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hirist

Head - AI Centre Of Excellence

Enterprise Hiring Solutions
15 - 20 Years
rupee80 L-1 Cr PA
Mumbai

Posted on: 29/09/2026

Job Description

The Mandate :

- Build and lead the company's AI Centre of Excellence (AI-COE) from the ground up - defining its structure, talent mix, operating model, and roadmap.

- Drive a company-wide digital transformation agenda across product, operations, customer experience, and internal workflows.

- Establish Master Data Management (MDM) as the foundation - ensuring data quality and governance that AI can reliably run on.

- Integrate AI into the core product suite : warehouse management, sales forecasting, pricing, demand sensing, and route optimization.

- Serve as the primary bridge between the India GCC and US headquarters - ensuring the GCC's engineering and AI talent is productively deployed against the transformation agenda.

- Own the vendor and partnership landscape for AI/ML tooling, cloud infrastructure, and data platforms.

- Present to the Warburg Pincus board on AI progress, investment ROI, and competitive differentiation.

Key Responsibilities :

AI-COE Leadership :

- Design the COE charter : governance model, ways of working, engagement model with product/engineering teams.

- Recruit and develop a team of ML engineers, data scientists, AI product managers, and platform architects.

- Define and communicate the AI vision internally and externally - to customers, investors, and talent.

Digital Transformation :

- Audit the current technology estate and identify digital debt, automation opportunities, and AI insertion points.

- Drive ERP modernisation, workflow automation, and intelligent process redesign across operations.

- Partner with product leadership to embed AI into existing and next-generation offerings.

Data Strategy & MDM :

- Establish an enterprise-wide data governance framework - ownership, quality standards, lineage, and access controls.

- Build the foundational data infrastructure (data warehouse / lakehouse) that supports AI/ML model training and deployment.

- Drive data democratisation : self-serve analytics for customers and internal stakeholders alike.

GCC Integration :

- Collaborate with the India MD to define the GCC's AI and engineering remit.

- Build a high-performing distributed team model that leverages India talent for AI development, data engineering, and platform build.

- Ensure time-zone-aware delivery rhythms and knowledge continuity between GCC and HQ.

Stakeholder & Commercial :

- Act as a thought leader with top customers - translating the AI roadmap into tangible business outcomes.

- Partner with sales and product teams on AI-powered differentiation in competitive deals and renewals.

- Manage AI investment portfolio - build vs. buy vs. partner decisions with a clear ROI lens.

Ideal Candidate Profile :

Experience :

- 15 - 20 years in technology leadership, with the last 5+ years in roles that blend AI/data strategy with operational transformation.

- Deep experience in PE-backed or high-growth software/SaaS environments - understands the velocity and accountability that comes with PE ownership.

- Hands-on background in building AI/ML platforms - not just sponsoring them. Has personally owned model development, MLOps, and production deployment.

- Experience standing up or scaling a GCC / offshore delivery model is strongly preferred.

- Beverage, FMCG, distribution, or supply chain domain exposure is a plus - but secondary to transformation track record.

Technical Depth :

- Fluent in modern data stack : cloud data platforms (Snowflake, Databricks, BigQuery), orchestration, and ML tooling.

- Strong understanding of LLM integration, GenAI application patterns, and responsible AI principles.

- MDM and data governance - has built or overhauled enterprise data foundations.

- API-first architecture thinking; comfortable with microservices, event-driven systems, and SaaS product design.

Leadership & Influence :

- A builder mentality - energised by standing up new capabilities, not maintaining existing ones.

- Able to operate from boardroom to sprint planning - equally fluent with PE investors and engineering squads.

- Strong commercial instinct : ties every AI initiative back to customer value and revenue impact.

- Track record of recruiting and retaining top AI/data talent in competitive markets.

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