AI Engineer
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Role details
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Job description
This role builds LLM and document-intelligence capabilities on a greenfield data and AI platform in a high-trust federal environment. Work is hands-on, scoped to a near-term product demonstration, and built to migrate - documented, portable, and transferred to the internal team. Engagement is 1 year with option to extend. Active T5/SSBI clearance required., * Develop RAG and document-processing pipelines on a cloud-based lakehouse platform (Databricks), including OCR, data ingestion, chunking, and retrieval.
- Build workflows for LLM-based summarization, information extraction, and evidence-grounded text generation with source attribution.
- Generate synthetic document corpora that capture fidelity and quality variation for meaningful analysis.
- Establish evaluation frameworks for retrieval accuracy, groundedness, hallucination checks, and structured output validation.
- Document processes, package deliverables, and track models and artifacts using tools like MLflow.
- Collaborate with internal teams to transfer knowledge and facilitate operational deployment.
Requirements
U.S. citizenship and active T5/SSBI federally adjudicated clearance required. [8]+ years building applied ML/AI or data systems, with demonstrated delivery of LLM and RAG systems you personally built - not notebook demos. Hands-on Databricks. Document processing at scale: OCR, layout-aware parsing, chunking tradeoffs, poor-quality source handling. Local/self-hosted LLM serving - vLLM, TGI, Ollama, llama.cpp, or equivalent - including running open-weight models in an isolated or air-gapped environment without reliance on external API endpoints. Structured extraction and grounded generation with source attribution. LLM evaluation methodology - you can explain how you measured correctness and what the evaluation missed. Privacy-preserving synthetic data generation from CUI, PII, or comparably restricted source data, with an understanding of re-identification risk. Strong Python. Government or defense contracting experience. Preferred Qualifications RAG built inside a government or FedRAMP-authorized environment (Azure OpenAI in GCC High, AWS GovCloud, Bedrock within an authorized boundary). Direct experience with FedRAMP Moderate, NIST 800-171, CMMC L2, or CUI handling. Databricks Vector Search, Mosaic AI Agent Framework and Agent Evaluation, Asset Bundles, MLflow. Unity Catalog governance. H2O (h2oGPTe, Driverless AI). Soft Skills Self-directed execution against a fixed milestone with minimal oversight. Honest reporting of model behavior - comfortable saying what an evaluation does and does not establish. Collaboration across technical and non-technical teams. Clear documentation and active knowledge transfer.
About the company
At Seneca Resources, we are more than just a staffing and consulting firm; we are a trusted career partner. With offices across the U.S. and clients ranging from Fortune 500 companies to government organizations, we provide opportunities that help professionals grow their careers while making an impact.
When you work with Seneca, you’re choosing a company that invests in your success, celebrates your achievements, and connects you to meaningful work with leading organizations nationwide. We take the time to understand your goals and match you with roles that align with your skills and career path. Our consultants and contractors enjoy competitive pay, comprehensive health, dental, and vision coverage, 401(k) retirement plans, and the support of a dedicated team who will advocate for you every step of the way.
Seneca Resources is proud to be an Equal Opportunity Employer, committed to fostering a diverse and inclusive workplace where all qualified individuals are encouraged to apply.
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