Serves as a Staff-level Forward Deployed Engineer for AI Factory (an internal AI/ML Ops Platform), leading the use of Lockheed Martin's AI Factory platform to solve customer MLOps and GenAI problems. Owns customer solution discovery, architecture, implementation strategy, deployment, and adoption for high-value AI/ML workflows while ensuring the platform is used effectively, consistently, and with maximum reuse. Uses this deployment work to identify weaknesses in AI Factory's foundational products and platform, such as design flaws, performance gaps, reliability risks, and integration friction, and drives actionable remediation suggestions back to core platform engineering team.
- 5+ years of related experience in software engineering, platform engineering, MLOps, ML infrastructure, and/or GenAI systems.
- Experience designing, deploying, or operating MLOps pipelines, model deployment workflows, data and artifact lineage, or GenAI application backends.
- Strong communication skills and the ability to work directly with customers, platform teams, and program stakeholders.
- Experience with LLM and GenAI systems, evaluation workflows, prompt or context engineering, or agentic application patterns.
- Demonstrated ability to lead technical direction for other engineers through architecture, decomposition, code review, or deployment standards.
- Hands-on familiarity with Kubernetes-based deployment patterns, GPU-backed environments, and secure software delivery practices.
- U.S. citizenship and ability to obtain and maintain a Secret or Top Secret clearance.
- B.S. (or higher) in Computer Science, Electrical / Aerospace Engineering, Applied Mathematics, or related field.
- Experience with enterprise AI/ML platforms such as Amazon SageMaker, Databricks Mosaic AI, Google Cloud Vertex AI / Gemini Enterprise Agent Platform, Microsoft Foundry, Domino Data Lab, Dataiku, IBM watsonx, or DataRobot.
- Familiarity with Python and at least one backend or systems language
- Demonstrated experience delivering production AI/ML systems or platform capabilities with ambiguous requirements and multiple stakeholders.
- Experience working across cloud and on-prem GPU environments.
- Ability to communicate technical tradeoffs clearly to senior stakeholders while maintaining delivery momentum across customer and internal teams.
Pay Information
GeoZone 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.
- Full-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.
- Full-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.
- Full-time salary range (GEOZONE 3): $120600.00 - $224000.00
- Includes metropolitan areas such as Dallas–Fort Worth, TX; Orlando, FL; Grand Prairie, TX; Marietta, GA; etc.
- Full-time salary range (GEOZONE 4): $108600.00 - $201600.00
- Includes metropolitan areas such as Camden, AR; Lexington, KY; Lufkin, TX; etc.
At 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.
The salary range for this position is as listed on the requisition. Please note that the salary information listed is a general guideline only.
Lockheed 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.
Benefits 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.
- Annual 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.
- For (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. PTO, Vacation, sick leave, and holiday hours are prorated based on start date during the calendar year.
Skills Required
- 5+ years of related experience in software engineering, platform engineering, MLOps, ML infrastructure, and/or GenAI systems
- Experience designing, deploying, or operating MLOps pipelines, model deployment workflows, data and artifact lineage, or GenAI application backends
- Strong communication skills and ability to work directly with customers, platform teams, and program stakeholders
- Experience with LLM and GenAI systems, evaluation workflows, prompt or context engineering, or agentic application patterns
- Ability to lead technical direction for other engineers through architecture, decomposition, code review, or deployment standards
- Hands-on familiarity with Kubernetes-based deployment patterns, GPU-backed environments, and secure software delivery practices
- U.S. citizenship and ability to obtain and maintain a Secret or Top Secret clearance
- Bachelor's degree or higher in Computer Science, Electrical or Aerospace Engineering, Applied Mathematics, or a related field
- Experience with enterprise AI/ML platforms such as Amazon SageMaker, Databricks Mosaic AI, Google Cloud Vertex AI, Gemini Enterprise Agent Platform, Microsoft Foundry, Domino Data Lab, Dataiku, IBM watsonx, or DataRobot
- Familiarity with Python and at least one backend or systems language
- Experience delivering production AI/ML systems or platform capabilities with ambiguous requirements and multiple stakeholders
- Experience working across cloud and on-premises GPU environments
- Ability to communicate technical tradeoffs clearly to senior stakeholders while maintaining delivery momentum
Lockheed Martin Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Lockheed Martin and has not been reviewed or approved by Lockheed Martin.
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Retirement Support — Retirement benefits are described as a standout element, with a strong 401(k) program and options like an employee stock purchase plan. Feedback suggests these features meaningfully enhance total compensation and long‑term financial security.
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Healthcare Strength — Healthcare coverage is portrayed as comprehensive from day one, with multiple plan options, mental health resources, and virtual care. Wellness supports such as on‑site services and preventive programs are also highlighted.
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Flexible Benefits — Work arrangements often include compressed schedules and telework, contributing to a favorable work‑life balance. Feedback suggests this flexibility is a key reason many view the overall package positively.
Lockheed Martin Insights
What We Do
Customer Focus, Innovation and Purpose are Built Into Everything We Do. Lockheed Martin. Your Mission is Ours ™. Headquartered in Bethesda, Maryland, Lockheed Martin is a global security and aerospace company principally engaged in the research, design, development, manufacture, integration and sustainment of advanced technology systems, products and services.
