Overview

Data, AI & Digital Innovation — India GCC

Responsibilities

• Manage GCC deliverables across Data Science, AI Engineering and ML Engineering. Single point of ownership for what the India GCC delivers across disciplines — ideation, experimentation, planning, execution, quality, and timelines.
• Ensure AI & ML platform stability with GCC engineers and consulting partners. Keep the enterprise AI/ML platform stable and reliable, using a combined workforce of GCC engineers and offshore consulting partners — with clear accountability regardless of who does the work.
• Partner with Data Science, AI Engineering and ML Engineering leadership in North America. Operate as the GCC counterpart to leadership in Chicago and Toronto — aligned on priorities, patterns, and standards, with a regular operating rhythm in both directions.
• Lead Data Science, AI Engineering, ML Engineering & MLOps from the GCC: own applied delivery of data science, AI and ML solutions built on the approved enterprise stack (Azure ML, Azure OpenAI Service, Snowflake Cortex, Copilot Studio).
• Lead Forward-Deployed Engineering (FDE) for GenAI delivery: run the FDE model — data scientists and engineers embedded directly with business teams to turn their problems into working GenAI solutions — owning how FDEs are assigned, how they engage, and the quality of what they ship.
• Mentor and grow the team: hire, coach, and develop data scientists, AI/ML engineers in Bangalore; set the technical bar and build future leads.
• Create the delivery framework: define how work moves from intake to production — standards for scoping, code quality, CI/CD, testing, evaluation, and release — so delivery is repeatable and predictable.
• Manage delivery: own commitments on scope, dates, quality, and cost; track progress, surface risks early, and course-correct visibly.
• Ensure the ML Platform and its SLAs: keep the enterprise AI/ML platform and pipelines reliable — MLOps, CI/CD, monitoring, incident response, cost management — and define, enforce, and report against SLAs for availability, support response, and delivery turnaround.
• Liaise with consulting partners: manage offshore consulting partners — onboarding, work allocation, quality review, and accountability for their deliverables.

Qualifications

• Hands-on experience delivering Data science, GenAI and ML solutions to production, ideally on Azure (Azure ML, Azure OpenAI Service, AKS, Azure DevOps).
• Strong MLOps background: containerization, CI/CD, deployment, monitoring, and reliability for ML/LLM systems.
• Proven people leadership: hiring, mentoring, and growing data scientists and engineers; comfortable operating in a forward-deployed model alongside business teams.
• Clear communicator, comfortable working across time zones with global leadership and non-technical stakeholders.
• CPG, retail, or other large-enterprise background.
• Location(s)
• Bengaluru - Brookfield GCC
• Kraft Heinz is an Equal Opportunity Employer – Underrepresented Ethnic Minority Groups/Women/Veterans/Individuals with Disabilities/Sexual Orientation/Gender Identity and other protected classes.