Lead Software Engineer - Remote

Job d:

Location:

Schaumburg, Illinois, United States Salary: $112,700 - $193,200/year

Job Area:
Technology Company:
United Health Group Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities.

Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

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.

Primary Responsibilities:

Lead design and delivery of modernized adjudication services, aligned to the program roadmap and target architecture

Responsible for upholding engineering best practices and implementing appropriate architectural designs to deliver safe and robust solutions

Build and enhance Java/Spring-based services and APIs supporting adjudication modernization initiatives

Decompose legacy capabilities into modular, testable, independently deployable components (where appropriate), improving maintainability and delivery velocity

Own end-to-end implementation for assigned modernization features: requirements clarification, technical design, build, test, release, and production support

Partner with product, architecture, and downstream platform teams to ensure modernized components integrate cleanly with existing claim processing flows

Implement robust observability (logs/metrics/traces), alerting, and SLO-focused engineering to improve reliability and operational readiness

Drive performance and scalability improvements for claim transaction workflows (latency, throughput, resiliency, failure isolation)
Establish and maintain technical documentation (designs, run-books, support procedures) for modernized services

Perform impact assessment and gap analysis from reverse engineering efforts

Drive cross-team technical coordination for delivery schedules, dependencies, and integration testing (internal and with partners/vendors, as applicable)
Provide technical guidance into stakeholder communications (engineering impacts, release readiness, implementation constraints, risks, mitigations) using approved internal guidance

Cloud, containers, and platform engineering (Azure + AWS)
Design, build, and operate cloud-native services on Azure and/or AWS, selecting appropriate managed services and patterns for reliability and cost Package and deploy applications using Docker and Kubernetes (K8s), applying secure configuration, resource tuning, and rollout strategies

Build/maintain CI/CD pipelines for automated build, test, security scanning, and deployment across environments

Improve infrastructure and deployment automation (IaC practices where used by the team), reducing manual steps and increasing repeatabilityAI engineering (prompt, agentic, harness) to accelerate delivery

Adoption of AI solutions in daily development workflow activities

Design and develop AI agents to automate/accelerate engineering and analysis tasks (e.g., code conversion, documentation, testing acceleration, migration support)
Apply AI prompt engineering and agentic AI patterns to create reliable task-oriented assistants with measurable outcomes

Be an AI champion within the team, encouraging and mentoring peers to leverage the power of AI to achieve solutions sooner

Build and maintain AI harness engineering capabilities (evaluation harnesses, regression suites, guardrails, telemetry) to ensure agent quality, safety, and repeatability

Integrate AI tooling into the developer workflow (CI hooks, PR checks, knowledge retrieval, standardized templates) to improve throughput and reduce defects

Establish operational controls for AI-enabled automation (access, logging, validation, fail-safes, human-in-the-loop where needed)
Quality, security, and operational excellence

Champion engineering best practices: clean code, design reviews, automated testing (unit/integration/contract), and secure-by-design implementation

Diagnose and resolve complex production issues; perform root-cause analysis and implement preventative fixes

Ensure…