Job Description

KRAFT HEINZ

Data, AI & Digital Innovation — India GCC

Group Lead, AI/ML Engineering

Location

Bangalore, India (India GCC)

Function

Data, AI & Digital Innovation — AI Engineering, ML Engineering & MLOps

Reports To

Jyoti Radhu — Director, Data, AI & Digital Innovation, GCC India

Key Partners

GenAI & ML leadership in Chicago and Toronto; offshore consulting partners

Role Summary

We are looking for a Group Lead to lead AI Engineering, ML Engineering, and MLOps from our India GCC in Bangalore. This leader will build and mentor the engineering team, establish the delivery framework, and own delivery of AI/ML solution and Platform .

How This Role Fits the Operating Model

1. Manage GCC deliverables across AI Engineering and ML Engineering. Single point of ownership for what the India GCC delivers across both disciplines — planning, execution, quality, and timelines.

2. 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.

3. Partner with 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.

Key Responsibilities

• Lead AI Engineering, ML Engineering & MLOps from the GCC: own applied delivery of 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 — 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 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.

Required Qualifications

• Hands-on experience delivering 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.
• Experience with agentic/LLM application development (LangGraph or comparable frameworks) and strong production-quality Python.
• Proven people leadership: hiring, mentoring, and growing engineers; comfortable operating in a forward-deployed model alongside business teams.
• Experience setting up delivery frameworks, SLAs, or operating processes for an engineering team.
• Experience managing vendors or consulting partners and holding them accountable for quality.
• Clear communicator, comfortable working across time zones with global leadership and non-technical stakeholders.

Preferred Qualifications

• Experience in a GCC/captive-center or hub-and-spoke operating model.
• CPG, retail, or other large-enterprise background.

Location(s)

Kraft Heinz is an Equal Opportunity Employer – Underrepresented Ethnic Minority Groups/Women/Veterans/Individuals with Disabilities/Sexual Orientation/Gender Identity and other protected classes.