About the job
In this critical engineering leadership role, you will be accountable for leading a global team of engineers who are accountable for the technology ecosystem running our UnitedHealthcare Medicare & Retirement business.
Responsibilities
Define and execute a multi year AI first modernization strategy aligned to the company's priorities, growth goals, and operating model
Lead the transformation of legacy platforms and applications toward AI enabled, cloud native, API driven architectures that improve speed, resilience, and cost efficiency
Manage multimillion dollar portfolios and deliver measurable cost savings. Own engineering investment portfolios and budgets, with accountability for ROI, sequencing trade offs, and value realization across modernization and AI initiatives
Champion an AI first engineering culture, where automation, intelligent workflows, code assist, and platform intelligence are embedded into how teams design, build, test, and operate software
Build, lead, and scale a high performing global engineering organization with a solid culture of accountability, continuous improvement, and inclusion, enabled by AI driven productivity and insights
Recruit, develop, and mentor senior engineering leaders capable of driving platform modernization and AI led delivery at scale
Oversee the modernization of consumer and enterprise platforms supporting millions of users, ensuring scalability, security, maintainability, and intelligent observability
Drive platform consolidation, rationalization, and reuse through shared services, common frameworks, reference architectures, and AI powered platform capabilities
Leverage AI to reduce technical debt, accelerate legacy remediation, improve testing and quality, and enhance developer experience
Ensure product performance, reliability, and uptime meet or exceed expectations for mission critical, public facing systems, using AI assisted monitoring, incident response, and resilience patterns
Influence and help establish enterprise engineering, AI, and platform standards to ensure reuse, interoperability, and regulatory consistency across domains
Establish AI as a foundational capability across the engineering ecosystem, from product features to internal platforms and operations
Lead integration of GenAI, ML, and advanced analytics into products and platforms to enable personalization, automation, insight generation, and decision support
Partner with Product, Data, and Analytics teams to ensure platforms enable AI driven, data informed user and operational experiences that deliver measurable value
Ensure responsible AI adoption, including governance, data ethics, explainability, model risk management, and compliance with healthcare regulations
Ensure platforms and applications are built and operated in compliance with HIPAA, HITRUST, SOC 2, and other applicable standards
Embed security, privacy, and responsible AI principles into architecture, tooling, and delivery practices ("secure and compliant by design")
Proactively identify and mitigate risks related to data integrity, patient safety, AI model behavior, operational resilience, and information security
Own execution across complex portfolios, including modernization roadmaps, budgets, sequencing, and capacity planning, with AI informing prioritization and trade offs
Drive cost optimization across cloud, tooling, and vendor ecosystems through architecture simplification, platform reuse, and AI enabled efficiency
Establish and track engineering health, modernization, and AI enablement KPIs, including developer productivity, time to value, platform reuse, and run cost reduction
Advance best in class practices across Agile delivery, DevOps, SRE, and AIOps, embedding automation and intelligence throughout the SDLC and AI-SDLC
Partner closely with Product, Clinical, Security, UX, and Executive leaders to ensure AI first modernization delivers clear business, operational, and patient outcomes
Serve as a strategic advisor and advocate for AI driven engineering transformation in enterprise planning, investment decisions, and change initiatives
Qualifications
Minimum
15+ years of software engineering experience, with 5+ years in senior engineering leadership roles
Proven track record modernizing large scale legacy platforms and establishing AI enabled, cloud native architectures
Experience delivering and operating enterprise and consumer grade systems at scale, supporting millions of users
Demonstrated success leading matrixed, globally distributed engineering teams
Deep expertise in cloud platforms (AWS, Azure, GCP), microservices, APIs, DevOps, application security, and modern SDLC and AI-SDLC practices
Hands on leadership integrating AI/ML and GenAI capabilities into production platforms and developer workflows
Exceptional communication, influence, and executive stakeholder management skills
Preferred
Product oriented engineering leader with solid focus on platform reuse, developer experience, and AI enabled productivity
Experience leading AI first transformation initiatives, including cloud migration, platform consolidation, and intelligent automation
Proven experience deploying GenAI at scale across both customer facing and internal engineering use cases
Experience in healthcare, digital health, financial services, or similarly regulated industries
Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field