Senior Software Engineer

UnitedHealth Group•San Francisco, CA

7h•$91,700 - $163,700•Remote

About The Position

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care’s most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together. This role supports the Identity Management rebuild initiative and ongoing support for the existing application. The Software Engineer will design, build, test, deploy, and operate scalable APIs, microservices, and data-intensive backend services. The role retains a solid foundation in Python and PySpark while expanding into API development, cloud-native application engineering, automation, observability, and secure software delivery. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

Requirements

7+ years of hands-on software engineering experience building and operating enterprise applications, backend services, APIs, or microservices
5+ years of hands-on experience with Python, including object-oriented programming, modular design, exception handling, packaging, automation, and maintainable coding practices
3+ years of hands-on experience developing RESTful APIs and working with API specifications, validation, authentication, versioning, and documentation
3+ years of hands-on experience with PySpark for distributed processing, transformation, data validation, and performance tuning
2+ years of working experience with Azure Databricks or similar distributed data platforms for data-intensive application use cases
2+ years of working experience with relational and NoSQL databases, data modeling, SQL, transaction patterns, and application-level data access
2+ years of Advanced experience designing and building microservices, including service decomposition, interface design, scalability, resilience, and operational support

Nice To Haves

Experience with event-driven architecture and messaging technologies such as Kafka, Azure Event Hubs, Azure Service Bus, or comparable platforms
Experience supporting performance testing, capacity planning, secure software development lifecycle practices, and cloud cost optimization
Experience building identity management, identity resolution, consumer profile, member/customer identity, or entity-resolution applications
Hands-on experience with Azure Data Factory and data pipeline orchestration
Hands-on experience building or supporting custom AI agents for coding, testing, documentation, validation, monitoring, incident triage, or workflow automation
Healthcare, insurance, consumer profile, or enterprise identity data experience
Knowledge of caching, API gateways, load balancing, rate limiting, asynchronous programming, and high-availability design
Experience with automated testing frameworks such as pytest and unit, integration, API, and regression testing practices
Git experience, including pull requests, code reviews, branching strategies, CI/CD fundamentals, release management, and production support
Experience implementing logging, monitoring, alerting, metrics, and distributed tracing for production services
Strong knowledge of software architecture, design principles, common design patterns, clean code, code quality, and maintainable architecture
Basic working understanding of cloud security, identity and access management, data privacy, governance, and enterprise compliance concepts
Proven advanced problem-solving and root cause analysis skills, with the ability to troubleshoot complex issues across application, API, data, and cloud layers
Proven leadership, communication, and collaboration skills, with the ability to influence technical decisions, mentor engineers, and explain risks, dependencies, tradeoffs, and delivery progress clearly
Demonstrate baseline proficiency with enterprise-approved AI tools such as GitHub Copilot, Microsoft 365 Copilot, Databricks Genie, and other approved GenAI platforms, where applicable
Apply AI tools responsibly to improve coding, code review, test creation, technical documentation, debugging, analysis, monitoring, and delivery quality
Use or support custom agents for software development, automated testing, API validation, failure detection, incident triage, runbook execution, and operational reporting
Follow enterprise guidance for responsible AI use, data protection, human review, security, and software quality

Responsibilities

Lead the design, development, testing, deployment, and support of backend applications, RESTful APIs, and microservices for the Identity Management rebuild and existing application
Design and build production-quality services using Python and modern API frameworks, establishing reusable patterns and engineering standards
Architect and develop data-intensive application components and distributed processing workflows using PySpark, Azure Databricks, and Azure Data Factory
Own API design standards, including contracts, request and response models, error handling, versioning strategies, and service documentation using OpenAPI or Swagger
Implement resilient microservice patterns, including service-to-service communication, retries, timeouts, idempotency, asynchronous processing, and graceful failure handling
Create automated unit, integration, API, regression, and performance tests; integrate quality checks into CI/CD pipelines
Implement application logging, metrics, tracing, alerting, and dashboards to improve observability, incident response, and operational reliability
Apply secure coding practices, authentication and authorization controls, secrets management, encryption, and privacy-by-design principles
Lead troubleshooting of complex production issues, perform root cause analysis, improve service performance, and drive scalability, reliability, and cost optimization
Champion Git-based engineering practices, lead code and design reviews, and strengthen branching, automated build, release control, and infrastructure-aware deployment workflows
Use enterprise-approved AI tools and custom agents to accelerate coding, testing, documentation, debugging, monitoring, and operational support
Partner with product, data engineering, platform engineering, architecture, security, and application teams to shape technical direction, deliver priorities, and communicate risks, dependencies, tradeoffs, and progress
Provide technical leadership through architecture reviews, design guidance, code reviews, and mentoring of software engineers
Identify technical debt, define modernization priorities, and drive continuous improvement in engineering quality, reliability, and delivery practices