Staff Software Engineer - Platform Architecture
- Compensation
- Not disclosed
- Location
- Remote
- Work setup
- Remote
- Seniority
- Staff
- Employment
- Contract
- Experience
- Not specified
- Category
- Software engineering
- Posted
Skills
Must have
- Deep expertise in large-scale distributed systems and scalable design. You've built and operated systems that handle high volume and real failure modes, and you're fluent in partitioning, back-pressur
- Strong event-driven architecture experience, hands-on with Kafka: topic and partition design, schema evolution and governance, consumer groups, idempotency, and the operational side of running it in p
- Strong API design across REST and GraphQL. We run a federated GraphQL gateway, so schema composition, versioning, and contract evolution matter here as much as clean endpoint design.
- 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). Deep AI architecture ownership sits w
- A well-rounded, hands-on engineer who goes deep in at least one strongly-typed language and moves comfortably across a polyglot stack. You have strong software-design instincts and care about clean in
- Sound data and storage instincts: data modeling, caching, query optimization, and how batch and streaming workloads (for example on Spark or Databricks) 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: how it works, where it breaks, and the trade-offs you made.
- Healthcare or FHIR experience is a strong plus and something you'll go deep in here. If you haven't worked in the domain yet, that's fine; it's learnable, and we'll help you get there.
Full description
Staff Software Engineer - Platform Architecture
Remote (US) · Full-time
Company Overview
b.well is solving healthcare’s fragmentation problem with our FHIR-based health data management platform. The platform connects data from EHRs, wearables, portals, and other sources, while our intelligence engine personalizes the consumer experience. By simplifying the complex healthcare ecosystem, we make it easy and convenient for consumers to engage and take action—whether it’s scheduling care, setting reminders, accessing health data, and more. For our clients, this means better health outcomes, operational efficiency, and stronger consumer engagement.
Position Overview
The Architecture team defines how that platform is designed and built. We set the patterns, contracts, and standards the rest of engineering builds on, run technical design reviews, and take on the hardest, most cross-cutting systems ourselves. We're hiring a Staff Software Engineer to own work like event-driven data integration on Kafka, large-scale distributed processing, and the API and federated GraphQL layer behind our SDKs — and to partner on making AI a dependable part of the platform.
This is a hands-on role. You design these systems, you build them, and you help operate them in production. You work horizontally across teams rather than inside a single product squad, so the patterns and services you create show up everywhere. The hard problems here are about scale, correctness, distributed-systems behavior, and the real-world messiness of healthcare data.
What you'll do:
- 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.