Lead AI Engineer
BigBear.ai2 years ago
USA (city not specified)Staff+
Responsibilities
- Define and lead architecture for generative AI solutions, including multi-agent workflows, retrieval-augmented generation, and LLM integrations.
- Design, build, and deploy multi-agent orchestration systems and custom Model Context Protocol servers connecting AI agents to enterprise and mission systems.
- Develop and optimize LLM applications using prompt engineering, dataset routing, and confidence gating.
- Engage government stakeholders to gather requirements, assess feasibility, and rapidly prototype mission-focused solutions.
- Design, develop, document, test, and debug full-stack applications across front-end, back-end, API, and data layers.
- Implement cloud-forward data environments and web/data pipelines for document ingestion, classification, and knowledge-domain routing.
- Build AI evaluation harnesses, perform citation verification and retrieval transparency work, and red-team systems for prompt injection and adversarial failure modes.
- Ensure deployed solutions meet security, compliance, performance, reliability, and mission requirements, including ATO and FedRAMP standards.
- Lead and mentor engineers, promote AI-first development practices, and support knowledge-sharing initiatives.
- Influence product roadmaps through field-discovered gaps and user feedback, coordinate installations, and monitor production performance.
Requirements
- Bachelor’s degree in computer science, software engineering, or a related field with 15 years of experience.
- Demonstrated experience leading engineering teams or serving as a technical lead on complex software initiatives.
- Hands-on experience designing and deploying generative AI or agentic AI systems in operational or production environments.
- Experience with multi-agent orchestration, RAG, prompt engineering, and LLM API integration.
- Proficiency in front-end and back-end development.
- Experience with Python, .NET/C#, Angular, TypeScript, Docker, AWS services, SQL Server, web/data pipelines, and Git-based CI/CD; equivalent technologies such as React, Java, PostgreSQL, or Azure are acceptable.
- Experience delivering software in secure, regulated environments, including ATO, FedRAMP, and security hardening.
- Strong analytical and problem-solving abilities and the ability to explain AI capabilities, limitations, and trade-offs to technical and non-technical stakeholders.
- Preferred experience includes building custom MCP servers, using AI-assisted development tools, and working with Helm/YAML, GitLab, Qlik, or Databricks.
- Preferred qualifications include experience with AI evaluation frameworks, adversarial LLM testing, data warehousing, ETL, business intelligence, and enterprise workflow integrations such as Power Automate custom connectors.
Tech Stack
Categories
About BigBear.ai
BigBear.ai develops AI-powered decision intelligence software, computer vision, and modeling/simulation tools for U.S. defense, intelligence, federal civilian, and critical-infrastructure markets. It sells software platforms and contract services, often deployed in secure government clouds, to support mission planning, logistics, and cybersecurity. Founded in 1988 and headquartered in McLean, Virginia, BigBear.ai is a public company listed on the NYSE under the ticker BBAI.