1. Data 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.

1. DataOps, MLOps & AI Operations

• Establish and scale enterprise-grade DataOps, 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.

1. Managed Services & Service Offering Development

• Design and scale enterprise Data & AI managed services offerings covering platform operations, application support, DataOps, 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.

1. Program Management & Delivery Governance

• Lead delivery execution across multiple Data & AI workstreams 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 & operational accountability.

1. 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.

1. 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.

1. Capability Building, Staffing & People Management

• Define the long-term capability model required for sustainable enterprise Data & AI operations.

• Lead workforce planning, staffing strategy, onboarding, capability development, and succession planning.

• Support recruitment and management of Data & AI delivery, operations, governance, engineering, AI, PMO, and support resources.

1. Communication & Executive Reporting

• Provide executive-level dashboards, operational updates, release readiness reports, risk registers, and performance reporting.

• Lead communication planning and change management activities supporting operational adoption and stakeholder engagement.

Desired Candidate Profile

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Information Systems, Business Administration, or a related field.

• 12+ years of experience in enterprise Data & AI delivery, platform operations, managed services, or digital transformation programs.

• Experience managing production critical enterprise platforms.

Technical Competencies

• Strong understanding of DataOps, MLOps, CI/CD, enterprise data platforms, data architecture, data governance, metadata, lineage, data quality, and analytics ecosystems.

• Experience operationalizing enterprise AI use cases in production environments.

• Strong understanding of AI/ML operationalization including model deployment, monitoring, retraining cycles, drift detection, inference operations, and AI governance controls.

• Familiarity with operational processes including testing governance, deployment pipelines, incident management, problem management, and service operations.

Leadership & Management Competencies

• Excellent executive stakeholder management, communication, negotiation, and leadership skills.

• Demonstrated experience leading multi-disciplinary teams across delivery, operations, AI, engineering, governance, and support functions.

• Ability to operate effectively in complex, multi-stakeholder, and multi-vendor environments.

Mandatory Requirements

• Proven experience leading enterprise scale DataOps, MLOps, AI operations, or Data & AI platform support organizations.

• Experience establishing managed services, operational governance models, and scalable support capabilities from inception.