Project Role : Technology OpS Support Practitioner
Project Role Description : Own the integrity and governance of systems, including best practices for delivering services. Develop, deploy and support infrastructures, applications and technology initiatives from an architectural and operational perspective in conjunction with existing standards and methods of delivery.
Must have skills : AI Agents & Workflow Integration
Good to have skills : Value Engineering (VE), IT Infrastructure Operations
Minimum 12 year(s) of experience is required
Educational Qualification : 15 years full time education
Role Summary
Drives the design and adoption of AI driven operating models across IT Operations, shifting delivery from task execution to outcome oriented, Human + AI + Agent workforce models.
The role focuses on value engineering, responsible AI adoption, and operational transformation at scale, ensuring AI investments deliver measurable improvements in cost, quality, velocity, and resilience.
Acts as a bridge between business strategy, IT operations, and emerging AI capabilities, translating complex AI concepts into clear business outcomes and executable operating models.
Key Responsibilities
AI Driven Operating Model Design
- Design AI driven operating models aligned to business outcomes (cost, quality, velocity, resilience)
- Define tiered agent workforce models (fully autonomous, semi autonomous, co pilot)
- Establish clear boundaries for when and when not to use agents
- Identify human critical processes and safe automation boundaries across IT operations
Value Engineering & Business Outcomes
- Shift focus from automation activity to value streams and ROI beyond labor savings
- Identify high impact AI and agentic use cases improving reliability, speed, and experience
- Quantify and articulate AI value in business language for leadership stakeholders
- Apply value stream and lean thinking to AI enabled Run transformations
AI, GenAI & Agentic Literacy
- Apply strong understanding of LLMs, RAG, prompt and context engineering, and guardrails
- Guide teams on agentic concepts, autonomy levels, and orchestration patterns
- Maintain awareness of AI ecosystems and platforms (Azure, AWS, GCP, OpenAI, Anthropic)
- Embed Responsible AI principles, including risk assessment and control models
IT Operations Domain Leadership
- Leverage deep experience across ITSM, Infra & Cloud Ops, SRE, IT Security, and Workplace Services
- Identify operational touchpoints best suited for AI augmentation vs human control
- Ensure AI solutions integrate with, not bypass, existing IT governance and processes
Workforce Transformation & Adoption
- Lead workforce transformation from task execution to agent orchestration
- Support re skilling initiatives for human + AI collaboration
- Manage resistance to AI adoption through co creation and change leadership
- Act as a trusted advisor to delivery and operations leaders during transformation
Ecosystem & Vendor Strategy
- Evaluate AI platforms and vendors beyond demos and marketing claims
- Assess ecosystem offerings for fit, risk, scalability, and long term value
- Influence platform and tooling decisions through an operating model lens
Required Skills & Experience
Strategic & Business Skills
- Strong value engineering mindset with measurable outcome focus
- Ability to explain AI and operating model changes in business first language
- Experience influencing senior stakeholders without direct authority
AI & Agentic Expertise
- Solid understanding of GenAI, LLMs, RAG, prompt/context engineering, and guardrails
- Clear understanding of agentic architectures and autonomy trade offs
- Strong Responsible AI, risk assessment, and control awareness
IT Operations Depth
- Proven experience across ITSM, Infrastructure, Cloud Ops, SRE, and Security
- Ability to reason about operational risk, governance, and service continuity
- Experience identifying safe automation boundaries in complex Run environments
Change & Transformation Leadership
- Experience leading workforce transformation and re skilling initiatives
- Strong collaboration and co creation mindset
- Comfortable operating in ambiguous, evolving environments
Career Level Expectations CL7
- Shapes operating models and transformation outcomes across multiple teams
- Acts as a strategic force multiplier, not an individual contributor
- Influences how AI is adopted safely, responsibly, and at scale
- Balances innovation with operational stability and trust
Success Measures
- Clear AI driven operating models adopted by Run organizations
- Measurable improvements in cost, quality, velocity, and resilience
- Reduced resistance and increased confidence in AI adoption
- Strong alignment between AI strategy, operations, and business outcomes
- Resource needs to be AI Ready.
- AI Powered Tech Talent
