AI Engineer

Location: McLean, VAEligibility: Must be a U.S. Person (required for access to an ITAR / export-controlledenvironment)About the RoleWe are hiring a Senior AI / LLM Engineer to design and build LLM-powered features andapplications across a range of use cases. You will work hands-on across the modern AIengineering stack — retrieval, integration, evaluation, and production hardening — and takeownership of significant pieces of the system from design through deployment. Retrieval-augmented generation over large, real-world enterprise data is a prominent part of the work,alongside platform integration and LLM-driven analysis. You will set technical direction withinyour area, make sound trade-offs under ambiguity, and help raise the bar for engineers aroundyou.What You’ll Do• Own the design and delivery of LLM-powered features end-to-end — from problemframing and architecture through production deployment and iteration.• Build and tune retrieval-augmented generation (RAG) pipelines over large, heterogeneousenterprise data — ingestion, chunking, embeddings, indexing, and entity/relationshipmodeling — with a focus on retrieval accuracy and closing coverage gaps.• Design and build data ingestion and indexing pipelines that reliably capture content, mapidentities across systems, and support incremental/resumable sync at scale.• Integrate LLMs (via managed platforms such as Amazon Bedrock) for question answering,analysis, and other tasks, preserving sessions, sources, and citations.• Integrate with enterprise platforms and collaboration tools through their APIs, includingSSO/OAuth flows and event-driven bot/app patterns.• Design permission-bounded access and correct attribution in multi-user contexts, so thesystem never surfaces data a user could not already access.• Establish evaluation practices for retrieval quality and answer correctness, and use themto drive iteration and catch regressions.• Add observability, logging, and audit trails, and lead debugging of quality and performanceissues in production.• Guide and mentor other engineers through design and code reviews, and contribute toshared standards.Required Qualifications• 6–8 years of software engineering experience, with at least 2 years building with LLMs orapplied ML in production.• Strong proficiency in Python (or comparable) and strong engineering fundamentals —testing, version control, clean and maintainable code.• Deep hands-on experience with RAG systems: embeddings, vector databases,chunking/indexing, and a strong track record diagnosing and improving retrieval quality.• Experience designing and building data ingestion/ETL pipelines over large, messy, real-world datasets.• Strong experience integrating third-party APIs into backend services, includingauthentication flows (OAuth/SSO) and webhook/event-driven patterns.• Hands-on experience with LLM APIs (e.g., Anthropic, OpenAI, or similar) andorchestration frameworks.• Experience building and relying on evaluations for model and retrieval outputs.• Experience with knowledge graphs or entity-relationship modeling for retrieval.• Experience building multi-user or multi-tenant systems with scoped permissions and auditrequirements.• Familiarity with observability and tracing for LLM or data pipelines.• A rigorous approach to data access, permissions, and handling sensitive information.• Experience taking systems to production on a major cloud platform (AWS preferred), anda track record of owning features independently.Preferred Qualifications• Experience with Amazon Bedrock or other managed LLM platforms.• Experience integrating with enterprise collaboration platforms (chat, wikis, ticketing) viatheir APIs.• MLOps exposure: Docker, CI/CD, production service deployment.• Bachelor’s or advanced degree in Computer Science, Engineering, or a related field — orequivalent practical experience.

Department: Artificial Intelligence (AI)
Experience: 7-10
Posted: 2026-08-18T08:56:11.457Z