Senior AI Engineer
ChatGPT Jobs
hybridseniorbackendfrontend King of Prussia, PA 17 days ago via LinkedIn
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AI Platform EngineeringREST APIsKubernetesReactNext.jsPythonGoPostgreSQLRedisGenAI/MLOps
About the role
Role Overview
Senior AI Engineer / AI Platform Engineer for the Lockheed Martin Artificial Intelligence Center (LAIC). You will primarily build and evolve the AI Factory platform—including robust back-end services, front-end interfaces, and API contracts that support GenAI, LLM, RAG, and agentic workflows.
Key Responsibilities
- API-first development: Design, implement, and maintain high-performance REST APIs for AI model orchestration and resource management.
- Full-stack ownership: Build end-to-end features, including:
- React/Next.js front-end experiences
- Python/Go back-end services at scale
- Platform design & governance: Help design modular, discoverable internal platform components that support LLM, RAG, and Agentic workflows.
- AI-augmented engineering: Use AI coding assistants and LLM agents to accelerate development (e.g., boilerplate generation, test generation, initial code reviews).
- Service integration: Create middleware to bridge Kubernetes infrastructure and user-facing interfaces.
- System architecture & performance: Optimize data flow between UI dashboards, metadata stores (PostgreSQL/Redis), and GPU-accelerated compute clusters.
Qualifications
- Bachelor’s degree in CS/Engineering (or equivalent practical experience).
- Production experience building and maintaining backend services in modern languages (Python, Go, Java, or C#).
- Experience designing, implementing, and operating REST APIs in production.
- Experience deploying and operating containerized services in Kubernetes.
- Cross-team collaboration from design through production.
- Must be a US Citizen.
Nice to Have
- Experience with AI platform components for LLMs, RAG, and agentic workflows.
- Hands-on use of AI coding assistants/agents in daily development.
About ChatGPT Jobs
Lockheed Martin Artificial Intelligence Center (LAIC) builds AI platforms and internal tooling to support large-scale GenAI and MLOps workflows. The team is focused on creating platform services, APIs, and interfaces that enable AI/ML practitioners to deploy and operate models effectively.
Scraped 7/10/2026