VP AI ML Engineering (Secunderabad)

UnitedHealth Group; Hyderabad; On-site; INR 6,000,000 - 12,000,000; Full time

Job summary

Optum, a part of UnitedHealth Group, seeks a Vice President of AI Engineering to shape the strategic direction for Enterprise AI Architecture, Engineering Delivery, Solution Strategy, and Product Management. This executive will lead a multidisciplinary team to build and scale AI capabilities, driving adoption and measurable business value across the enterprise.

The role bridges enterprise strategy, product leadership, and technical execution, collaborating with business and technology leaders to

Responsibilities

• Define and execute the enterprise AI strategy and multi year roadmap, leveraging Generative AI, LLMs, multimodal AI, data platforms, and cloud technologies to drive innovation, adoption, and measurable business outcomes
• Own and scale AI solution architectures that enable intelligent automation across corporate functions, focusing on reuse, interoperability, security, and maintainability
• Lead engineering organizations delivering enterprise AI platforms, establishing DevOps, MLOps, and LLMOps practices for reliable, scalable delivery

Job description

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.

The Vice President, AI Engineering, sets the strategic direction for Enterprise AI Architecture, Engineering Delivery, Solution Strategy, and Product Management. This role serves as a strategic technology leader responsible for building, accelerating, governing, and scaling the delivery of the enterprise AI portfolio.

The role encompasses defining the enterprise AI technology strategy, deploying scalable AI capabilities, and advancing AI adoption across key business functions to enable an AI-first enterprise. We are seeking an accomplished leader to build and guide a high-performing organization committed not only to delivering AI-powered solutions, but also to establishing reusable AI platforms, driving enterprise adoption, and creating measurable business value through responsible AI innovation.

This position oversees a multidisciplinary organization of AI engineers, solution architects, product leaders, and delivery professionals responsible for designing, architecting, implementing, and scaling enterprise AI capabilities across the UHG ecosystem.

The role bridges enterprise strategy, product management, stakeholder engagement, and technical execution. Working closely with business and technology leaders, this executive will translate business priorities into scalable AI capabilities that improve operational efficiency, employee experience, and organizational effectiveness. Success in this role requires deep technical expertise, executive leadership, business acumen, and a passion for building enterprise capabilities that enable long-term transformation.

Primary Responsibilities

Enterprise AI Strategy

• Define and execute the enterprise AI strategy and multi year roadmap, leveraging advancements in Generative AI, LLMs, multimodal AI, Agentic AI, data platforms, and cloud technologies to drive innovation, adoption, and measurable business outcomes
• Lead the evolution of Enterprise AI across strategy, architecture, engineering, product management, platform capabilities, research, and value realization to deliver sustained enterprise impact
• Own a portfolio of enterprise AI capabilities spanning internally developed solutions and strategic platforms such as Microsoft Copilot, Google AgentSpace, and emerging AI technologies
• Establish and scale the AI operating model, governance, and delivery frameworks that enable responsible, secure, and efficient adoption of AI across the enterprise
• Partner across Enterprise AI, Digital, Data, Infrastructure, Security, and Architecture organizations to drive strategic alignment, platform interoperability, technology standards, and capability reuse
• Champion enterprise-wide AI transformation by identifying high-value opportunities, accelerating adoption, and embedding AI-powered products, copilots, intelligent workflows, and agent-based systems into business operations
• Lead world-class AI engineering capabilities, with expertise in data engineering, analytics, modern data platforms, and enterprise-scale AI delivery to ensure operational excellence and business value realization

Corporate Systems Solution Strategy & Architecture

• Reimagine and drive enterprise AI solution strategy that enables intelligent automation and transforms business operations across corporate functions
• Translate business and technology roadmaps into scalable AI-enabled solutions that accelerate enterprise transformation
• Influence business and technology partners to modernize enterprise platforms into AI-ready architectures while maximizing the value of AI capabilities embedded within enterprise software platforms
• Drive innovation by defining scalable solution architectures that emphasize reuse, interoperability, security, and long-term maintainability
• Partner with enterprise architecture, engineering, and product organizations to ensure solution designs align with enterprise standards and strategic priorities
• Develop reusable reference architectures, design patterns, and integration frameworks that accelerate delivery across multiple business domains

Technical Delivery Leadership

• Lead engineering organizations responsible for delivering enterprise AI platforms and AI-powered business capabilities across the enterprise
• Establish engineering excellence through contemporary AI engineering practices, including DevOps, MLOps, and LLMOps, leveraging CI/CD, scalable architecture, Infrastructure as Code, containerization, observability