AI Application Engineer

About the role

BigBear.ai is seeking an AI Applications Engineer. In this position, you will develop and maintain AI applications and a config-driven decision-support platform that combines LLM-powered chat (RAG), structured data (MCP/PostgreSQL), and dashboards to support operational readiness and logistics workflows. You will own features end-to-end across backend APIs, database, and the modern React UI, with ongoing support for the existing Dash/Flask application during migration.

Responsibilities

• Build and maintain full-stack features: FastAPI services, PostgreSQL schema/migrations, and React/TypeScript UI in an Nx monorepo
• Design, implement, and maintain LLM/RAG pipelines using LangChain (Python) or LangChain4J (Java)—retrieval, embeddings, tool/agent orchestration, and prompt workflows
• Integrate LLM providers (e.g. OpenAI, Anthropic, Ask Sage), document ingestion, semantic search, and chat/report features
• Work with vector stores (e.g. PostgreSQL (pgvector), Weaviate), Redis, and Keycloak auth; implement role-based access and secure API patterns
• Connect to external systems via MCP, REST/PostgREST, and related data adapters
• Write and maintain tests (pytest, Vitest) and participate in CI/CD (Docker, GitHub Actions)
• Debug production issues, improve reliability/performance, and keep dependencies and security patches current
• Use AI-assisted development tools (e.g. Cursor) effectively: prompt well, review generated code critically, and ship production-quality changes at a steady pace

Requirements

• 3+ years full-stack development with strong Python and React/TypeScript
• Must be able to obtain and maintain a security clearance
• All applicants must currently reside in the United States.
• All applicants must reside in the National Capital Region.
• Hands-on LLM/RAG experience building production features with LangChain or LangChain4J (chains, retrievers, agents/tools, embeddings, vector stores)
• Experience building and consuming REST APIs (FastAPI or similar)
• Solid PostgreSQL skills: schema design, SQL, migrations (pgvector a plus)
• Comfortable with Docker, local dev environments, and basic deployment workflows
• Strong debugging, testing, and code review habits
• Ability to work independently across backend, frontend, database, and AI layers
• Proven comfort using AI coding assistants as a daily workflow—not as a substitute for understanding the codebase

Preferred Qualifications

• Dash/Plotly, Flask, or legacy-to-modern UI migration experience
• Keycloak/OAuth, Redis sessions
• Nx monorepos, TanStack Router/Query, Tailwind CSS
• MCP protocol, Ask Sage, or similar enterprise LLM platforms
• Government/defense or regulated-environment experience