Lead Software Engineer - Remote

UnitedHealth Group•Minnetonka, MN

10h•Remote

About The Position

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. We are seeking a Lead Software Engineer to join the Claims Preprocessing team. The role involves managing operational development and support, including application deployments, production support, and implementing machine learning solutions such as generative AI to improve Priority 1 application support. The position requires knowledge of both traditional software development life cycle methods and modern AI algorithms, proficiency in Java Full Stack, Kafka, React, Node.js, experience with the GenAI stack (including RAG and agents), expertise in AI evaluation tools and techniques, and an ongoing commitment to responsible use of AI within regulated healthcare environments. The ideal candidate brings strong domain expertise in claims preprocessing workflows, deep hands‑on engineering ability, architectural decision‑making capability, and a proven track record of reducing incidents, improving system SLAs, and driving measurable reliability advancements. 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

Bachelor’s degree in Computer Science, Engineering, or equivalent experience
12+ years of experience in SDLC, SRE, DevOps, or related engineering domains
3+ years of experience leading engineering or operations teams
Hands on experience architecting and implementing observability solutions (Open Telemetry, Splunk, Grafana, Prometheus)
Hands on experience applying AI/GenAI capabilities-such as RAG, agents, or ML driven anomaly detection-to improve observability, incident response, or operational workflows
Deep understanding of systems architecture, cloud infrastructure, networking, security, and automation
Solid proficiency with CI/CD tools such as GitHub Actions, Jenkins, or Azure DevOps
Proficiency with scripting or programming languages (Python, Bash, PowerShell) for automation and tooling
Proven expertise with public cloud platforms (preferably Azure) and experience supporting or driving on prem to cloud migrations

Nice To Haves

Experience with claims preprocessing workflows, regulatory SLAs, HIPAA aligned operational controls, and transactions including 837, 835, 277, and 271
Experience building custom telemetry pipelines or integrating AI/ML for anomaly detection
Leadership experience in globally distributed teams
Experience with IaC tools (Terraform, ARM/Bicep, Ansible)
Experience working in highly regulated or enterprise scale environments
Proven solid background in performance engineering, capacity planning, or large-scale distributed systems
Demonstrated success driving engineering excellence initiatives (DevSecOps, automated testing frameworks, SRE best practices)
Proven exposure to AI tools and their application in SRE workflows for faster delivery and smarter operations

Responsibilities

Lead and manage a high performing team of software engineers, providing coaching, mentorship, and fostering a collaborative culture
Partner with Product Owners and stakeholders to define scope, requirements, priorities, and delivery expectations
Develop and maintain project plans, technical roadmaps, and execution strategies for new features, enhancements, and platform initiatives
Oversee engineering activities end to end-from design and development through deployment, production operations, and continuous improvement
Drive Agile practices and ceremonies (PI planning, standups, backlog refinement, reviews) to ensure predictable, high quality delivery
Lead incident response, root cause analysis, and post mortems; implement corrective actions to improve reliability and reduce recurrence
Architect, evolve, and manage observability platforms using Open Telemetry, Splunk, Grafana, or similar tools
Build and maintain automation frameworks and tools to reduce manual work, improve consistency, and increase operational efficiency
Ensure engineering excellence through robust vulnerability management, automated testing, solid code quality standards, and performance monitoring
Partner with SREs, platform teams, and global engineering groups to align architecture, priorities, and delivery outcomes
Identify opportunities to improve system reliability, performance, scalability, and operational maturity, lead implementation of improvements
Leverage AI-powered tools and platforms to enhance observability, incident response, and operational efficiency
Support cloud modernization initiatives, including on-prem to cloud migration strategies and implementation