AI Technical Delivery Manager

Role purpose: Lead end-to-end delivery of AI/ML and Generative AI solutions by coordinating business stakeholders, data teams, AI engineers, developers, vendors, and operations teams. Key responsibilities: Own the end-to-end delivery of AI projects from requirements through production.

Translate business problems into clear AI use cases, requirements, and delivery plans . Manage project scope, timelines, budget, resources, risks, dependencies, and quality. Coordinate data scientists, ML engineers, software engineers, data engineers, architects, and business teams .

Manage delivery of GenAI, LLM, machine-learning, automation, and AI-agent solutions . Establish project milestones, KPIs, acceptance criteria, and success metrics. Ensure AI solutions are properly tested, validated, secured, and production-ready .

Work with architecture, cybersecurity, legal, risk, and compliance teams on responsible AI and governance . Manage vendors and third-party AI/cloud technology providers where applicable. Oversee deployment, monitoring, model performance, incident management, and continuous improvement.

Drive user adoption and change management after implementation. Provide regular status reports and communicate risks, issues, and decisions to senior management. Identify opportunities to scale successful AI solutions across the organization.

Typical qualifications Bachelor's degree in Computer Science, Information Technology, Engineering, Business, or a related field . Experience managing technology, data, AI/ML, or digital-transformation projects .

Understanding of:Machine learning and AI lifecycleGenerative AI and LLMsCloud platformsData engineering and analyticsAPIs and software developmentMLOps/LLMOpsAI governance and security Strong project/program management skills. Excellent stakeholder and communication skills.

Experience with Agile/Scrum, Jira, Confluence, or similar delivery tools is often useful. Certifications such as PMP, PRINCE2, Scrum/Agile, or cloud certifications