SR AI Context Engineer

GEHA Health; United States; Hybrid; USD 125,000 - 158,000; Full time

Benefits offered by this job

Competitive pay

Incentive plan

Health benefits

401(k)

Well-being program

Paid time off

Community enrichment time

Life and AD&D

Disability insurance

Tuition assistance

Job summary

G.E.H.A, Government Employees Health Association, Inc., is seeking a Senior AI Context Engineer in Digital Innovation to turn enterprise data into precise, high-quality context for AI tools. You will own extraction, chunking, vector indexing and RAG retrieval across HIPAA-compliant environments.

Working with the Sr. AI Solutions Architect and AI Full Stack Developers, you’ll design secure data enrichment, access controls and scalable context services to support GenAI features in a

Qualifications

• 5+ years of backend software engineering or data-centric development.
• 1–2 years optimizing AI/RAG architectures, prompt context strategies, and vector retrieval pipelines for LLM applications.

Responsibilities

• Extraction & Chunking: Build and refine parsing to contextual units for LLMs in partnership with cross-functional teams.
• Semantic Search & Reranking: Implement hybrid search, metadata routing, and reranking for precision.
• Agentic Context Services: Design context payloads for Model Context Protocol (MCP) servers and LLM orchestration tools.
• Index Design & Optimization: Implement vector indexing and embedding schemes in enterprise vector stores.
• Vector Metadata: Design tagging schemes for precise filtering and context retrieval.
• Retrieval Evaluation & Groundedness: Establish frameworks to monitor retrieval relevance and embedding drift.

Skills

Backend engineering

GenAI & RAG

Python

SQL

Security & privacy

Data-centric development

Tools

Airflow

Prefect

Temporal

LlamaIndex

Unstructured.io

LangChain

Pinecone

pgvector

Weaviate

Qdrant

Azure AI Search

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

• 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.
• 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.
• 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

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. Our diversity drives innovation deepens connections and strengthens our organization.

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.