Jobs at Lockheed Martin

Build and deploy production AI systems centered on ontologies, knowledge graphs, and agent workflows. Translate enterprise data and user needs into semantic models, graph systems, and reliable software. Develop evaluation, testing, observability, security, and deployment controls across AI, data, application, and infrastructure layers. Work directly with domain experts, lead technical delivery, mentor engineers, and convert customer engagements into reusable platform capabilities.

Lead architecture and delivery of production AI systems involving agents, ontologies, knowledge graphs, semantic models, and enterprise data integrations. Translate ambiguous user needs into secure, reliable capabilities; establish governance, evaluation, traceability, and human-review practices; guide deployments across cloud platforms, APIs, databases, and applications; resolve complex system issues; mentor engineers; and convert customer-specific solutions into reusable platform capabilities.

Leads the design, development, governance, and productization of enterprise data models, pipelines, data products, and ontologies. Builds machine-learning-ready datasets, implements security and lineage controls, optimizes Databricks and Delta Lake environments, establishes data-product standards, collaborates with architects and data scientists, and mentors engineering talent. The role also defines product roadmaps, service levels, usage metrics, and continuous-improvement processes for enterprise data assets supporting AI agents, analytics, and applications.

Build and deploy production AI systems focused on ontologies, semantic models, and knowledge graphs. Translate enterprise data and user needs into AI agent workflows, software services, APIs, and graph systems. Develop evaluation, testing, observability, security, and deployment controls for AI and data products. Work directly with domain experts, lead technical delivery, resolve production issues, present architectural decisions, review code, mentor engineers, and convert customer engagements into reusable platform capabilities.

Leads AI and machine learning research and engineering teams developing autonomous systems and mission applications. Oversees algorithm research, model development, prototyping, testing, deployment, and optimization across reinforcement learning, deep learning, computer vision, signal processing, and control systems. Manages workloads, resources, project delivery, technical standards, stakeholder communication, and employee development while identifying opportunities to apply emerging AI technologies.

Develop and support SAP S/4HANA and ECC solutions for logistics and production planning value streams. Design ABAP enhancements, interfaces, forms, custom applications, RAP solutions, and integrations across SAP and external systems. Evaluate proofs of concept, scope RICEWF requirements, review technical specifications, and ensure scalable, sustainable implementations. Collaborate with scrum teams and technology partners on complex design decisions while mentoring junior developers and delivering high-quality enterprise software.

Researches and develops AI, machine learning, computer vision, signal processing, and control algorithms for autonomous defense and commercial systems. Builds, trains, evaluates, and optimizes models; develops prototypes and data products; defines requirements; and collaborates across perception, mission planning, simulation, testing, and customer application teams.