{"id":1926875,"url":"https://alion.io/job/lockheed-martin-ai-machine-learning-engineering-staff-2","title":"AI Machine Learning Engineering Staff","company":{"id":37086,"name":"Lockheed Martin","domain":"lockheedmartin.com","url":"https://alion.io/company/lockheedmartin","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"A","score":99,"open_postings":83,"ghost_share":0,"stale_share":0,"repost_share":0.048,"time_to_fill_p50_days":27,"computed_at":"2026-10-08T05:49:30Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":120600,"max":224000,"currency":"USD","period":"year","gross":null,"usd_annual":224000},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"AWS Strands Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"CrewAI","optional":false},{"name":"Docker","optional":false},{"name":"GitLab CI","optional":false},{"name":"Google ADK","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"Machine Learning","optional":false},{"name":"Pydantic AI","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Tool Use","optional":false},{"name":"Amazon EKS","optional":true},{"name":"CIS Benchmarks","optional":true},{"name":"Django","optional":true},{"name":"Flask","optional":true},{"name":"Grafana","optional":true},{"name":"Harbor","optional":true},{"name":"JavaScript","optional":true},{"name":"Langfuse","optional":true},{"name":"LLM","optional":true},{"name":"OpenShift","optional":true},{"name":"OpenTelemetry","optional":true},{"name":"OWASP Top 10","optional":true},{"name":"Prometheus","optional":true},{"name":"React.js","optional":true},{"name":"SBOM","optional":true},{"name":"TypeScript","optional":true}],"status":"live","first_seen_at":"2026-09-25T18:38:16Z","employer_posted_date":"2026-10-05","last_verified_at":"2026-10-08T21:51:17Z","board_verified":true,"closed_at":null,"days_open":13,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":13},"description":"Standard Job Description\nThe Data and AI Enablement Org is seeking an engineer for the AI Strategy Acceleration portfolio, focused on accelerated agentic development across the enterprise.\nWhat You Will Be Doing:\nHit the ground running - ship platform features, pipeline improvements, and security enhancements fast in rapid 4-day sprint cycles\nDesign and implement agentic AI systems (tool-calling, RAG pipelines, autonomous workflows) using frameworks such as LangGraph, CrewAI, AWS Strands, Google ADK, Pydantic AI, and LangChain\nDrive security practices including vulnerability remediation, authentication systems, and compliance artifacts - surfacing risks and recommendations to technical leadership\nMaintain and improve test automation and regression frameworks\nMaintain and evolve the CI/CD pipeline (GitLab CI) including security scanning, container builds, and package publishing\nContribute across the full platform as needed - new features, tooling, developer experience, metrics, and other priorities as the product evolves\nExecute on architectural direction from senior technical leadership while contributing ideas and improvements\nWho You Are:\nYou ship production-quality code fast - iterating rather than perfecting, clean, tested, and secure without cutting corners\nYou use GenAI coding assistants as a core part of your workflow\nYou have deep experience in Python, CI/CD, and containerized deployment\nYou implement agentic AI patterns in production-grade systems, not just prototypes\nYou care about test quality, security, and pipeline reliability as much as features\nYou own team commitments, not just your tasks - if a teammate is blocked, you help deliver rather than starting your next item\nUS Citizenship required due to program requirements and system access.\nStandard Job Description:\nResponsible for developing, integrating, and deploying autonomy and artificial intelligence algorithms for mission systems, supporting the technology development life cycle from requirements generation through development, integration, and testing, as well as research in some organizations.Develops, integrates, and implements algorithms to enable perception, motion/mission planning, controls, etc. functionality in LM products and platforms; Translates requirements and applies requirements to development code, integrating autonomy, AI or machine learning algorithms to LM products and platforms; Determines software methods to best acquire and execute knowledge; Implements algorithms into software to train systems to recognize patterns and perform specific functions; Responsible for various phases of developing and maintaining autonomy software from requirements generation, software design and development to integration, testing, troubleshooting and debugging, and implementation; Review test outcomes, conducts troubleshooting, and works to debug issues; Develops human-machine interface scenarios, breaking missions into tasks; Documents interface requirements and implements human-machine interfaces\nBasic Qualifications\n8+ years of progressive software development experience with strong Python engineering skills (async patterns, packaging, type systems, cross-platform compatibility) and hands-on production system delivery\nExperience with LLMs, Generative AI, or agentic AI frameworks (e.g., LangGraph, CrewAI, Google ADK, AWS Strands) with understanding of tool-calling, RAG, and autonomous workflow patterns\nExperience with containerized development and deployment (e.g., Docker, Kubernetes)\nUS Citizenship is required due to program requirements and system access\nBachelor's degree in Computer Science, Information Technology, Engineering, AI/ML, or a related field or equivalent education/experience\nDesired Skills\nExperience designing and maintaining test automation frameworks (e.g., unit, integration, regression, e2e) with proven ability to improve coverage, reliability, and test infrastructure\nExperience maintaining and improving CI/CD pipelines (e.g., GitLab CI) including automated testing, security scanning, release automation, enterprise packaging (Nexus/Harbor), and semantic versioning\nProduction experience building agentic AI systems: tool-calling orchestration, RAG pipelines, multi-step autonomous workflows, agent evaluation and testing patterns\nInformation security, compliance, and classified environments: CIS benchmarks, security control frameworks, ATO artifacts, air-gapped deployment and offline packaging\nAgent evaluation methodology: benchmarking, quality metrics, correctness validation for LLM-powered systems\nCloud platform experience (e.g., AWS, OpenShift, EKS) including deployment, scaling, and operational ownership of containerized services\nAdvanced DevSecOps and secure coding practices: security scanning (SAST/DAST/container), SBOM generation, vulnerability remediation, OAuth2/SSO/MFA, OWASP top 10\nDemonstrated use of GenAI coding assistants to accelerate development and increase quality\nFull-stack development: Python web frameworks (Django, Flask) or React/TypeScript frontend + Python API backend for developer portals or internal tools\nOpenTelemetry instrumentation for AI/agent systems: metrics, tracing, logging, and integration with observability platforms (Prometheus, Grafana, Langfuse)\nMaster's degree in Computer Science, Information Technology, Engineering, AI/ML, or related field\nPay Information\nGeoZone Definition: GeoZones are geographic groupings created by Lockheed Martin to align compensation ranges with regional labor markets and cost-of-labor differences across the United States. Locations are assigned a Geo Zone based on the primary work location of the role.\nFull-time salary range (GEOZONE 1): $150800.00 - $280000.00 Includes metropolitan areas such as Sunnyvale CA; Pal Alto, CA; New York City metropolitan area; Newark, New Jersey; etc.\n\nFull-time salary range (GEOZONE 2): $135700.00 - $251900.00 Includes metropolitan areas such as Denver, CO; King of Prussia, PA; Stratford, CT; Moorestown, NJ; etc.\n\nFull-time salary range (GEOZONE 3): $120600.00 - $224000.00Includes metropolitan areas such as Dallas-Fort Worth, TX; Orlando, FL; Grand Prairie, TX; Marietta, GA; etc.\n\nFull-time salary range (GEOZONE 4): $108600.00 - $201600.00Includes metropolitan areas such as Camden, AR; Lexington, KY; Lufkin, TX; etc. \n\nAt Lockheed Martin, we know mission success starts with taking care of our people. Our Total Rewards program is designed to attract top talent, support your well-being, and help you grow-both professionally and personally.\nThe salary range for this position is as listed on the requisition. Please note that the salary information listed is a general guideline only.\nLockheed Martin considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/ training, key skills as well as market(work location) and business considerations when extending an offer.\nBenefits offered: Medical, Dental, Vision, Flexible work arrangements and schedules (e.g., 4x10), 401(k) match, Paid time off, Holidays, Parental Leave, EAP, Flexible Spending Accounts, Education Assistance, Life Insurance, Short-Term Disability, and Long-Term Disability.\nAnnual short-term and/or long-term incentive compensation programs may be offered depending on the position. Payments under these annual programs are not guaranteed and can vary from year to year and are tied to a range of performance metrics.\nFor (Washington state applicants only) Non-represented full-time employees: accrue at least 10 hours per month of Paid Time Off (PTO) to be used for incidental absences and other reasons; receive at least 90 hours for holidays. Represented full time employees accrue 6.67 hours of Vacation per month; accrue up to 52 hours of sick leave annually; receive at least 96 hours for holidays. 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