Platform Architect (Healthcare solution)

Intellias is building a next-generation healthcare data platform designed to connect healthcare providers, applications, devices, and digital services into a unified ecosystem. The platform integrates data from EHR systems, patient portals, digital health applications, wearables, and additional healthcare sources using modern interoperability standards and cloud-native technologies.

Must Have:

• 8+ years of software engineering experience
• Strong hands-on backend development experience in Python and/or other modern backend languages
• Proven experience designing and operating large-scale distributed systems
• Strong experience with event-driven architectures and Apache Kafka
• Deep understanding of distributed systems concepts including eventual consistency, partitioning, idempotency, back-pressure, failure recovery, and consistency vs availability trade-offs
• Experience designing and evolving REST APIs and GraphQL architectures
• Strong experience with AWS and Kubernetes
• Expertise in cloud-native architectures and production operations
• Strong data architecture and data modeling experience
• Experience with modern data platforms such as MongoDB, ClickHouse, Spark, Databricks
• Good understanding of OAuth, OIDC, token exchange, authorization, and multi-tenancy
• Strong communication and technical leadership skills
• Professional English for collaboration with US-based stakeholders

Nice to Have:

• FHIR, HL7, EHR integrations
• Healthcare interoperability experience
• Experience working with PHI/PII and regulated environments
• HIPAA-related architectural knowledge
• Experience with Java/Spring Boot
• Experience with TypeScript/Node.js
• Experience with Apollo Federation, WunderGraph Cosmo or similar solutions
• Experience integrating AI/LLM capabilities into production platforms
• Experience with AI-assisted engineering tools like GitHub Copilot, Cursor, Claude Code
• Previous Staff or Principal Engineer experience
• Experience building internal developer platforms and reusable engineering frameworks

• Design and build large-scale distributed systems and platform services
• Drive architecture and implementation of event-driven systems using Kafka
• Define scalable patterns for asynchronous processing, orchestration, and messaging
• Design and evolve REST and federated GraphQL architectures
• Establish standards for API governance, schema evolution, versioning, and service integration
• Build reusable platform components and reference implementations
• Contribute directly to production code and technical prototypes
• Design healthcare data architecture supporting FHIR-based interoperability
• Define patterns for security, identity, authorization, and multi-tenancy
• Drive architecture reviews and technical decision-making across teams
• Use observability and production telemetry to improve platform reliability
• Collaborate with engineering, product, data, AI, and security stakeholders
• Mentor senior engineers and technical leads

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