The role will act as the senior onsite engagement lead for the client, governing end-to-end delivery, operational readiness, release management, platform stability, AI operations, and managed services execution across multiple enterprise platforms.
The role is responsible for designing, launching, and scaling enterprise grade Data Ops, MLOps, AI operations, CI/CD, application support, and managed services capabilities from the ground up. This includes enabling governance frameworks, operational standards, release governance processes, service management models, operational KPIs, support structures, and scalable delivery capabilities.
In addition, the role plays a key leadership function in stakeholder management, capability development, business growth, and long-term service expansion. The successful candidate must demonstrate strong leadership across Data & AI delivery, production operations, organizational capability building, and executive stakeholder engagement within complex multi-vendor environments.
Responsibilities- 1. Enterprise Platform Delivery & Operations Leadership
- Own enterprise delivery and operational governance across multiple data platforms.
- Lead production readiness, hypercare governance, release management, operational acceptance, and transition into managed services.
- Govern enterprise platform lifecycle management including environment management, deployment governance, rollback planning, and operational stabilization.
- Ensure delivery alignment with strategic business objectives, roadmap priorities, operational timelines, and release schedules.
- Drive operational scalability, resiliency, observability, monitoring, and continuous service improvement initiatives.
- 2. Data Ops, MLOps & AI Operations
- Establish and scale enterprise-grade Data Ops, MLOps, CI/CD, and AI operations frameworks.
- Define operational standards for model deployment, monitoring, retraining coordination, drift management, inference operations, and AI governance controls.
- Govern AI operational readiness and support processes for enterprise AI use cases across multiple production platforms.
- Standardize release management, deployment automation, testing governance, and operational quality assurance processes.
- 3. Managed Services & Service Offering Development
- Design and scale enterprise Data & AI managed services offerings covering platform operations, application support, Data Ops, MLOps, and AI operations.
- Develop reusable operational frameworks, governance standards, support models, delivery playbooks, and service catalogs.
- Define L1/L2/L3 support operating models, escalation procedures, SLA structures, and operational KPIs.
- Drive continuous improvement initiatives to enhance service quality, operational maturity, and delivery efficiency.
- 4. Program Management & Delivery Governance
- Lead delivery execution across multiple Data & AI work streams including data engineering, analytics, governance, AI enablement, and operational support.
- Monitor delivery progress, operational risks, issues, dependencies, and readiness activities across all programs.
- Ensure compliance with enterprise standards, governance policies, cybersecurity requirements, and operational controls.
- Govern delivery reporting, performance tracking, financial oversight, and operational accountability.
- 5. Stakeholder Leadership & Client Engagement
- Act as the senior onsite engagement lead for Data & AI programs and operations.
- Build trusted relationships with executive stakeholders, sector leadership, technical teams, and implementation partners.
- Lead executive governance forums, steering committees, operational reviews, and strategic planning sessions.
- Drive alignment across business, architecture, operations, AI, infrastructure, and governance stakeholders.
- 6. Vendor & Multi-Partner Governance
- Govern multi-vendor delivery and operational coordination across implementation partners, cloud providers, platform vendors, and support teams.
- Manage dependencies, escalation management, operational coordination, and delivery alignment across all involved parties.
- 7. Capability Building, Staffing & People Management
- Define the long-term capability model required for sustainable…
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