Job description
Government Employees Health Association, Inc. (G.E.H.A) is a nonprofit member association that provides health and dental benefits that millions of federal employees and retirees, military retirees and their families have counted on since 1937. Offering one of the largest health and dental benefit provider networks available to federal employees in the United States, G.E.H.A empowers health and wellness by meeting its members where they are, when they need care.
G.E.H.A has one mission: To empower federal workers to be healthy and well.
As a Senior AI Context Engineer in Digital Innovation, you turn raw, structured and unstructured enterprise information—such as policy documents, brochures, and clinical records—into accurate, high-quality context for AI applications. Positioned at the intersection of applied data science and software engineering, you focus on the quality, semantic structuring, and retrieval accuracy of data consumed by G.E.H.A’s AI solutions. You own the extraction, document chunking, vector indexing, and RAG retrieval mechanics that power G.E.H.A’s AI tools.
Operating closely with the Sr. AI Solutions Architect, AI Full Stack Developer, and enterprise partners, you serve as the contextual bridge between the enterprise Data & Analytics, Digital Innovation and enterprise applications. In this role, you establish data enrichment, retrieval and evaluation frameworks that ensure AI agents have fast, secure, and compliant access to business context, all while leveraging enterprise cloud and data infrastructure.SKILLS
Duties and Responsibilities:
Context Engineering & Retrieval Optimization
Extraction & Chunking: Build and refine advanced structured and unstructured information parsing, layouts processing, and chunking workflows (converting PDFs, clinical notes, data, and policy docs) into high-quality contextual units for LLMs in partnership with cross-functional teams.
Semantic Search & Reranking: Implement hybrid search mechanics, metadata routing, and reranking logic to drastically improve retrieval precision and minimize model hallucinations.
Agentic Context Services: Design context payload specifications and metadata structures that feed into Model Context Protocol (MCP) servers and LLM orchestration tools built by application developers.
Vector Indexing & Retrieval Architecture
Index Design & Optimization: Recommends and implements vector indexing strategies, embedding schemes, and semantic query designs inside enterprise-provisioned vector stores (e.g., Pinecone, pgvector, Azure AI Search) to ensure high-performance, low-latency retrieval.
Vector Metadata: Design and manage sophisticated metadata tagging schemes to enable precise filtering, hybrid search, and domain-specific context retrieval.
Retrieval Evaluation & Groundedness: Establish automated evaluation frameworks to continuously monitor retrieval relevance, context quality, groundedness scores, and embedding drift over time.
Context Security, Compliance & Governance
Healthcare Context Compliance: Ensure all document processing and contextual payloads strictly adhere to HIPAA and HITRUST standards, implementing automated masking and tokenization for Protected Health Information (PHI).
Context-Level Access Control: Ensure role-based access control (RBAC) rules within vector metadata, ensuring AI search queries only return contextual snippets that the active user is authorized to see.
Auditing & Hand-off Lineage: Maintain context tracking and audit logs for prompt payloads, establishing clean data hand-off specifications when transitioning validated innovation prototypes to enterprise Data & Analytics or IT teams.
Collaborative Execution
Reference Pattern Alignment: Build upon the reference architectures, CI/CD templates, and "golden paths" established by the Sr. AI Solutions Architect.
Product Support: Work alongside the AI Product Owner and AI Full Stack Developers to rapidly supply high-accuracy context layers for upcoming GenAI features.
Knowledge, Skills, and Abilities:
Experience: 5+ years of experience in backend software engineering, applied machine learning/search, or data-centric application development.
GenAI & RAG Focus: 1–2 years of hands-on experience specifically optimizing AI and RAG architectures, prompt context strategies, and vector retrieval pipelines for LLM applications.
Programming & Tooling: Advanced proficiency in Python and SQL, alongside familiarity with modern orchestration tools (e.g., Airflow, Prefect, Temporal).
Unstructured Content Parsing: Deep experience using parsing frameworks (e.g., LlamaIndex, Unstructured.io, LangChain document loaders) to process complex layouts, tables, and unstructured documents.
Vector & Search Engines: Hands-on experience working with vector databases, embeddings, and semantic search platforms (e.g., Pinecone, pgvector, Weaviate, Qdrant, Azure AI Search).
Evaluation Frameworks: Familiarity with RAG and LLM context evaluation frameworks (e.g., Ragas, TruLens, Arize Phoenix) to measure retrieval recall, precision, and groundedness.
Data Security & Privacy: Practical experience handling sensitive healthcare data (PHI/PII) within high-compliance software environments.
Work-at-home requirements
Must have the ability to provide a non-cellular High Speed Internet Service such as Fiber, DSL, or cable Modems for a home office.
A minimum standard speed for optimal performance of 30x5 (30mpbs download x 5mpbs upload) is required.
Latency (ping) response time lower than 80 ms
Hotspots, satellite and wireless internet service is NOT allowed for this role.
A dedicated space lacking ongoing interruptions to protect member PHI / HIPAA information
How we value you
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
While this is a remote opportunity, at this time G.E.H.A does not hire employees from U.S. territories or the following states: Alaska, Hawaii, California, Washington, Oregon, Colorado, Wyoming, Montana, New York, Connecticut, Vermont, Pennsylvania, Maine.
Please note that the salary information is a general guideline only. G.E.H.A considers factors such as (but not limited to) scope and responsibilities of the position, candidate’s work experience, education/training, key skills, internal peer equity, as well as, market and business considerations when extending an offer.
The target hiring range for this position is $124,666 - $157,710 USD. At G.E.H.A, the current maximum salary for this role is $175,734 USD. While initial compensation may vary based on experience and qualifications, there is a path to work toward this top rate through performance and continued growth within the organization.G.E.H.A is an Equal Opportunity Employer, which means we will not discriminate against any individual based on sex, race, color, national origin, disability, religion, age, military status, genetic information, veteran status, pregnancy, marital status, gender identity, and sexual orientation, as well as all other characteristics and qualities protected by federal, state, or local law. G.E.H.A will not discriminate against employees or applicants because they have inquired about, discussed, or disclosed their compensation or the compensation of another employee or applicant. We are committed to creating an inclusive environment for all employees.
G.E.H.A is headquartered in Lee's Summit, Missouri, in the Kansas City area. We recognize the importance of balance and flexibility and offer hybrid and work-from-home options for many of our roles.
Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.