Senior AI Context Engineer

🕒 July 29

🐻 Alaska, California, +11 more states – Remote

🐻 Alaska – Remote 🏄 California – Remote ⛰️ Colorado – Remote 🦌 Connecticut – Remote 🌺 Hawaii – Remote 🦞 Maine – Remote 🦬 Montana – Remote 🗽 New York – Remote 🌲 Oregon – Remote 🔔 Pennsylvania – Remote 🍁 Vermont – Remote ☕ Washington – Remote 🦬 Wyoming – Remote

💵 $124.7k - $157.7k / year

⏰ Full Time

🟠 Senior

🤖 Artificial Intelligence

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GEHA Health

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1937

🏥 Healthcare

🛡️ Insurance

⚕️ Healthcare Insurance

Healthcare • Insurance • Healthcare Insurance

GEHA Health is a large benefits association dedicated to serving federal employees, retirees, and their families. Founded by postal workers in 1937, GEHA offers a comprehensive range of health and dental plans, including FEHB and PSHB options, as well as additional benefits such as gym memberships, vision benefits, and wellness rewards. With a network of 1. 7 million providers nationwide and extensive prescription drug coverage, GEHA prioritizes reinvesting profits to enhance member experiences and support federal workforce health. Their plans include Medicare Advantage options and a robust telehealth offering, ensuring their members receive the best possible care and coverage.

📋 Description

• Turn raw, structured and unstructured enterprise information—such as policy documents, brochures, and clinical records—into accurate, high-quality context for AI applications • Focus on the quality, semantic structuring, and retrieval accuracy of data consumed by G.E.H.A’s AI solutions • Own the extraction, document chunking, vector indexing, and RAG retrieval mechanics that power G.E.H.A’s AI tools • Establish data enrichment, retrieval, and evaluation frameworks that ensure AI agents have fast, secure, and compliant access to business context

🎯 Requirements

• 5+ years of experience in backend software engineering, applied machine learning/search, or data-centric application development • 1–2 years of hands-on experience specifically optimizing AI and RAG architectures, prompt context strategies, and vector retrieval pipelines for LLM applications • Advanced proficiency in Python and SQL • Familiarity with modern orchestration tools (e.g., Airflow, Prefect, Temporal) • Deep experience using parsing frameworks (e.g., LlamaIndex, Unstructured.io, LangChain document loaders) • Hands-on experience working with vector databases, embeddings, and semantic search platforms (e.g., Pinecone, pgvector, Weaviate, Qdrant, Azure AI Search) • Familiarity with RAG and LLM context evaluation frameworks (e.g., Ragas, TruLens, Arize Phoenix) • Practical experience handling sensitive healthcare data (PHI/PII) within high-compliance software environments

🏖️ Benefits

• Competitive pay/salary ranges • Incentive plan • Health/Vision/Dental benefits effective day one • 401(k) retirement plan: company match – dollar for dollar up to 4% employee contribution (pretax or Roth options) plus a 6% annual company contribution • Robust employee well-being program • Paid Time Off • Personal Community Enrichment Time • Company-provided Basic Life and AD&D • Company-provided Short-Term & Long-Term Disability • Tuition Assistance Program