Software Engineer - Backend Services

Truveta•Seattle, WA

4d•Hybrid

About The Position

Truveta is building a diverse and inclusive team to tackle complex health and technical challenges. We are seeking enthusiastic new graduates who are problem-solvers, collaborative teammates, and eager to make a difference in healthcare. If you’re excited about purposeful work, joining a mission-driven team, and launching your career in a supportive environment, Truveta could be the perfect place to start. 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 contribute to meaningful backend services and features 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, helping ensure 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.

Requirements

3+ years of software engineering experience, with hands-on experience building backend services, production systems, or platform infrastructure.
Contributed to the design, development, deployment, debugging, and operation of backend services in production, and you understand what it takes to keep services reliable after launch.
Strong Python backend engineering experience, including async programming, testing, packaging, API design, and maintainable service architecture.
Comfortable using modern Python tooling such as uv , ruff , and ty to build clean, reliable, and maintainable services.
Think beyond implementation and care about production operations, including observability, reliability, incident-aware development, debugging distributed systems, and deployment troubleshooting.
Build secure services by default, with experience in secure service design, secrets handling, token hygiene, dependency scanning, CVE triage, OWASP-aligned practices, and security patching within SLA.
Built or contributed to backend service integrations with LLM APIs such as OpenAI, Azure OpenAI, or equivalent, with attention to reliability, security, latency, error handling, and maintainability.
Practical exposure to agentic AI frameworks or interoperability protocols such as LangGraph, LangChain, MCP, or A2A, and understand 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; AKS and Azure Pipelines experience is preferred.
Understand the importance of responsible artifact and dependency management, with exposure to 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

Enthusiastic new graduates who are problem-solvers, collaborative teammates, and eager to make a difference in healthcare.
Excited about purposeful work, joining a mission-driven team, and launching your career in a supportive environment.
Motivated by purpose and enjoy building durable backend systems that support learning, decision-making, and discovery in healthcare.
AKS and Azure Pipelines experience is preferred.

Responsibilities

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.
Contribute to backend features and services end to end: Capable of taking well-scoped services and features from design through implementation, deployment, monitoring, 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, or contributing to integrations with, 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 configuration, deployment stage setup, 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, and security patching within SLA.
Manage artifacts and dependencies responsibly: Experienced with or exposed to artifact registry workflows such as JFrog, Docker/PyPI proxying, GPU artifact mirroring, package provenance, or similar dependency management practices.
Collaborate across boundaries: Partner effectively with platform, ML, application, data, and product engineers to transform concepts into scalable, reliable backend solutions.
Demonstrate strong engineering ownership: Own meaningful features or service components, contribute to technical design, raise code quality, support peers, and make pragmatic trade-offs that balance speed, quality, security, and reliability.
Act with purpose: Apply thoughtful engineering and security-first principles to create backend systems that advance healthcare intelligence responsibly and at scale.