AI Engineering Manager

Job Description: You will join dunnhumby as an AI Engineering Manager, leading a team of AI engineers based in India to develop and maintain production-grade GenAI and agentic AI solutions that drive the global products and services of Tesco Media & Insight Platform. - Lead a team of AI engineers to deliver secure and scalable AI solutions for production. - Collaborate with Product, Commercial, Data Science, and Engineering teams to define business problems and shape roadmaps for new AI opportunities. - Architect and implement GenAI and agentic AI solutions on GCP using Vertex AI and other core GCP services. - Utilize Microsoft AI / Azure AI Foundry and modern agent platforms to design and implement agentic workflows and integrations. - Create AI agents and agentic workflows to automate and enhance retail media and insight use cases. - Ensure security, privacy, and governance in AI solutions by implementing access control, secrets management, and safety mechanisms. - Establish DevOps/MLOps practices for AI, including CI/CD, infrastructure as code, incident response, and environment promotion. - Implement observability for AI systems through tracing, logging, metrics, dashboards, and alerts. - Develop AI testing and evaluation strategies, including model evaluation, regression testing, and human-in-the-loop feedback loops. - Collaborate with Retail Media and Insight teams to deliver AI capabilities across the media lifecycle. Qualifications Required: - Experience in software/data/ML engineering with a focus on AI/ML solutions in production. - Leadership experience in AI/ML engineering or as a senior technical lead. - Proficiency in GCP and Vertex AI for designing and operating production workloads. - Familiarity with Microsoft AI / Azure AI Foundry and agentic AI frameworks. - Strong understanding of LLMs, foundation models, and agentic workflows. - Background in security, governance, and compliance for AI solutions. - Knowledge of DevOps/MLOps practices for AI and AI evaluation techniques. - Excellent communication and stakeholder management skills for collaboration on an international level. (Note: Any additional details of the company were not provided in the job description.) Job Description: You will join dunnhumby as an AI Engineering Manager, leading a team of AI engineers based in India to develop and maintain production-grade GenAI and agentic AI solutions that drive the global products and services of Tesco Media & Insight Platform. - Lead a team of AI engineers to deliver secure and scalable AI solutions for production. - Collaborate with Product, Commercial, Data Science, and Engineering teams to define business problems and shape roadmaps for new AI opportunities. - Architect and implement GenAI and agentic AI solutions on GCP using Vertex AI and other core GCP services. - Utilize Microsoft AI / Azure AI Foundry and modern agent platforms to design and implement agentic workflows and integrations. - Create AI agents and agentic workflows to automate and enhance retail media and insight use cases. - Ensure security, privacy, and governance in AI solutions by implementing access control, secrets management, and safety mechanisms. - Establish DevOps/MLOps practices for AI, including CI/CD, infrastructure as code, incident response, and environment promotion. - Implement observability for AI systems through tracing, logging, metrics, dashboards, and alerts. - Develop AI testing and evaluation strategies, including model evaluation, regression testing, and human-in-the-loop feedback loops. - Collaborate with Retail Media and Insight teams to deliver AI capabilities across the media lifecycle. Qualifications Required: - Experience in software/data/ML engineering with a focus on AI/ML solutions in production. - Leadership experience in AI/ML engineering or as a senior technical lead. - Proficiency in GCP and Vertex AI for designing and operating production workloads. - Familiarity with Microsoft AI / Azure AI Foundry and agentic AI frameworks. - Strong understanding of LLMs, foundation models, and agentic workflows. - Background in security, governance, and compliance for AI solutions. - Knowledge of DevOps/MLOps practices for AI and AI evaluation techniques. - Excellent communication and stakeholder management skills for collaboration on an international level. (Note: Any additional details of the company were not provided in the job description.)