AI Application Engineer

Residency All applicants must currently reside in the United States Overview 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.

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 What you need to have 3+ years full-stack development with strong Python and React/TypeScript Must be able to obtain and maintain a security clearance Hands-on LLM/RAG experience building production features with LangChain or LangChain4J (chains, retrievers, agents/tools, embeddings, vector stores)

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 What we'd like you to have 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 Pay transparency Please note the targeted compensation range is provided as an estimate, and any actual compensation offer may vary depending on the needs of the company, or an applicant's skillset, competencies, experience, education, certifications, location, or other factors. The estimated range does not include the value of any benefits offered. About BigBear.ai BigBear.ai is a leading provider of AI-powered decision intelligence solutions for national security, supply chain management, and digital identity. Customers and partners rely on Bigbear.ai’s predictive analytics capabilities in highly complex, distributed, mission-based operating environments. Headquartered in McLean, Virginia, BigBear.ai is a public company traded on the NYSE under the symbol BBAI. For more information, visit https://bigbear.ai/ and follow BigBear.ai on LinkedIn: @BigBear.ai and X: @BigBearai. BigBear.ai is an Equal opportunity employer all protected groups, including protected veterans and individuals with disabilities.