Senior Software Engineer - Backend Services

Senior Software Engineer - Backend Services  Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values . This position is based out of our headquarters in the Greater Seattle area.  #LI-hybrid Who We Need   Join Truveta’s Intelligence Platform and Applications team to build the backend services, platform foundations, and production systems that power the next generation of healthcare intelligence. Guided by Truveta’s mission of Saving Lives with Data, you’ll help engineer reliable, scalable, and secure services that transform complex health data into actionable intelligence for clinicians, researchers, and healthcare organizations. We are seeking a Senior Software Engineer with deep backend service engineering experience, strong production ownership, and cloud-native platform discipline. You’ll design, build, deploy, and operate services that are reliable, observable, maintainable, and secure at scale. Your work will support AI-enabled healthcare workflows, but the emphasis is on building backend systems, service architecture, APIs, infrastructure integrations, and operational foundations that make those workflows dependable in production. You’ll help shape the core service and platform capabilities that make healthcare intelligence systems scalable, resilient, and trustworthy, driving real-world progress across research, care delivery, operations, and patient outcomes. This Opportunity   Patients, doctors, and medical researchers deserve technology that is reliable, secure, and capable of turning health data into meaningful insight. As part of the Intelligence Platform and Applications team, you’ll use your expertise in backend engineering, distributed systems, cloud-native infrastructure, and production operations to build the robust service layer that intelligent healthcare applications depend on. This is an opportunity to own backend systems end to end: from service design and API development to deployment, debugging, observability, reliability, and security. You’ll work across platform, application, data, and AI-enabled workflows, ensuring that services are well-architected, operationally sound, and built for long-term maintainability. If you’re motivated by purpose and enjoy building durable backend systems that support learning, decision-making, and discovery in healthcare, you’ll find this an inspiring place to grow. You’ll work in an ambitious, fast-paced, collaborative environment where every contribution helps make healthcare more connected, intelligent, and impactful.   We are seeking backend engineers who: Design and build production-grade backend services: Experienced in service architecture, API design, async-first Python development, testing, packaging, debugging, and operating backend systems in production. Own services end to end: Capable of taking services and features from design through implementation, deployment, monitoring, incident response, and ongoing maintenance. Engineer for scale, resilience, and maintainability: Grounded in modular architecture, separation of concerns, code quality, observability, performance, and pragmatic design trade-offs. Bring strong Python backend craftsmanship: Experienced with async programming, modern Python service patterns, well-tested code, and tools such as uv , ruff , and ty to deliver reliable, maintainable systems. Support AI-enabled workflows through strong backend foundations: Experienced integrating LLM APIs such as OpenAI, Azure OpenAI, or equivalent into backend services, with attention to reliability, security, latency, error handling, and maintainability. Understand modern AI service integration patterns: Practical exposure to agentic AI frameworks or interoperability protocols such as LangGraph, LangChain, MCP, or A2A, and an understanding of how these patterns support tool orchestration, service integration, and AI workflow design. Improve deployment and operational reliability: Able to contribute to CI/CD template maintenance, deployment stage configuration, pipeline hardening, environment debugging, rollback strategy, and production readiness. Build reliable cloud-native systems: Hands-on with Docker, devcontainers, Kubernetes, CI/CD pipelines, infrastructure-as-code patterns, AKS, Terraform/Terragrunt, and deployment automation. Build secure services by default: Experienced with dependency health, Snyk/CVE triage, library upgrades, token hygiene, OWASP-aligned practices, secrets handling, an