Senior Software Engineer - Backend Services

Truveta•Seattle, WA

3d•$155,000 - $190,000•Hybrid

About The Position

Truveta is seeking a Senior Software Engineer to join their Intelligence Platform and Applications team. The role involves building backend services, platform foundations, and production systems for a next-generation healthcare intelligence platform. The engineer will design, build, deploy, and operate reliable, scalable, and secure services that transform health data into actionable intelligence. The position emphasizes backend systems, service architecture, APIs, infrastructure integrations, and operational foundations, with a focus on supporting AI-enabled healthcare workflows. The role offers an opportunity to own backend systems end-to-end, from design to maintenance, in a collaborative and fast-paced environment.

Requirements

5+ years of software engineering experience, with meaningful ownership of backend services, production systems, or platform infrastructure.
Experience designing, building, deploying, debugging, and operating backend services in production, with an understanding of keeping services reliable after launch.
Strong Python backend engineering experience, including async programming, testing, packaging, API design, and maintainable service architecture.
Comfort using modern Python tooling such as uv, ruff, and ty.
Understanding of production operations, including observability, reliability, incident-aware development, debugging distributed systems, and deployment troubleshooting.
Experience building secure services by default, including secure service design, secrets handling, token hygiene, dependency scanning, CVE triage, OWASP-aligned practices, and security patching within SLA.
Experience building backend service integrations with LLM APIs such as OpenAI, Azure OpenAI, or equivalent, with attention to reliability, security, latency, error handling, and maintainability.
Practical experience in agentic AI frameworks or interoperability protocols such as LangGraph, LangChain, MCP, or A2A, and understanding of how these patterns support tool orchestration, service integration, and AI workflow design.
Hands-on experience with cloud-native platform foundations such as Kubernetes, containers, CI/CD pipelines, and infrastructure-as-code tools such as Terraform.
Understanding of responsible artifact and dependency management, with experience using systems such as JFrog, Docker/PyPI proxying, GPU artifact mirroring, or similar workflows.
B.S. or M.S. in Computer Science, Engineering, Artificial Intelligence, or a related technical field, or equivalent practical experience.

Nice To Haves

AKS and Azure Pipelines experience is preferred.

Responsibilities

Design and build production-grade backend services, including service architecture, API design, async-first Python development, testing, packaging, debugging, and operating backend systems in production.
Own services end to end, from design through implementation, deployment, monitoring, incident response, and ongoing maintenance.
Engineer for scale, resilience, and maintainability, focusing on modular architecture, separation of concerns, code quality, observability, performance, and pragmatic design trade-offs.
Bring strong Python backend craftsmanship, including async programming, modern Python service patterns, well-tested code, and tools such as uv, ruff, and ty.
Support AI-enabled workflows through strong backend foundations, including integrating LLM APIs (e.g., OpenAI, Azure OpenAI) with attention to reliability, security, latency, error handling, and maintainability.
Understand modern AI service integration patterns, with practical exposure to agentic AI frameworks or interoperability protocols (e.g., LangGraph, LangChain, MCP, A2A).
Improve deployment and operational reliability by contributing to CI/CD template maintenance, deployment stage configuration, pipeline hardening, environment debugging, rollback strategy, and production readiness.
Build reliable cloud-native systems using Docker, devcontainers, Kubernetes, CI/CD pipelines, infrastructure-as-code patterns, AKS, Terraform/Terragrunt, and deployment automation.
Build secure services by default, with experience in dependency health, Snyk/CVE triage, library upgrades, token hygiene, OWASP-aligned practices, secrets handling, and security patching within SLA.
Manage artifacts and dependencies responsibly, with experience in artifact registry workflows (e.g., JFrog, Docker/PyPI proxying, GPU artifact mirroring).
Collaborate effectively with platform, ML, application, data, and product engineers to transform concepts into scalable, reliable backend solutions.
Demonstrate senior-level ownership by mentoring peers, raising engineering standards, improving operational practices, and making pragmatic trade-offs.
Apply thoughtful engineering and security-first principles to create backend systems that advance healthcare intelligence responsibly and at scale.