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Senior Director AI/ML Engineering

Reads like a Data Leadership role: running a data team.

Gurgaon, Haryana

Pay
Pay not listed
Work setting
Not stated
Employment
Not stated
Apply at UnitedHealth Group

What you’ll bring

All qualifications

Core experience

  • Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, Mathematics, or a related technical field
  • 15+ years of technology and software engineering experience, including at least 8-10 years of leadership experience managing engineering organizations
  • Experience leading enterprise-scale AI platforms, MLOps, AI governance frameworks, model deployment, observability, and production operations
  • Experience developing senior leaders, driving organizational transformation, managing talent strategies, workforce planning, succession planning, and building high-performing engineering cultures
  • Experience translating business strategy into technology roadmaps and investment priorities
  • Experience establishing and operating AI governance frameworks, Responsible AI practices, model risk management processes, security controls, compliance requirements, and audit readiness

Preferred experience

  • Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering Management, or Business Administration
  • Solid knowledge of Azure AI services, APIs, distributed systems, and platform engineering
Qualification wording
Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, Mathematics, or a related technical field
15+ years of technology and software engineering experience, including at least 8-10 years of leadership experience managing engineering organizations
Experience leading enterprise-scale AI platforms, MLOps, AI governance frameworks, model deployment, observability, and production operations
Experience developing senior leaders, driving organizational transformation, managing talent strategies, workforce planning, succession planning, and building high-performing engineering cultures
Experience translating business strategy into technology roadmaps and investment priorities
Experience establishing and operating AI governance frameworks, Responsible AI practices, model risk management processes, security controls, compliance requirements, and audit readiness
Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering Management, or Business Administration
Solid knowledge of Azure AI services, APIs, distributed systems, and platform engineering
Education & alternatives
Required Qualifications: - Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, Mathematics, or a related technical field - 15+ years of technology and software engineering experience, including at least 8-10 years of leadership experience managing engineering organizations
Preferred Qualifications: - Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering Management, or Business Administration - Ph.D. in AI, Machine Learning, Computer Science, or a related discipline is advantageous for highly specialized AI leadership roles
- Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering Management, or Business Administration - Ph.D. in AI, Machine Learning, Computer Science, or a related discipline is advantageous for highly specialized AI leadership roles - Industry certifications such as Microsoft Azure AI Engineer, Azure Solutions Architect, AWS Machine Learning Specialty, Google Professional Machine Learning Engineer, SAFe Agilist, PMP, TOGAF, Certified Scrum Professional, or other AI, cloud, architecture, and leadership certifications

Tools in this posting

  • AWS
  • Azure
Source — Tool mentions in context
- Ph.D. in AI, Machine Learning, Computer Science, or a related discipline is advantageous for highly specialized AI leadership roles - Industry certifications such as Microsoft Azure AI Engineer, Azure Solutions Architect, AWS Machine Learning Specialty, Google Professional Machine Learning Engineer, SAFe Agilist, PMP, TOGAF, Certified Scrum Professional, or other AI, cloud, architecture, and leadership certifications - Solid knowledge of Azure AI services, APIs, distributed systems, and platform engineering
- Industry certifications such as Microsoft Azure AI Engineer, Azure Solutions Architect, AWS Machine Learning Specialty, Google Professional Machine Learning Engineer, SAFe Agilist, PMP, TOGAF, Certified Scrum Professional, or other AI, cloud, architecture, and leadership certifications - Solid knowledge of Azure AI services, APIs, distributed systems, and platform engineering Key Competencies

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Actively hiringFirst seen by us 7 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 22, 2026 · 7 days ago
Recorded sightings
53
Last seen by us
Oct 29, 2026

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Job description

View original posting ↗

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.

 

An SG31 Senior Director, AI/ML Engineering is a senior technology executive responsible for leading enterprise AI initiatives from strategy through execution and value realization. The role provides leadership for AI engineering organizations and serves as the accountable owner for AI platforms, intelligent automation capabilities, machine learning solutions, and emerging AI technologies that support business transformation. The position focuses on delivering measurable business outcomes through AI while ensuring scalability, reliability, security, and governance.

 

The Senior Director is responsible for setting the technical and business direction for AI programs, establishing multi-year roadmaps, prioritizing investments, and aligning technology execution with organizational goals. They work closely with business leaders, product teams, operations partners, architecture groups, and executive leadership to identify opportunities where AI can improve efficiency, reduce cost, enhance customer experiences, and create new capabilities. Success is measured not only by technology delivery but also by adoption, operational impact, productivity gains, and financial value creation.

 

As a people leader, the role oversees a team of engineering leaders, AI engineers, machine learning engineers, data scientists, and platform specialists distributed across onshore and offshore locations. Responsibilities include organizational design, talent strategy, workforce planning, hiring, performance management, leadership development, and succession planning. The Senior Director creates an environment of innovation, accountability, continuous learning, and engineering excellence while building a solid leadership bench capable of scaling enterprise AI capabilities.

 

From a technology perspective, this leader owns the end-to-end lifecycle of AI solutions, including platform architecture, model deployment, intelligent agents, automation frameworks, cloud infrastructure, production operations, observability, and reliability engineering. The role ensures that AI capabilities are developed as reusable enterprise assets rather than isolated solutions, enabling faster adoption and greater return on investment across multiple business domains.

 

The position carries significant accountability for Responsible AI, compliance, security, and risk management. The Senior Director ensures that all AI solutions comply with governance requirements, regulatory obligations, ethical AI principles, privacy standards, and operational controls. They establish processes for model monitoring, performance measurement, incident management, human oversight, and continuous improvement to maintain trust and reliability at enterprise scale.

 

The role requires solid executive presence and the ability to influence senior leaders across the organization. The Senior Director regularly communicates strategy, progress, risks, investment needs, and business outcomes to executives while building alignment across diverse stakeholder groups. They act as the bridge between technology and business organizations, ensuring that AI investments are translated into meaningful operational and financial results.

 

Ultimately, an SG31 Senior Director, AI/ML Engineering is expected to provide broad organizational leadership, own enterprise-scale AI platforms and programs, drive adoption and value realization, build high-performing teams, ensure governance and operational excellence, and serve as the accountable leader for delivering transformative AI capabilities that advance the organization's strategic objectives.

 

Primary Responsibility:

  • Comply with all applicable Company policies, procedures, and business directives, changes including those relating to work location, team assignments, work schedules, and flexible work arrangements

Required Qualifications:

  • Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, Mathematics, or a related technical field
  • 15+ years of technology and software engineering experience, including at least 8-10 years of leadership experience managing engineering organizations
  • Experience leading enterprise-scale AI platforms, MLOps, AI governance frameworks, model deployment, observability, and production operations
  • Experience developing senior leaders, driving organizational transformation, managing talent strategies, workforce planning, succession planning, and building high-performing engineering cultures
  • Experience translating business strategy into technology roadmaps and investment priorities
  • Experience establishing and operating AI governance frameworks, Responsible AI practices, model risk management processes, security controls, compliance requirements, and audit readiness
  • Experience partnering with CIOs, business executives, product leaders, operations leaders, and external partners
  • Solid understanding of financial management, budgeting, business case development, operational metrics, and technology investment governance.
  • Deep understanding of Artificial Intelligence, Machine Learning, Large Language Models (LLMs), Agentic AI, Natural Language Processing, Generative AI, intelligent automation, cloud platforms, and modern software engineering practices
  • Proven track record of building and scaling enterprise AI/ML solutions, leading large engineering teams, and delivering measurable business outcomes through AI, automation, and digital transformation initiatives
  • Demonstrated success leading multi-functional teams across onshore and offshore locations
  • Exceptional communication, influencing, and stakeholder management skills
  • Proven ability to manage complex portfolios, prioritize competing demands, drive value realization, and communicate effectively with executive leadership
  • Demonstrated ability to present strategy, roadmap, business value, risks, and recommendations to senior leadership and executive committees
  • Demonstrated ability to inspire teams while maintaining solid accountability for execution and results
  • Demonstrated ability to balance innovation with enterprise governance, regulatory obligations, privacy requirements, and operational risk management

 

Preferred Qualifications:

  • Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering Management, or Business Administration
  • Ph.D. in AI, Machine Learning, Computer Science, or a related discipline is advantageous for highly specialized AI leadership roles
  • Industry certifications such as Microsoft Azure AI Engineer, Azure Solutions Architect, AWS Machine Learning Specialty, Google Professional Machine Learning Engineer, SAFe Agilist, PMP, TOGAF, Certified Scrum Professional, or other AI, cloud, architecture, and leadership certifications
  • Solid knowledge of Azure AI services, APIs, distributed systems, and platform engineering

 

Key Competencies

Strategic thinking, enterprise leadership, AI innovation, platform ownership, product mindset, organizational design, talent development, executive communication, stakeholder influence, financial stewardship, operational excellence, governance leadership, and business outcome accountability.

 

Ideal SG31 Profile

An executive-level AI leader who can build and scale enterprise AI platforms, lead large engineering organizations, influence senior leadership, govern AI responsibly, and deliver measurable business value through adoption, automation, productivity improvements, cost savings, and transformational AI capabilities.

 

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

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Location & working pattern

Gurgaon, Haryana

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