Senior Manager, AI/ ML Software Engineering - MN On site

UnitedHealth Group•Minnetonka, MN

13d•$112,700 - $193,200•Hybrid

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 in making healthcare work better for everyone through people-led, responsible AI while Caring. Connecting. Growing together. As a Senior Manager of Software Engineering, you will lead the planning, execution, and delivery of strategic technology initiatives across healthcare, Payment Integrity, AI, and enterprise platform domains. Based onsite in Minnesota, you will partner directly with Product Owners, Business Leaders, Architecture, Operations, and Engineering teams to define roadmaps, establish execution governance, and drive end-to-end software delivery. You will manage globally distributed engineering teams, championing innovative technology capabilities including AI/ML, Generative AI, intelligent automation, and cloud architecture to deliver scalable, secure, high-quality enterprise solutions that improve operational effectiveness and business outcomes. 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, Information Systems, or a related technical field, or 4+ years of equivalent software engineering experience
10+ years of software engineering or technology delivery experience
5+ years of experience leading software engineering teams and large-scale technical initiatives
Experience managing globally distributed onshore and offshore engineering teams
Experience leading the end-to-end delivery and operationalization of AI/ML or Generative AI capabilities within enterprise applications
Experience with cloud platforms (e.g., Azure), enterprise data services, APIs, microservices, and modern programming technologies (e.g., Python, Java, or .NET)
Demonstrated experience utilizing AI-enabled productivity tools (e.g., Copilot, ChatGPT) to optimize engineering team outputs
Proven track record of partnering directly with business stakeholders, product management, and executive leadership

Nice To Haves

Experience delivering healthcare, healthcare payer, claims processing, or Payment Integrity platforms
Experience implementing AI/GenAI solutions within healthcare or regulated enterprise environments
Experience with intelligent document processing, OCR, workflow automation, or document orchestration platforms
Knowledge of healthcare interoperability standards including FHIR, HL7, CCD, and X12
Technical familiarity with containerization platforms (e.g., Kubernetes/AKS), event-driven architectures, and CI/CD infrastructure automation
Proven track record of leading cloud modernization, platform transformation, and engineering excellence initiatives at scale

Responsibilities

Lead the planning, execution, and delivery of strategic software engineering and technology initiatives across healthcare, Payment Integrity, AI, and enterprise platform domains
Partner with Product Owners, Business Leaders, Architecture, Operations, and onshore and offshore Engineering teams to define product roadmaps, technical priorities, and execution plans aligned with business objectives
Manage, mentor, and coach globally distributed onshore and offshore engineering teams, fostering accountability, continuous learning, collaboration, and high-performance delivery
Drive the adoption and operationalization of AI/ML, Generative AI, intelligent automation, and data-driven solutions to improve business outcomes and operational effectiveness
Integrate enterprise AI capabilities into team workflows, establish AI growth goals in developer development plans, and align hiring strategies with evolving technology competencies
Champion the ethical use of technology by embedding transparency, fairness, security, and Responsible AI governance throughout the software development lifecycle
Promote the effective use of AI-enabled developer productivity tools (such as Microsoft Copilot, GitHub Copilot, and ChatGPT) to improve delivery speed, engineering practices, and code quality
Establish and monitor key delivery metrics, OKRs, operational KPIs, and program health indicators to provide visibility and decision support to executive leadership
Drive continuous improvement across DevOps, CI/CD automation, release management, site reliability engineering, and production operations