Head of Engineering AI and Data Science
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Summary
Executive leadership role in Bengaluru heading AI & Data Science engineering: defining an enterprise-wide AI platform strategy, building and scaling teams, and shipping agentic/GenAI features (LLMs, RAG, vector search) into customer-facing products using Python, ML frameworks and major clouds.
- 15+ years in software engineering, building enterprise platforms and scalable applications, including significant leadership experience and a track record of building and scaling teams. Ideally, this includes experience setting up a team in a new location.
- Experience defining a platform strategy for AI adoption across a large organisation and leading the change needed to adopt it.
- Proven people management experience, including hiring, coaching and performance management.
- Proven experience turning AI and Data Science functionality into platforms and reusable solutions with product and business impact, rather than as a research or modelling discipline in isolation.
- Experience shipping agentic AI features inside a commercial, customer facing product, rather than in internal analytics tooling.
- Generative AI and Agentic AI experience, with practical depth in AI agents, agentic workflows, large language models, vector databases, Retrieval-Augmented Generation (RAG) and natural language processing techniques that power search and discovery.
- Strong engineering foundations in applying Machine Learning and deep learning within products, with practical credibility in Python, SQL and at least one major ML framework, such as TensorFlow, PyTorch or scikit-learn.
- Working depth in at least one major cloud platform, such as Azure, AWS or GCP, and modern AI Ops practices.
- Strong stakeholder management and executive communication skills. Comfortable working across global time zones and functions.
- A collaborative approach that puts the team first, with a track record of building trust across Engineering, Product, Research and Commercial functions.