Senior Healthcare Forward Deployed Engineer

Role

Lead forward-deployed pods embedded with health plans, PBMs, and payer operations to deliver AI programs that automate or augment administrative and clinical work. Own end-to-end program delivery including scoping, architecture, governance, adoption, team development, and executive strategy.

Key Responsibilities

• Lead and manage multiple concurrent workstreams across claims operations, utilization and care management, network/provider data, analytics, and actuarial stakeholders.
• Define program scope, desired outcomes, and success criteria; identify where AI can automate or augment payer workflows.
• Architect and govern technical solutions spanning multi-system integrations across core administrative, claims, and clinical platforms; produce clear diagrams and documentation for engineers, clinicians, and executives.
• Ensure solutions are safe, compliant, and fair with human oversight and PHI safeguards.
• Reimagine operating models for operations and clinical teams rather than simply automating existing processes.
• Shape interoperability approaches connecting plans, providers, and the broader ecosystem around claims and clinical data.
• Lead, coach, and develop engineers in the pod; set delivery standards, manage performance, and codify reusable methods, blueprints, and accelerators.
• Partner with client C-suite and health-plan leadership to build value architectures, ROI backlogs, use-case prioritization frameworks, and multi-year adoption roadmaps.

Qualifications

• Minimum of 8 years of hands-on engineering experience with cloud-native systems (APIs, microservices, containerization, serverless) and with AI platforms (examples cited: Claude, OpenAI, Vertex AI).
• At least 1 year designing and deploying agentic solutions in production (agents, orchestration, context engineering, RAG, workflows).
• Minimum 8 years coding in at least one general-purpose language (example: Python, Java).
• Minimum 8 years production deployment experience: CI/CD, infrastructure as code (Terraform, Helm), monitoring, and debugging with end-to-end delivery ownership in client-embedded environments.
• Minimum 3 years delivering AI or technology programs inside payer organizations and 3 years hands-on using Claude or equivalent frontier AI tools.
• Bachelor’s degree or equivalent experience (or Associate’s degree with additional work experience).

Technical Fundamentals

• Web fundamentals: HTTP/HTTPS, request/response lifecycle, REST APIs, JSON.
• API design and integration: authentication, pagination, rate limits, retries, versioning, webhooks, batch feeds; comfortable with FHIR and payer/clearinghouse APIs.
• Data fundamentals: relational and NoSQL databases, data modeling, SQL applied to claims, eligibility, and clinical data; data quality and lineage reasoning.
• Frontier AI: prompting, grounding responses in data (retrieval/RAG), structured outputs, tool use, evaluating quality, and designing for non-determinism and human oversight.
• Security and PHI handling: authentication vs authorization, token-based auth (OAuth/JWT), input validation, encryption in transit and at rest, least-privilege access, audit logging.
• System tradeoffs: caching, queues/background jobs, idempotency, synchronous vs asynchronous work.

Compensation & Benefits

• Location-specific annual salary ranges are provided for multiple U.S. states (examples include ranges such as $80,400 to $316,300 depending on state).
• Benefits include medical, dental, vision, life, long-term disability coverage, a 401(k) plan, bonus opportunities, paid holidays, and paid time off.

Other Notes

• Role may require travel (0–100% depending on business need and client requirements).
• Candidates must be able to work embedded with client organizations and comply with applicable work authorization requirements.