Senior Engineer, Software

Ensemble Health Partners•Richmond, VA

16d•Remote

About The Position

Ensemble Health Partners is one of the fastest-growing revenue cycle management companies in healthcare. Our Automation & AI Platform team builds the infrastructure that powers intelligent, bot-driven workflows across dozens of health system clients - from eligibility checks and claim scrubbing to prior-auth and remittance posting. We are looking for a senior engineer who think in systems, not just in code. You will be embedded in a high-ownership team building production-grade automation at the intersection of distributed systems, agentic AI, and healthcare data. You will own end-to-end delivery - from API design and infrastructure provisioning to operability and incident response - and be expected to move comfortably across a typed backend, a component-based frontend, and declarative cloud infrastructure. We care far more about how you reason about systems than which languages you have used. Our stack spans Python, TypeScript, Azure, Playwright, and a growing AI/agentic layer - strong engineers pick this up fast.

Requirements

10+ years of overall technology experience, with 6+ years designing and operating production distributed systems
Depth in service and API design: service boundaries, contracts and versioning, data modeling, and managing change across independently deployed components.
Strong command of event-driven and async architecture Message queues, idempotency, deduplication, retries, dead-lettering, backpressure, and eventual consistency - and the failure modes each introduces.
Polyglot fluency Productive in at least one modern backend language; comfortable owning changes in a web frontend; able to learn a new stack quickly rather than needing a specific one.
Hands-on cloud and infrastructure-as-code experience Identity-based service auth, RBAC, private networking, secrets management, containerized deployment, and CI/CD on a major cloud platform (Azure preferred).
Security-first instinct OAuth2/OIDC and token validation, least privilege, secret handling, and a practical sense of where sensitive data leaks.
Production operability as a default Structured logging, distributed tracing, and metrics. You own what you ship.
Pragmatism in ambiguous environments Ability to deliver value while two architectural paths coexist, driving convergence without blocking progress.

Nice To Haves

LLM agents and tool use: agentic loops, vision-grounded UI automation, or integrating AI models as components in a larger system (Claude / Computer Use especially relevant).
Browser or desktop automation at scale - and a hard-won sense of what makes it brittle vs. robust.
Model Context Protocol (MCP) or comparable tool/adapter abstractions.
Background in healthcare or another regulated-data domain - familiarity with HIPAA constraints, Epic/FHIR/Interconnect integration is a strong plus.
Experience deprecating a legacy system gracefully while its replacement runs in parallel.

Responsibilities

Design, build, and operate distributed services and automation pipelines that run in production at scale - owning the full lifecycle from architecture to on-call.
Drive architecture decisions on service boundaries, API contracts, data modeling, and change management across independently deployed components.
Build and extend our agentic automation layer - integrating LLMs and browser/desktop UI automation into robust, self-healing workflows.
Contribute to our cloud infrastructure: container deployments, managed identities, private networking, secrets management, and CI/CD pipelines on Azure.
Instrument everything you ship - structured logging, distributed traces, and metrics - and respond to production incidents with the same rigor you bring to feature work.
Work pragmatically in a codebase mid-migration: deliver value while two architectural paths coexist, and leave the system more converged than you found it.
Mentor engineers, participate in design reviews, and raise the bar for engineering quality across the team.