Senior AI Engineer - GenAI

About the role

Kraft Heinz is hiring a Senior AI Engineer in Bengaluru to build and deploy Generative AI features and models. The role covers data preparation, prompt engineering, agent and workflow building, testing and performance tuning, and works closely with AI architects, data scientists, data engineers and developers.

Key responsibilities

• Implement and deploy GenAI features and models, including data preparation, prompt engineering, agent and workflow building, testing and performance tuning, within established engineering patterns.
• Solve well-defined to moderately complex problems, escalating novel or architectural challenges to senior engineers.
• Contribute to GenAI components such as LLMs, RAG, agentic workflows and context engineering, and support their integration across data, models and applications.
• Support disciplined evaluation and error analysis of AI outputs to keep non-deterministic systems predictable and reliable.
• Debug, monitor and tune deployed solutions to meet quality, latency and cost expectations.
• Collaborate daily with AI engineers, architects, data scientists, data engineers, data architects, data stewards, developers and QA, working with the team lead and senior engineers and occasionally with product owners.
• Build tools and capabilities that generate value across the business, with indirect, advisory impact on outcomes.

Required profile

• Bachelor's degree in Computer Science, Engineering, Information Technology or a related field.
• 4-5 years of experience in AI/ML, data science or software engineering, with hands-on model development and some production deployment.
• Preferred: Microsoft Certified Azure AI Engineer Associate.
• Building GenAI features within a business unit or function (Data Science / IT).
• Dependable individual contributor who takes ownership of deliverables and is comfortable with bounded, well-defined problems.

Required skills

• Working expertise with LLMs, RAG, prompt and context engineering, and agentic workflows / frameworks (e.g., LangGraph), grounded in evals and error analysis.
• Familiarity building and deploying solutions on a major cloud platform, preferably Microsoft Azure.
• Solid programming skills (e.g., Python) and good software-engineering practices in coding, testing and integration.
• Familiarity with the modern data and AI stack (e.g., Azure AI / OpenAI services, Snowflake).
• Awareness of Responsible AI, security and privacy considerations.