Software Engineer-Remote

UnitedHealth Group•San Francisco, CA

5d•$72,800 - $130,000•Remote

About The Position

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. The ideal candidate has 5+ years of software engineering experience and a track record of building reliable enterprise services in Azure or a comparable cloud environment. 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

5+ 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
Experience designing and building microservices, including service decomposition, interface design, scalability, resilience, and operational support
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 with Docker and a working understanding of Kubernetes or managed container platforms
Experience implementing logging, monitoring, alerting, metrics, and distributed tracing for production services
Understanding of software 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 good problem-solving and root cause analysis skills, with the ability to troubleshoot across application, API, data, and cloud layers
Proven good communication and collaboration skills, with the ability to explain technical decisions, risks, dependencies, and delivery progress clearly

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

Responsibilities

Design, develop, test, deploy, and support backend applications, RESTful APIs, and microservices for the Identity Management rebuild and existing application
Build production-quality services using Python and modern API frameworks
Develop data-intensive application components and distributed processing workflows using PySpark and Azure Databricks and Azure Data Factory
Define clear API contracts, request and response models, error-handling standards, 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
Troubleshoot production issues, perform root cause analysis, improve service performance, and contribute to scalability and cost optimization
Use Git-based engineering practices, code reviews, branching strategies, automated builds, release controls, and infrastructure-aware deployment workflows
Use enterprise-approved AI tools and custom agents to accelerate coding, testing, documentation, debugging, monitoring, and operational support
Collaborate with product, data engineering, platform engineering, architecture, security, and application teams to deliver priorities and communicate risks, dependencies, and progress