Forward Deployed Engineer Sr

Lockheed Martin is a leader in aerospace and defense, and they are seeking a Senior Forward-Deployed Engineer to work on their AI Factory platform. This role involves partnering with senior staff and end users to implement and optimize AI/ML operations and ensure effective deployment of solutions.

Responsibilities:

• Own assigned customer deployment workstreams end to end, from technical discovery and solution shaping through implementation, rollout, and handoff to sustained use
• Translate customer and user requirements into deployable AI Factory solutions spanning MLOps pipelines, GenAI backends, data-processing workflows, and agentic applications
• Design, deploy, configure, and maintain Kubernetes-based MLOps pipelines across AWS, Azure, GCP, and on-prem GPU-backed environments, including training, inference, and data-processing workflows
• Adapt platform architecture and integration plans to customer-specific infrastructure, security constraints, runtime requirements, and operational standards
• Act as a technical advocate for AI Factory during implementation by steering customers toward out-of-the-box platform capabilities before custom work is introduced
• Capture platform bugs, performance gaps, reliability risks, and integration friction discovered during deployments, and document actionable remediation suggestions for AI Factory product and engineering teams
• Turn repeated deployment pain points into reusable templates, guardrails, configuration patterns, or implementation guidance that improve future delivery
• Embed traceability, auditability, security, and responsible AI guardrails, including model lineage, data provenance, and access controls, into deployed solutions for regulated environments
• Produce clear, versioned deployment artifacts and operational documentation that support certification, audit readiness, and reliable production support
• Own design decisions for assigned workstreams and contribute substantive feedback in design and code reviews
• Mentor less-experienced engineers on deployment best practices such as Kubernetes debugging, CI/CD for ML, and operating production AI systems
• Evaluate emerging MLOps, GenAI, and agentic capabilities for fit with customer delivery needs and Lockheed Martin's AI Factory platform direction

Requirements:

• 3+ years of hands-on experience in software engineering, platform engineering, MLOps, ML infrastructure, or GenAI systems
• Demonstrated experience owning delivery of production AI/ML systems, platform capabilities, or deployment workstreams across ambiguous requirements and multiple stakeholders
• Experience designing, deploying, or operating Kubernetes-based MLOps pipelines, model training and inference workflows, or data-processing systems in GPU-backed environments
• Demonstrated ability to debug complex deployment issues across infrastructure, containers, networking, security controls, and application runtime behavior
• Strong written and verbal communication skills with customer engineering teams, internal product groups, and peer engineers
• U.S. citizenship and ability to obtain and maintain a Secret or Top Secret clearance
• B.S. (or higher) in Computer Science, Electrical or Aerospace Engineering, Applied Mathematics, or a related discipline
• Working knowledge of platforms such as Amazon SageMaker, Google Vertex AI, Azure ML, Databricks Mosaic AI, IBM watsonx, Dataiku, Domino, or DataRobot
• Familiarity with LLM deployment, prompt engineering, retrieval-augmented generation, or agentic application patterns
• Proficiency in Python plus at least one systems or backend language such as Go, Rust, Java, or C++
• Experience navigating both public-cloud and on-prem GPU-accelerated environments
• Understanding of model and data provenance, bias mitigation, and compliance documentation