Overview

dunnhumby is the global leader in Customer Data Science, partnering with the world's most ambitious retailers and brands to put the customer at the heart of every decision.

Responsibilities

• Deliver secure, scalable AI and agentic solutions into production. Additionally if needed, you will lead a high-performing team of AI engineers.
• Run structured intake for new AI opportunities, working with Product, Commercial, Data Science and Engineering teams in India and the UK to clarify business problems, define scope and success metrics, and shape roadmaps.
• Architect and implement GenAI and agentic AI solutions on GCP, leveraging Vertex AI (models, endpoints, pipelines, vector search/RAG, Agent Builder) and core GCP services.
• Use Microsoft AI / Azure AI Foundry (or equivalent) and modern agent platforms to design and implement agentic workflows, tools and integrations with internal and external systems.
• Design AI agents and multi-step agentic workflows, including tool calling, MCP servers and agent-to-agent protocols, to automate and augment retail media and insight use cases.
• Ensure security, privacy and governance across AI solutions, including handling of sensitive data, access control, secrets management and safety/guardrail mechanisms.
• Define and embed DevOps/MLOps practices for AI (CI/CD for models, prompts and agents; infrastructure as code; environment promotion; blue/green and canary releases; incident response).
• Implement robust observability for AI systems: tracing prompts and tool calls, logging, metrics, dashboards and alerts to monitor quality, performance and cost.
• Establish AI testing and evaluation strategies: offline and online model evaluation, red-teaming, regression testing, and human-in-the-loop review and feedback loops.
• Act as a hands-on technical leader, reviewing designs and code, unblocking complex problems, and setting engineering standards and best practices for AI delivery.
• Coach, mentor and develop AI engineers, supporting their growth and ensuring a culture of learning, experimentation and continuous improvement.
• Strong experience in software/data/ML engineering, including significant hands-on work building and operating AI/ML or LLM-based solutions in production.
• Proven experience leading AI/ML/LLM engineering teams or acting as a senior technical lead, ideally in a global or distributed setup.
• Deep practical knowledge of GCP and Vertex AI, with experience designing and operating production workloads using Vertex AI models, endpoints, pipelines and RAG/vector search.

Qualifications

• Solid understanding of LLMs and foundation models (transformers, tokenization, context windows, embeddings, RAG, fine-tuning vs adapters vs prompts, tool calling and risks such as hallucinations or prompt injection).
• Hands-on experience designing and building AI agents or agentic workflows, integrating them with tools, APIs and internal systems, and managing their reliability, safety and observability.
• Strong background in security, governance and compliance for AI solutions, including handling of sensitive data, role-based access controls and auditability.
• Knowledge of AI evaluation techniques and model testing, including experiment design, quantitative and qualitative evaluation, and human-in-the-loop processes.
• Excellent communication and stakeholder management skills; able to collaborate effectively with teams in India and internationally, and to balance ambition, feasibility and risk.
• We won't just meet your expectations. We'll defy them. So, you'll enjoy the comprehensive rewards package you'd expect from a leading technology company. But also, a degree of personal flexibility you might not expect. Plus, thoughtful perks, like flexible working hours and your birthday off.
• You'll also benefit from an investment in cutting-edge technology that reflects our global ambition. But with a nimble, small business feel that gives you the freedom to play, experiment and learn.