new opportunities for automation Strategy & Technical Leadership: Contribute to enterprise platform strategy and long-term technical roadmaps. Provide technical leadership on complex initiatives while mentoring engineers on automation, integration, and software engineering best practices WHO YOU ARE 8+ years of experience designing enterprise-scale integrations and automation across modern SaaS environments Strong software engineering background with experience building APIs, integrations, automation, or platform services Proficient in one or more programming languages such as Python, Go, TypeScript, or JavaScript Experienced working with REST APIs, webhooks, OAuth, SCIM, GraphQL, and modern authentication standards Familiar with enterprise platforms such as Okta, Workday, Slack, Atlassian, GitHub, Google Workspace, or similar SaaS ecosystems Skilled in designing scalable architectures that balance business requirements, security, and operational simplicity Experienced collaborating across engineering, security, infrastructure, and business teams to deliver impactful technical solutions Passionate about leveraging AI, automation, and software engineering to solve operational challenges Curious, collaborative, and motivated by continuous improvement and thoughtful systems design Bonus: Experience implementing AI agents, MCP integrations, LLM-powered workflows, or enterprise AI platforms Experience with Terraform, Infrastructure as Code, or cloud automation tooling Experience with event-driven architectures, message queues, or serverless technologies Experience integrating Workday, Okta, Atlassian Cloud, Slack Platform, GitHub Enterprise, or Google Workspace APIs Familiarity with cloud platforms such as AWS, GCP, or Azure Experience building internal developer platforms or enterprise integration frameworks Experience supporting high-growth SaaS organizations with complex enterprise technology environments For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $104,000 and $164,000/year with an expected On Target Earnings (OTE) between $115,000 and $182,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company. WHAT WE OFFER Braze benefits vary by location, and we encourage you to review our specific benefits offerings for each country at here . More details on benefits plans will be provided if you receive an offer of employment. From offering comprehensive benefits to fostering hybrid ways of working, we've got you covered so you can prioritize work-life harmony. Braze offers benefits such as: Competitive compensation that may include equity Retirement and Employee Stock Purchase Plans Flexible paid time off Comprehensive benefit plans covering medical, dental, vision, life, and disability Family services that include fertility benefits and equal paid parental leave Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend A curated in-office employee experience, designed to foster community, team connections, and innovation Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching Employee Resource Groups that provide supportive communities within Braze Collaborative, transparent, and fun culture recognized as a Great Place to Work ABOUT BRAZE Braze is the leading customer engagement platform that empowers brands to Be Absolutely Engaging Braze helps brands deliver great customer experiences that drive value both for consumers and for their businesses. Built on a foundation of composable intelligence, BrazeAI allows marketers to combine and activate AI agents, models . click apply for full job details

This job is with Gilead Sciences Inc., an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. At Gilead, we're creating a healthier world for all people. For more than 35 years, we've tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer - working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world's biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference. Every member of Gilead's team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we're looking for the next wave of passionate and ambitious people ready to make a direct impact. We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together. Job Description Architecture & Platform Strategy Define and evolve the target-state architecture for the self-serve data, AI, and agentic AI platform, aligned to enterprise strategy, data mesh principles, and regulatory requirements Establish enterprise standards and reference architectures for data products, semantic layer services, AI/LLM gateways, agent orchestration, and API- and MCP-based data access Architect the platform layers that let AI systems and agents find, trust, ask, and act on enterprise data - including data product interfaces, semantic context services, and governed write/action patterns Define tiered certification and governance patterns that scale data product trust from registered assets to autonomous-grade, AI-ready products Establish foundational patterns for retrieval, context enrichment, grounding, and tool exposure (RAG, semantic layer, MCP tool surfaces) to support agentic and real-time decisioning use cases Engineering & Infrastructure Lead engineering of scalable, secure platform infrastructure on AWS (S3, Lake Formation, Glue, EKS, Bedrock, IAM, networking) and Databricks (Unity Catalog, Delta Lake, Delta Live Tables, Databricks SQL, MLflow, Mosaic AI) Engineer the agentic AI platform stack: agent runtimes, orchestration, agent identity and access management, action/write contracts, evaluation harnesses, and observability Implement platform engineering best practices: infrastructure-as-code (Terraform), CI/CD, automated testing, environment promotion, and GxP/Part 11-compliant change management Drive operational excellence across reliability, cost management (FinOps for data and AI workloads), observability, and incident response, grounded in SRE and Well-Architected practices Ensure security, data protection, and access governance patterns (fine-grained entitlements, row/column-level controls, audit lineage) meet regulated-industry requirements Delivery Leadership & Product Management Contribute to the platform product roadmap: define outcomes, prioritize the backlog, and sequence capability delivery against enterprise AI adoption goals Lead delivery across a team of vendor partners, holding the team to clear standards for quality, velocity, and operability Drive build/buy/adopt decisions with rigor - vendor evaluation, kill criteria, and total-cost analysis - and integrate acquired capabilities into a coherent platform experience Define and track platform health and adoption metrics (DORA, reliability SLOs, self-serve adoption, time-to-data-product) and report progress to senior leadership Serve as a trusted advisor and technical leader: mentor engineers, run architecture reviews, and partner with business domains to identify and enable high-value data and AI use cases Communicate architecture and trade-offs crisply to audiences from engineers to Director/VP. stakeholders, simplifying complexity without losing rigor Basic Qualifications 10+ years in platform engineering, data engineering, or enterprise data/AI platform architecture, including 3+ years leading engineering teams or major platform programs Deep hands-on expertise with AWS data and AI services, including S3, Lake Formation, Glue, EKS, Bedrock, Kinesis/MSK, IAM, and Terraform-based infrastructure automation Strong production experience with Databricks: Unity Catalog, Delta Lake, Delta Live Tables, Databricks SQL, MLflow, and workspace/governance administration at enterprise scale Demonstrated experience designing or building agentic AI or LLM-powered systems: agent orchestration, RAG pipelines, LLM gateways, tool/function calling, MCP or comparable protocols, and AI evaluation/observability Proven ability to build resilient, scalable pipelines for high-volume batch and streaming data, with proficiency in SQL and Python (or Scala/Java) Strong understanding of distributed systems, event-driven architecture, workflow orchestration, and API-first integration patterns Experience designing secure, governed, production-grade cloud architectures, including fine-grained access control, lineage, and auditability Track record of delivery leadership: roadmap ownership, backlog management, cross-functional coordination, and shipping platform capabilities that achieve measured adoption Excellent communication skills with the ability to simplify complexity and influence senior decision-makers Preferred Qualifications Experience in biopharma, life sciences, or other heavily regulated domains, with working knowledge of GxP, 21 CFR Part 11, and computer system validation Background in data mesh or federated data architectures, data product operating models, and domain enablement at enterprise scale Experience with semantic layer technologies, knowledge graphs, metadata/catalog platforms, and data contract frameworks Familiarity with FinOps for data and AI workloads, including cost attribution, chargeback/showback, and LLM token economics Experience managing large vendor/partner ecosystems and running structured vendor evaluations with defined success and kill criteria Product management experience or certification; familiarity with DORA metrics, SPACE framework, and platform-as-a-product operating models AWS Professional (Solutions Architect or Data Analytics) and/or Databricks certifications The salary range for this position is: $168,980.00 - $218,680.00. Gilead considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location. These considerations mean actual compensation will vary. This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package. Benefits include company-sponsored medical, dental, vision, and life insurance plans . For additional benefits information, visit: Eligible employees may participate in benefit plans, subject to the terms and conditions of the applicable plans. For jobs in the United States: Gilead Sciences Inc. is committed to providing equal employment opportunities to all employees and applicants for employment, and is dedicated to fostering an inclusive work environment comprised of diverse perspectives, backgrounds, and experiences. Employment decisions regarding recruitment and selection will be made without discrimination based on race, color, religion, national origin, sex , age, sexual orientation, physical or mental disability, genetic information or characteristic, gender identity and expression, veteran status, or other non-job related characteristics or other prohibited grounds specified in applicable federal, state and local laws. In order to ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Era Veterans' Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact for assistance. For more information about equal employment opportunity protections, please view the 'Know Your Rights' poster. NOTICE: EMPLOYEE POLYGRAPH PROTECTION ACT YOUR RIGHTS UNDER THE FAMILY AND MEDICAL LEAVE ACT Gilead Sciences will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, (c) consistent with the legal duty to furnish information; or (d) otherwise protected by law. . click apply for full job details

Job Description Job Description Description: Position Summary Precise is excited to launch an entry-level AI Developer position in our Innovation Lab, with select candidates starting as interns with the potential to convert into a full-time role. We will invite exceptional recent graduates or early-career professionals to join us full-time. These candidates may begin with a 3-month paid internship period, with strong performers offered a full-time, permanent position on the team. This is a hands-on opportunity to build real AI solutions alongside visionary tech leads who love to teach and coach. You will move ideas from concept to working prototypes or fully functional applications in days or weeks, not months, using generative AI, agentic AI, machine learning and intelligent automation. Must be USC/GC/EAD Prefer candidates local to Rockville office but will consider remote Key Responsibilities: Design and build Generative AI applications using large language models (LLMs), prompt engineering and retrieval-augmented generation (RAG). Develop agentic AI workflows where AI agents plan, use tools and APIs, and complete multi-step tasks with human oversight. Rapidly prototype new ideas, turning concepts into working demos and proofs of concept within short sprint cycles. Use AI coding assistants to accelerate development, while reviewing, testing and validating all AI-generated code. Apply and enhance machine learning models for real-world use cases, including data preparation, training, evaluation and deployment. Identify repetitive business processes and automate them with Robotic Process Automation (RPA), combined with AI for intelligent automation. Capture, clean, analyze and validate data from multiple sources, using SQL and NoSQL databases. Deploy solutions on cloud platforms such as AWS, Google Cloud or Azure. Research emerging AI tools and industry practices, and share findings through demos and presentations. Projects Our projects will let you learn and grow skills in Generative AI, agentic AI, rapid prototyping, AI-assisted development, machine learning and RPA. Example areas include: AI assistants that answer questions from company knowledge using RAG. Multi-agent systems that automate end-to-end workflows such as research, reporting or customer support. Intelligent document processing that combines ML, LLMs and RPA to extract and act on data. Predictive analytics and ML models that support client and business decisions. Rapid innovation sprints that test new AI tools and turn the best ideas into client-ready prototypes. Requirements: Entry-level AI Developers with a degree (or near-completion) in Computer Science, Data Science, AI or a related field. You are smart, hungry to learn, passionate about possibility and excited to experiment with emerging technology. A great AI developer is a great developer first. You should have solid, demonstrated development skills, along with experience and/or coursework in some or all of the following: Strong Python proficiency (required); JavaScript, TypeScript or Java a plus Hands-on development experience (personal projects, internships, open source or coursework) shipping real, working applications Solid programming fundamentals: OOD, data structures, algorithms, testing and debugging LLM APIs (OpenAI, Anthropic), orchestration (LangChain, LlamaIndex) and agent frameworks (LangGraph, CrewAI, vendor SDKs) ML libraries: scikit-learn, PyTorch (TensorFlow/Keras a plus) SQL/NoSQL and vector databases (pgvector, Pinecone, Weaviate) for RAG Cloud platforms (AWS, Google Cloud, Azure) and their AI services (Bedrock, Vertex AI, Azure AI Foundry); Git, Docker, CI/CD basics REST/GraphQL API development and backend services LLM observability/evaluation tools (LangSmith, Weights & Biases) a plus Strong software engineering fundamentals, clean coding practices, strong communication skills, curiosity and a responsible approach to AI (accuracy, privacy and ethics) are essential. ABOUT US Precise Software Solutions, Inc. is a mission-focused technology services company delivering secure digital platforms, infrastructure, and operational IT services to government organizations. A CMMI Level 3-appraised company, Precise partners with agency technology leaders and solution providers to design, build, operate, and modernize enterprise IT solutions that support critical public missions combining agility, innovation, and performance to deliver measurable results. Precise specializes in cloud and hybrid infrastructure, platform engineering, security operations and compliance, application modernization, and data platforms and analytics. The company is known for its agile, delivery-driven approach and innovative engineering practices, applying operational rigor and performance-focused execution to improve system resilience, security, and scalability across complex government environments. BENEFITS AND PERKS Comprehensive Health Benefits (Medical, Dental and Vision) Flexible Spending Accounts (FSA) & Health Savings Account (HSA) Retirement Plan with 4% match and discretionary match at year end Paid Time Off (PTO): 15 days of PTO accrued per year; 7 holidays+ 3 Floating holidays; 2 Innovation days (paid training days) Short Term and Long-Term Disability Paid Parental Leave Paid Jury Duty leave Life and AD&D Insurance Critical Illness Insurance Training and Development Wellness Incentives & Discount programs Employee Referral Program Annual Charity Donation Match Awards and Recognition Equal Employment Opportunity Statement Precise Software Solutions is committed to providing a workplace free from discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, age, national origin, disability, sexual orientation, gender identity or expression, marital status, genetic information, protected veteran status, or other legally protected status. We are an inclusive organization and actively promote equality of opportunity for all with the right mix of talent, skills and potential. We expect every member of the Precise community to do their part to cultivate and maintain an environment where everyone has the opportunity to feel included and is afforded the respect and dignity they deserve.

Overview Senior DevSecOps & Platform Engineer (CORPIT) Bowhead is seeking a highly skilled Senior DevSecOps & Platform Engineer to support the Naval Surface Warfare Center Dahlgren Division (NSWCDD) Research, Development, Test & Evaluation (RDT&E) environment. The successful candidate will possess a diverse technical background encompassing DevSecOps architecture, platform engineering, full-stack application development, cybersecurity compliance, and emerging Artificial Intelligence/Machine Learning (AI/ML) technologies. This position requires a versatile technical professional capable of designing, developing, deploying, securing, and maintaining enterprise applications and infrastructure across complex computing environments. The individual will play a critical role in integrating modern development practices, automating infrastructure and deployment processes, ensuring compliance with Department of Defense (DoD) cybersecurity requirements, and supporting innovative AI-enabled capabilities. The ideal candidate will demonstrate strong technical proficiency, analytical problem-solving skills, and the ability to collaborate with government stakeholders, software developers, cybersecurity personnel, and infrastructure engineering teams. Responsibilities DevSecOps Architecture and Platform Engineering Design, implement, and maintain secure, scalable DevSecOps platforms supporting enterprise application development and deployment. Develop, manage, and optimize Continuous Integration/Continuous Deployment (CI/CD) pipelines using GitLab. Support containerized application environments utilizing Docker and Kubernetes. Administer and troubleshoot Linux and Windows operating environments. Support virtualized infrastructure utilizing VMware vSphere. Integrate artifact repositories, development tools, and collaborative platforms, including Artifactory, Jira, and Confluence. Identify opportunities to automate infrastructure management, application deployments, and operational workflows. Full-Stack Application Development Develop, maintain, and enhance software applications using Python and JavaScript. Support application integration across multiple platforms, databases, and enterprise systems. Develop and maintain database connectivity and application functionality utilizing Microsoft SQL Server, Oracle SQL, MySQL, and MariaDB. Collaborate with development teams to improve application performance, reliability, scalability, and security. Incorporate automated testing, code validation, and secure software development practices throughout the application lifecycle. Troubleshoot complex application, infrastructure, and integration issues. Cybersecurity and Compliance Integrate cybersecurity requirements and secure development practices throughout the software development lifecycle. Implement and validate Security Technical Implementation Guides (STIGs) across applicable systems and applications. Support vulnerability identification, assessment, tracking, and remediation using Assured Compliance Assessment Solution (ACAS), SCAP, McAfee security tools, and related technologies. Implement static code analysis and vulnerability scanning tools, including Xray, within development pipelines. Collaborate with cybersecurity professionals to address identified vulnerabilities and maintain compliance with applicable DoD security requirements. Support security assessments, audit preparation, remediation activities, and continuous monitoring efforts. Promote security automation and continuous compliance throughout the development and deployment process. Artificial Intelligence and Machine Learning Integration Support the evaluation and integration of AI/ML technologies into enterprise development and operational environments. Develop and implement agentic workflows and AI-enabled automation capabilities. Work with Large Language Models (LLMs) and agentic harnesses to support intelligent workflow orchestration and process improvement. Evaluate opportunities to leverage AI technologies to enhance software development, troubleshooting, cybersecurity operations, and organizational efficiency. Collaborate with technical stakeholders to assess the feasibility, security, and operational value of emerging AI capabilities. Technical Collaboration and Customer Support Serve as a technical subject matter expert across DevSecOps, application development, platform engineering, and cybersecurity disciplines. Collaborate with government customers and multidisciplinary technical teams to identify requirements and develop effective solutions. Provide technical recommendations concerning system architecture, application deployment, security improvements, and infrastructure modernization. Develop and maintain technical documentation, standard operating procedures, and configuration records. Investigate and resolve complex technical challenges while maintaining customer communication and operational continuity. Qualifications Seven to ten (7-10) years of experience. BA/BS degree required. Must have an IAT level III certificaiton. Demonstrated professional experience in DevSecOps engineering, platform engineering, software development, or closely related technical disciplines. Working knowledge of Linux and Windows operating systems. Experience with containerization and orchestration technologies, including Docker and Kubernetes. Experience supporting virtualized infrastructure using VMware vSphere. Hands-on experience developing and maintaining GitLab CI/CD pipelines. Familiarity with Artifactory, Jira, and Confluence. Programming experience using Python and JavaScript. Experience working with relational databases, including one or more of the following: Microsoft SQL Server, Oracle SQL, MySQL, or MariaDB. Understanding of cybersecurity principles, vulnerability management, and secure software development practices. Experience with cybersecurity compliance tools and processes, including STIGs, ACAS, SCAP, static code analysis, or comparable technologies. Strong troubleshooting and root-cause analysis capabilities across applications, infrastructure, and development environments. Ability to communicate technical information effectively to engineering teams, program leadership, and government stakeholders. Ability to work independently and collaboratively within a multidisciplinary technical environment. Preferred Qualifications Experience designing and implementing enterprise DevSecOps architectures. Advanced Kubernetes administration, configuration, and troubleshooting experience. Experience integrating automated security scanning and vulnerability management into CI/CD pipelines. Familiarity with DoD cybersecurity compliance requirements and Risk Management Framework (RMF) processes. Experience supporting DoD RDT&E or similarly complex federal IT environments. Experience developing full-stack applications and integrating enterprise database systems. Knowledge of AI/ML technologies, Large Language Models, agentic harnesses, and agentic workflows. Experience implementing AI-enabled automation within secure enterprise environments. Experience supporting platform modernization, infrastructure automation, and continuous compliance initiatives. Relevant industry certifications in DevSecOps, cloud technologies, Kubernetes, software engineering, or cybersecurity. Desired Professional Attributes Demonstrates adaptability across multiple technical disciplines and rapidly evolving technologies. Possesses strong analytical skills and an innovative approach to problem-solving. Maintains a security-focused mindset throughout development and operational activities. Demonstrates initiative in identifying opportunities for automation and process improvement. Effectively balances software development, infrastructure operations, and cybersecurity requirements. Builds productive relationships with customers and technical stakeholders. Demonstrates attention to detail, accountability, and a commitment to mission success. Targeted salary range is $175,000 to $195,000 annually based on qualifications and experience. Physical Demands: Must be able to lift up to 25 pounds Must be able to stand and walk for prolonged amounts of time Must be able to twist, bend and squat periodically SECURITY CLEARANCE REQUIREMENTS: Must currently hold a security clearance at the Top Secret/SCI level. US Citizenship is a requirement for Top Secret/SCI clearance at this location. Please note that the salary information is a general guideline only. Bowhead considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/training, key skills, internal peer equity, as well as, market and business considerations when extending an offer.

Overview Join a team where innovation meets mission. Our AI, cloud, cyber, and modernization solutions save agencies thousands of hours, safeguard national security, and strengthen health and humanitarian missions worldwide. With 1,700+ team members, 1,500+ AI/data experts, and 100+ prime contracts, we deliver at scale and with purpose. We've been recognized as a Top Workplace by the Washington Post for six straight years and named to the Inc. 5000 Fastest Growing Private Companies 13 of the past 14 years. Credence is a welcoming home for those looking to grow and contribute to positive change. We encourage all employees to expand beyond their boundaries, dive into important world-changing Federal challenges. Position Summary Credence has an immediate need for a Senior AI Software Engineer to join our growing AI and Automation practice. In this role, you will serve as a senior technical contributor responsible for designing, developing, and deploying advanced AI-driven solutions, including generative AI, LLM-powered applications, and agentic AI systems. You will collaborate with cross-functional engineering, data, cloud, and stakeholder teams to deliver scalable, secure, and mission-focused AI capabilities for federal clients, while helping guide technical direction, strengthen engineering practices, and mentor other engineers. Responsibilities include, but are not limited to the duties listed below Generative AI & LLM Solution Delivery Lead the design, development, prototyping, and refinement of AI-powered capabilities using generative AI, large language models, retrieval patterns, prompt/context engineering, and secure API integrations. Agentic AI System Development Own end-to-end agentic AI development lifecycles, including model selection, agent design, tool/function calling, orchestration, response synthesis, evaluation, and deployment of reliable AI agents. Senior Software Engineering Leadership Apply strong software engineering principles to design maintainable, testable, and scalable systems; conduct code reviews, establish technical patterns, and leverage AI-assisted development tools responsibly to accelerate delivery. Cross-Functional Technical Collaboration Partner with data engineers, software engineers, data scientists, cloud engineers, and mission stakeholders to translate business and mission needs into operational AI and automation solutions. Cloud Enablement & DevSecOps Integration Design and automate deployment workflows using Infrastructure as Code (IaC), CI/CD pipelines, containers, and cloud-native services to support secure, repeatable, and scalable AI delivery. Production Monitoring & Optimization Monitor AI systems post-deployment, perform performance tuning, and apply best practices for reliability and scalability. Technical Rigor & Documentation Write clean, well-documented code following industry and federal guidelines; support reproducible development. Technical Mentorship & Continuous Improvement Stay current on emerging AI/ML trends, agentic frameworks, model capabilities, and engineering practices while mentoring team members and contributing to reusable standards, documentation, and technical design reviews. Requirements What You Bring Bachelor's or Master's in Computer Science, AI/ML, or a related field. 7+ years of hands-on software engineering experience, including significant experience delivering AI/ML, generative AI, or LLM-powered solutions in production or production-like environments. Experience building generative AI applications, working with LLMs, implementing tool/function calling, and applying model evaluation, prompt/context engineering, or retrieval-augmented generation approaches. Experience designing or implementing agentic AI solutions using frameworks or platforms such as Agent2Agent Protocol, Bedrock Agents, Mastra, CrewAI, Strands, AgentCore, LangChain, or LangGraph. Strong understanding of leading AI APIs and model platforms such as OpenAI, Anthropic, Gemini, Amazon Bedrock, and Google Vertex AI. Proficiency in TypeScript and familiarity with key libraries and frameworks such as Nx, Next.js, Mastra, Vercel AI SDK, Playwright, Jest, and Vite. Python proficiency and familiarity with libraries and frameworks (uv, Pydantic, FastAPI, CrewAI, LangChain, LangGraph, Unstructured). Demonstrated curiosity and practical experimentation with emerging AI technologies, with a strong focus on responsible innovation and measurable mission impact. Familiarity with CI/CD pipelines (GitLab CI) Experience with VS Code and AI extensions such as Cline and Claude Code. Strong communication skills and client-oriented mindset. U.S. Citizenship with eligibility for DoD Secret clearance. Preferred Curious and experimental about the latest innovations in AI with an orientation toward the relentless pursuit of delivering mission impact. Exposure to adjacent skillsets such as data engineering, data science, UI/UX, cloud engineering, and platform engineering to understand the entire software ecosystem. Experience with IaC tools such as Terraform, Open Tofu, AWS CDK, or CloudFormation to deploy cloud native applications. Knowledge of federal cybersecurity, RMF, FedRAMP, or regulatory frameworks. Why This Role Matters Real-World Impact - Your work will support defense and health agencies where AI solutions directly contribute to national security and public well-being. Growth-Oriented Technical Leadership - Work with technical leaders, shape agentic AI delivery practices, and mentor team members while continuing to deepen your own expertise in advanced AI engineering. Culture of Empowerment - You'll be part of a team that values innovation, trust, collaboration, and mission success. Salary Range: $155,000 - $200,000 annually. Actual compensation will be determined based on the selected candidate's experience, education, certifications, skills, and overall qualifications. Benefits Health Care Plan (Medical, Dental & Vision) Retirement Plan (401k, IRA) Life Insurance (Basic, Voluntary & AD&D) Paid Time Off (Vacation, Sick & Public Holidays) Family Leave (Maternity, Paternity) Short Term & Long Term Disability Training & Development Wellness Resources

Description Overview Join a team where innovation meets mission. Our AI, cloud, cyber, and modernization solutions save agencies thousands of hours, safeguard national security, and strengthen health and humanitarian missions worldwide. With 1,700+ team members, 1,500+ AI/data experts, and 100+ prime contracts, we deliver at scale and with purpose. We've been recognized as a Top Workplace by the Washington Post for six straight years and named to the Inc. 5000 Fastest Growing Private Companies 13 of the past 14 years. Credence is a welcoming home for those looking to grow and contribute to positive change. We encourage all employees to expand beyond their boundaries, dive into important world-changing Federal challenges. Credence has an immediate need for an AI Platform & DevSecOps Engineer to support federal programs hosted within AWS GovCloud. This hands-on engineering role combines DevSecOps, cloud infrastructure, platform engineering, security automation, and AI platform enablement to support secure and reliable delivery of mission-critical applications. The engineer will design, automate, secure, and operate cloud infrastructure, CI/CD pipelines, container platforms, and shared platform services while supporting the infrastructure and operational capabilities needed for AI-enabled applications and services. The ideal candidate has a strong foundation in AWS, Kubernetes, Infrastructure as Code (IaC), CI/CD, Python, security automation, and production operations, along with practical knowledge of modern AI technologies and the infrastructure patterns used to securely deploy and operate AI-enabled solutions. Core Responsibilities DevSecOps & Platform Engineering: Design, build, and maintain secure, scalable platform capabilities supporting application development and delivery within AWS GovCloud. Develop reusable infrastructure, automation, deployment patterns, and platform services that improve engineering consistency, security, and developer productivity. AWS GovCloud Architecture & Management: Design, implement, and maintain secure, scalable, and compliant AWS GovCloud environments supporting DoD and federal applications. Work with AWS services including Amazon EKS, ECS/Fargate, IAM, VPC, S3, CloudWatch, and other approved cloud-native services. DevSecOps Pipeline Development: Build, maintain, and improve CI/CD pipelines using technologies such as GitLab CI/CD, Jenkins, AWS CodePipeline, and related tooling. Automate application and infrastructure deployments while integrating testing, security scanning, compliance checks, and deployment controls into delivery workflows. Infrastructure as Code (IaC): Automate infrastructure provisioning and configuration using technologies such as Terraform, CloudFormation, and Ansible. Develop reusable infrastructure components and apply version control, peer review, automated validation, and repeatable deployment practices. Containerization & Orchestration: Deploy and operate containerized applications using Docker/OCI containers and Kubernetes, including Amazon EKS. Support workload configuration, networking, storage, secrets, scaling, resource management, upgrades, security, and troubleshooting. Security & Compliance: Integrate security throughout the software development lifecycle and support compliance with applicable federal cybersecurity frameworks, including NIST 800-53, NIST 800-171, RMF, FedRAMP, STIGs, and Zero Trust principles. Implement and support automated security capabilities including SAST/DAST, software composition analysis, container scanning, IaC scanning, secrets detection, vulnerability management, and compliance validation. AI Platform Enablement: Support the cloud infrastructure and shared platform capabilities required to securely deploy and operate AI-enabled applications and services. Work with AI and software engineering teams to establish repeatable patterns for deployment, configuration, access control, security, monitoring, scalability, and operational support. AI/LLM Service Integration: Support the secure integration and operation of approved AI and LLM services, including platforms such as Amazon Bedrock and other enterprise AI services. Assist engineering teams with infrastructure, authentication and authorization, API connectivity, configuration, deployment automation, monitoring, and operational troubleshooting. Monitoring, Observability & Incident Response: Implement monitoring, logging, tracing, dashboards, and alerting across cloud infrastructure, Kubernetes, applications, and platform services using technologies such as AWS CloudWatch, Security Hub, GuardDuty, Splunk/ELK, Prometheus, Grafana, OpenTelemetry, or comparable solutions. Participate in incident response, root-cause analysis, vulnerability remediation, and continuous reliability improvements. Automation & Scripting: Develop automation and platform tooling using Python, Bash, PowerShell, or similar technologies to eliminate repetitive operational tasks, integrate services and APIs, enforce platform standards, and improve deployment efficiency. Production Operations: Troubleshoot complex infrastructure, application, CI/CD, Kubernetes, networking, and cloud service issues in production and production-like environments. Support operational readiness, system reliability, capacity, performance, and continuous improvement. Collaboration & Knowledge Sharing: Work closely with software engineers, AI engineers, cybersecurity teams, cloud engineers, architects, and mission stakeholders to integrate security, automation, and platform capabilities throughout the software development lifecycle. Develop technical documentation, architecture diagrams, runbooks, and reusable engineering standards. Why This Role Matters Mission Impact - Build and operate secure cloud and DevSecOps capabilities that directly support mission-critical federal applications and emerging AI-enabled solutions. Secure AI Enablement - Help bridge the gap between AI development and production operations by providing secure, automated, observable, and repeatable platform capabilities for deploying AI-enabled applications within federal environments. Modern Platform Engineering - Work across AWS GovCloud, Kubernetes, Infrastructure as Code, CI/CD, automation, cybersecurity, observability, and emerging AI technologies while helping modernize how applications are delivered and operated. Cross-Functional Engineering - Collaborate with DevSecOps, software, AI, cloud, and cybersecurity engineers to solve complex technical challenges without being limited to a single technology domain. Continuous Growth - Expand existing DevSecOps and cloud expertise into AI platform engineering while continuing to deepen skills in automation, security, cloud-native technologies, and production operations. Requirements What You Bring Bachelor's degree in Computer Science, Information Technology, Engineering, Cybersecurity, or a related technical field, or equivalent relevant professional experience. 5+ years of hands-on experience in DevSecOps, DevOps, cloud engineering, platform engineering, software engineering, or related technical roles. Strong hands-on experience designing, deploying, or operating workloads within AWS; AWS GovCloud experience is highly desirable. Hands-on experience with Docker/OCI containers and Kubernetes, preferably Amazon EKS. Experience developing and maintaining CI/CD pipelines using GitLab CI/CD, Jenkins, AWS CodePipeline, or comparable technologies. Strong experience with Infrastructure as Code, including Terraform, CloudFormation, or comparable technologies. Proficiency with Python and experience using Bash, PowerShell, or similar scripting languages for automation. Experience with Git-based development workflows, automated testing, artifact management, and modern software delivery practices. Experience integrating security capabilities into CI/CD and cloud environments, including vulnerability scanning, secrets management, IAM, secure configuration, and automated security controls. Experience implementing monitoring, logging, alerting, and operational troubleshooting for production or production-like environments. Working knowledge of AI/ML and generative AI technologies, including LLMs, AI APIs, model inference, and cloud infrastructure supporting AI-enabled applications. Experience supporting, deploying, integrating, or operating AI/ML or AI-enabled applications in cloud or containerized environments. Understanding of cloud security principles, identity and access management, networking, encryption, secrets management, and least-privilege access. Strong troubleshooting, technical communication, documentation, and cross-functional collaboration skills. U.S. Citizenship with eligibility for a DoD Secret clearance. Preferred Experience supporting DoD, federal civilian, or other highly regulated environments. Hands-on experience with AWS GovCloud. Knowledge of federal cybersecurity requirements and frameworks including RMF, NIST 800-53, NIST 800-171, FedRAMP, DISA STIGs, and Zero Trust. Experience with Amazon Bedrock, Amazon Sagemaker, or other enterprise AI/ML platforms and services. Familiarity with operational considerations for AI workloads, including security, observability, scalability, availability, performance, and cost. Experience implementing CI/CD or platform automation supporting AI-enabled applications and services. Familiarity with AI security and governance considerations within federal or regulated environments. Experience with Helm, Argo CD, Flux, or other Kubernetes/GitOps technologies. Experience with observability technologies such as CloudWatch, Prometheus, Grafana, OpenTelemetry, Splunk, or ELK. Experience with software supply-chain security practices such as SBOM generation, artifact signing, provenance, container hardening, and policy enforcement . click apply for full job details

Overview Join a team where innovation meets mission. Our AI, cloud, cyber, and modernization solutions save agencies thousands of hours, safeguard national security, and strengthen health and humanitarian missions worldwide. With 1,700+ team members, 1,500+ AI/data experts, and 100+ prime contracts, we deliver at scale and with purpose. We've been recognized as a Top Workplace by the Washington Post for six straight years and named to the Inc. 5000 Fastest Growing Private Companies 13 of the past 14 years. Credence is a welcoming home for those looking to grow and contribute to positive change. We encourage all employees to expand beyond their boundaries, dive into important world-changing Federal challenges. Position Summary Credence has an immediate need for a Senior AI Data Engineer to join our growing AI and Automation practice. You will be a technical anchor in our AI and Automation practice. You'll apply advanced AI and data engineering expertise to design, build, and deploy data-driven solutions. You'll drive agentic AI development lifecycles and collaborate across engineering, data, and stakeholder teams to deliver high-impact, cloud-native AI capabilities that advance federal missions. Responsibilities include, but are not limited to the duties listed below Data Integrations for Generative AI & LLM Usage Build and optimize data pipelines that prepare, clean, and structure data for generative AI and LLM usage. Data Lake & Warehouse Engineering Manage and organize large datasets across cloud platforms (e.g., AWS, Azure, GCP) using data lake and warehouse technologies. Implement medallion architecture (Bronze/Silver/Gold layers) to ensure data quality, lineage, and accessibility. Database Management & Performance Work with both SQL and NoSQL systems to model, query, and load large-scale datasets. Monitor, tune, and maintain high-performance data stores supporting analytics and reporting. Collaborative Engineering Work alongside data engineers, software engineers, and data scientists to develop operational agentic AI systems. Cloud Enablement Help automate model deployment workflows using Infrastructure as Code (IaC), CI/CD pipelines, and container orchestration tools. Production Monitoring & Optimization Monitor AI systems post-deployment, perform performance tuning, and apply best practices for reliability and scalability. Technical Rigor & Documentation Write clean, well-documented code following industry and federal guidelines, support reproducible development. Professional Growth Stay current on AI/ML trends and tools and actively learn from senior team members through mentorship and technical design reviews. Requirements U.S. Citizenship with eligibility for DoD Secret clearance. Bachelor's or Master's in Computer Science, Data/AI/ML, or a related field. 7+ years of hands-on experience delivering Data/AI/ML solutions. Strong understanding of ETL, ELT, and other similar data pipeline processes, as well as Enterprise Data and Storage Systems, such as experience with OpenSearch/Elastic Search, Kafka, Bedrock, Glue, DataBricks, Snowflake, AWS S3, RDS, EBS, or Glacier Experience with vector databases, embeddings, and their affiliated data structures, file formats, services, APIs, etc (e.g. FAISS, PGVector, OpenSearch/Elasticsearch, Hugging face with Pinecone, Bedrock Knowledge Base) Experience in generative AI, working with LLMs, adding tool calls (MCP) and agents (A2A). Understanding of leading AI APIs such as OpenAI, Anthropic, Gemini, Bedrock, Vertex for use with LLMs and RAG search. Familiarity with CI/CD pipelines (GitLab/GitHub/Jenkins) Experience with VS Code and AI extensions such as Cline and Claude Code. Strong communication skills and client-oriented mindset. Preferred Curious and experimental about the latest innovations in AI with an orientation toward the relentless pursuit of delivering mission impact. Python proficiency and familiarity with libraries and frameworks (Pyspark, Pandas, uv, Pydantic, FastAPI, CrewAI, LangChain, LangGraph, Unstructured). Experience with IaC tools such as Terraform, Open Tofu, AWS CDK, or CloudFormation to deploy cloud native applications. Experience with agentic frameworks such as Agent2Agent Protocol, AWS Bedrock Agents, Mastra, CrewAI, Strands, or AgentCore. Exposure to adjacent skillsets such as data science, UI/UX, cloud engineering, and platform engineering to understand the entire software ecosystem. Knowledge of federal cybersecurity, RMF, FedRAMP, or regulatory frameworks. Why This Role Matters Real-World Impact - Your work will support defense and health agencies where AI solutions directly contribute to national security and public well-being. Growth-Oriented Environment - Learn from technical leaders, innovate within Agentic AI, and mentor those around you in AI best practices. Culture of Empowerment - You'll be part of a team that values innovation, trust, collaboration, and mission success. Salary Range: $115,000 - $155,000 annually. Actual compensation will be determined based on the selected candidate's experience, education, certifications, skills, and overall qualifications. Benefits Health Care Plan (Medical, Dental & Vision) Retirement Plan (401k, IRA) Life Insurance (Basic, Voluntary & AD&D) Paid Time Off (Vacation, Sick & Public Holidays) Family Leave (Maternity, Paternity) Short Term & Long Term Disability Training & Development Wellness Resources

Overview Join a team where innovation meets mission. Our AI, cloud, cyber, and modernization solutions save agencies thousands of hours, safeguard national security, and strengthen health and humanitarian missions worldwide. With 1,700+ team members, 1,500+ AI/data experts, and 100+ prime contracts, we deliver at scale and with purpose. We've been recognized as a Top Workplace by the Washington Post for six straight years and named to the Inc. 5000 Fastest Growing Private Companies 13 of the past 14 years. Credence is a welcoming home for those looking to grow and contribute to positive change. We encourage all employees to expand beyond their boundaries, dive into important world-changing Federal challenges. Position Summary Credence has an immediate need for a Senior AI Software Engineer to join our growing AI and Automation practice. In this role, you will serve as a senior technical contributor responsible for designing, developing, and deploying advanced AI-driven solutions, including generative AI, LLM-powered applications, and agentic AI systems. You will collaborate with cross-functional engineering, data, cloud, and stakeholder teams to deliver scalable, secure, and mission-focused AI capabilities for federal clients, while helping guide technical direction, strengthen engineering practices, and mentor other engineers. Responsibilities include, but are not limited to the duties listed below Generative AI & LLM Solution Delivery Lead the design, development, prototyping, and refinement of AI-powered capabilities using generative AI, large language models, retrieval patterns, prompt/context engineering, and secure API integrations. Agentic AI System Development Own end-to-end agentic AI development lifecycles, including model selection, agent design, tool/function calling, orchestration, response synthesis, evaluation, and deployment of reliable AI agents. Senior Software Engineering Leadership Apply strong software engineering principles to design maintainable, testable, and scalable systems; conduct code reviews, establish technical patterns, and leverage AI-assisted development tools responsibly to accelerate delivery. Cross-Functional Technical Collaboration Partner with data engineers, software engineers, data scientists, cloud engineers, and mission stakeholders to translate business and mission needs into operational AI and automation solutions. Cloud Enablement & DevSecOps Integration Design and automate deployment workflows using Infrastructure as Code (IaC), CI/CD pipelines, containers, and cloud-native services to support secure, repeatable, and scalable AI delivery. Production Monitoring & Optimization Monitor AI systems post-deployment, perform performance tuning, and apply best practices for reliability and scalability. Technical Rigor & Documentation Write clean, well-documented code following industry and federal guidelines; support reproducible development. Technical Mentorship & Continuous Improvement Stay current on emerging AI/ML trends, agentic frameworks, model capabilities, and engineering practices while mentoring team members and contributing to reusable standards, documentation, and technical design reviews. Requirements What You Bring Bachelor's or Master's in Computer Science, AI/ML, or a related field. 7+ years of hands-on software engineering experience, including significant experience delivering AI/ML, generative AI, or LLM-powered solutions in production or production-like environments. Experience building generative AI applications, working with LLMs, implementing tool/function calling, and applying model evaluation, prompt/context engineering, or retrieval-augmented generation approaches. Experience designing or implementing agentic AI solutions using frameworks or platforms such as Agent2Agent Protocol, Bedrock Agents, Mastra, CrewAI, Strands, AgentCore, LangChain, or LangGraph. Strong understanding of leading AI APIs and model platforms such as OpenAI, Anthropic, Gemini, Amazon Bedrock, and Google Vertex AI. Proficiency in TypeScript and familiarity with key libraries and frameworks such as Nx, Next.js, Mastra, Vercel AI SDK, Playwright, Jest, and Vite. Python proficiency and familiarity with libraries and frameworks (uv, Pydantic, FastAPI, CrewAI, LangChain, LangGraph, Unstructured). Demonstrated curiosity and practical experimentation with emerging AI technologies, with a strong focus on responsible innovation and measurable mission impact. Familiarity with CI/CD pipelines (GitLab CI) Experience with VS Code and AI extensions such as Cline and Claude Code. Strong communication skills and client-oriented mindset. U.S. Citizenship with eligibility for DoD Secret clearance. Preferred Curious and experimental about the latest innovations in AI with an orientation toward the relentless pursuit of delivering mission impact. Exposure to adjacent skillsets such as data engineering, data science, UI/UX, cloud engineering, and platform engineering to understand the entire software ecosystem. Experience with IaC tools such as Terraform, Open Tofu, AWS CDK, or CloudFormation to deploy cloud native applications. Knowledge of federal cybersecurity, RMF, FedRAMP, or regulatory frameworks. Why This Role Matters Real-World Impact - Your work will support defense and health agencies where AI solutions directly contribute to national security and public well-being. Growth-Oriented Technical Leadership - Work with technical leaders, shape agentic AI delivery practices, and mentor team members while continuing to deepen your own expertise in advanced AI engineering. Culture of Empowerment - You'll be part of a team that values innovation, trust, collaboration, and mission success. Salary Range: $155,000 - $200,000 annually. Actual compensation will be determined based on the selected candidate's experience, education, certifications, skills, and overall qualifications. Benefits Health Care Plan (Medical, Dental & Vision) Retirement Plan (401k, IRA) Life Insurance (Basic, Voluntary & AD&D) Paid Time Off (Vacation, Sick & Public Holidays) Family Leave (Maternity, Paternity) Short Term & Long Term Disability Training & Development Wellness Resources