AI Application Engineer

Bigbear.ai; McLean (VA); Hybrid; USD 120,000 - 180,000; Full time

Job summary

BigBear.ai seeks an AI Applications Engineer to build end-to-end AI applications and a config-driven decision-support platform that blends LLM-powered chat, structured data, and dashboards to support operational readiness and logistics workflows. You will own features across backend APIs, database, and a modern React UI while migrating a Dash/Flask app.

You will design and implement LLM/RAG pipelines with LangChain or LangChain4J, connect to external data sources, vector stores, Redis, and

Qualifications

• 3+ years of full-stack development with Python and React/TypeScript.
• Ability to obtain and maintain a security clearance.
• Hands-on LLM/RAG experience with LangChain or LangChain4J.
• 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 deployment workflows.
• Strong debugging, testing, and code review habits.
• Ability to work independently across backend, frontend, database, and AI layers.
• Proficient with using AI coding assistants as part of daily workflow.

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 or LangChain4J.
• Integrate LLM providers, document ingestion, semantic search, and chat/report features.
• Work with vector stores (PostgreSQL pgvector, Weaviate), Redis, and Keycloak auth; implement RBAC.
• 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 secure.
• Use AI-assisted development tools effectively and ship production-quality changes.

Skills

Python

React/TypeScript

LLM/RAG

REST APIs

SQL

Debugging

Testing

CI/CD

Independent work

Tools

FastAPI

Docker

GitHub Actions

PostgreSQL

pgvector

LangChain

Nx monorepo

Redis

Keycloak

Job description

Residency

All applicants must currently reside in the United States

All applicants must reside in the National Capital Region.

Overview

BigBear.ai is seeking an AI Applications Engineer. In this position, you will develop and maintain AI applicationsand a config-driven decision-support platform that combines LLM-powered chat (RAG), structured data (MCP/PostgreSQL), and dashboards to supportoperational 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.

What you will do

• 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 pipelinesusing 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 Keycloakauth; 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/RAGexperience building production features with LangChainor LangChain4J(chains, retrievers, agents/tools, embeddings, vector stores)
• Experience building and consuming REST APIs(FastAPI or similar)
• Solid PostgreSQLskills: 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 assistantsas 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.