Note: The job is a remote job and is open to candidates in USA. Seneca Resources is a trusted staffing and consulting firm that partners with professionals to help them grow their careers. They are seeking an AI Engineer to build LLM and document-intelligence capabilities on a greenfield data and AI platform in a high-trust federal environment, focusing on hands-on development for product demonstration and knowledge transfer to internal teams.
Responsibilities
- 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
Skills
- 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
- 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)
Benefits
- Competitive pay
- Comprehensive health, dental, and vision coverage
- 401(k) retirement plans
- The support of a dedicated team who will advocate for you every step of the way
Company Overview