AI Engineer

Role Summary
This contract AI Engineer role involves developing advanced language models and document intelligence capabilities within a high-trust federal environment. The position requires hands-on work on a greenfield data and AI platform, focusing on building scalable, secure, and reliable AI solutions. The engineer will contribute to a near-term product demonstration, with scope for knowledge transfer and future internal team ownership, operating on a one-year contract with an option to extend.

Responsibilities

• Develop retrieval-augmented generation (RAG) and document-processing pipelines utilizing Databricks lakehouse ingestion, OCR, chunking, embedding, and retrieval methods.
• Build large language model (LLM) workflows for summarization, structured data extraction, and evidence-grounded text generation with source attribution.
• Generate synthetic document corpora that meet fidelity and quality variation criteria for meaningful AI outputs.
• Establish evaluation frameworks to assess retrieval quality, grounding, hallucination rates, and structured output validity, including human-in-the-loop review processes.
• Package deliverables as jobs and asset bundles, track progress using MLflow, and maintain comprehensive documentation for internal team ownership.
• Implement privacy-preserving synthetic data generation techniques for sensitive or restricted data sources, understanding re-identification risks.
• Ensure secure local deployment of open-weight LLMs (such as TGI, Ollama, llama.cpp) in isolated or air-gapped environments.
• Collaborate with cross-functional teams to integrate AI solutions within the federal environment, adhering to security and compliance standards.
• Monitor and report model performance metrics, providing clear, actionable insights for evaluation and improvement.

Qualifications

• This position requires eligibility for a U.S. Government security clearance. In accordance with federal law, U.S. citizenship is required. (Active T5/SSBI federally adjudicated security clearance).
• Minimum of 8 years of experience in building applied ML/AI or data systems, with demonstrated delivery of personal LLM and RAG systems beyond notebook prototypes.
• Extensive hands-on experience with Databricks platform, including development, deployment, and management.
• Proven expertise in processing data at scale, including OCR, parsing of mixed-quality sources, and handling poor source quality.
• Practical knowledge of local/self-hosted LLM serving environments such as vLLM, TGI, Ollama, llama.cpp, or similar.
• Strong background in structured data extraction, grounded generation with source attribution, and model evaluation methodologies.
• Experience generating privacy-preserving synthetic data from sensitive sources, with awareness of re-identification risks.
• Proficiency in Python programming and related data science tools.
• Prior experience working within government or defense contracting environments.

Publishing Pay Range: $80.00 – $84.00 hourly
This is a fully remote role and can be performed from any approved location within the United States.