Note: The job is a remote job and is open to candidates in USA. BigBear.ai is hiring an AI Application Engineer to build full-stack enterprise AI applications and capabilities using LLMs, agents, RAG, and enterprise data integrations. The role focuses on configurable AI workflows, interactive user experiences, and production-quality software.
Responsibilities
- Design and develop full-stack AI applications using Python, REST APIs, React/TypeScript, and relational databases
- Build AI-powered features using LLMs, RAG, semantic search, and agent-based architectures
- Develop integrations connecting AI agents with enterprise databases, APIs, documents, and business systems
- Help build a configurable AI platform that supports domain-specific knowledge, reusable AI capabilities, workflow automation, and interactive user experiences
- Implement and enhance data visualization, dashboards, chat interfaces, and AI-assisted business workflows
- Experiment with AI frameworks, tools, and technologies to evaluate and implement new capabilities
- Collaborate with solution architects, AI engineers, and domain experts to transform business requirements into working applications
- Develop maintainable, tested, secure, and production-quality software using modern development practices
- Leverage AI coding assistants to accelerate development while maintaining strong engineering standards
- Support modernization and integration of existing applications as needed
Skills
- All applicants must currently reside in the United States
- 3+ years of software development experience, including hands-on backend and/or full-stack application development
- Ability to obtain and maintain a U.S. government security clearance
- Strong Python programming skills and experience developing REST APIs using FastAPI, Flask, or similar frameworks
- Experience developing modern web applications using JavaScript/TypeScript and React or comparable frontend technologies
- Working knowledge of SQL and relational databases such as PostgreSQL
- Practical experience developing or integrating LLM-powered applications, including RAG, AI agents, or LLM API integrations
- Familiarity with modern development tools, Git, Docker, testing, and debugging
- Ability to learn new frameworks quickly, solve complex technical problems, and independently deliver working software
- Experience with LangChain, LangGraph, LangChain4j, or similar AI application frameworks
- Experience with vector databases such as pgvector, Weaviate, or other semantic search technologies
- Familiarity with AI agent tool integration, Model Context Protocol (MCP), and agent orchestration
- Experience integrating multiple LLM providers such as OpenAI, Anthropic, or Ask Sage
- Experience with configurable platforms, workflow automation, or dynamic application interfaces
- Experience with PostgreSQL, Redis, Keycloak/OAuth, and enterprise authentication
- Experience with Dash/Plotly, Nx monorepos, or modernization of legacy applications
- Familiarity with CI/CD, containerization, and cloud-native deployment
- Experience developing software for government, defense, or other regulated environments
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