Staff Software Engineer - Platform Architecture

b.well Connected Health is addressing the fragmentation problem in healthcare with their FHIR-based health data management platform. They are seeking a Staff Software Engineer to design and build large-scale distributed systems, own API architecture, and partner on AI integration, while mentoring other engineers and ensuring the platform's coherence.

Responsibilities:

• Design and build event-driven distributed systems on Kafka: orchestrator and worker services, schema and contract governance (AsyncAPI, CloudEvents), idempotent consumers, sagas and event choreography, and config-driven pipelines that onboard new data sources without code changes
• Own API architecture at scale across REST and a federated GraphQL gateway (WunderGraph Cosmo) that powers our SDKs, including schema composition, versioning, contract evolution, and FHIR conformance
• Partner on AI architecture and enablement: help make LLMs and agents dependable parts of the system (retrieval, evaluation, guardrails, and clear boundaries around protected health data), working alongside the dedicated Applied AI Engineering lead who owns that area
• Shape FHIR and health-data architecture: terminology services, resource modeling, clinical quality measurement (DQM and CQL), high-volume document storage, and query performance across MongoDB and ClickHouse
• Help run the technical design review process and document the decisions and standards, so significant designs are reviewed against consistent criteria and the platform stays coherent as it grows
• Stay close to the code and to production: write real software, build proofs of concept that prove out a pattern before teams adopt it, and use observability and operational data to confirm decisions hold up and to debug incidents when they don't
• Mentor senior engineers and tech leads on distributed-systems thinking, system design, and the trade-offs behind good architecture

Requirements:

• Deep expertise in large-scale distributed systems and scalable design
• Strong event-driven architecture experience, hands-on with Kafka
• Strong API design across REST and GraphQL
• A well-rounded, hands-on engineer who goes deep in at least one strongly-typed language and moves comfortably across a polyglot stack
• Sound data and storage instincts: data modeling, caching, query optimization, and how batch and streaming workloads fit together with operational systems
• Cloud-native and security fundamentals: Kubernetes and AWS, identity and auth (OIDC, token exchange), and multi-tenant isolation in a regulated environment that handles protected health data
• You can walk someone through a system you've designed and operated end to end
• Exposure to AI as a component of a system is a plus — LLMs or agents and the practical concerns around them (retrieval, evaluation, guardrails, cost and latency)
• Healthcare or FHIR experience is a strong plus and something you'll go deep in here