Job Introduction
Job Title: Product Manager – Artificial Intelligence
Department: Digital & Technology
Location: Birmingham (minimum of two days a week) Hybrid Role
Reports to: Technology Transformation Director
Budget responsibility: Yes, up to £1m annually
People responsibilities: Yes, leadership of Data Scientist and Dev Ops Engineer
Role Purpose:
The AI Product Manager will drive the strategy, development, and deployment of AI-based products within the organisation. The role is pivotal in ensuring that AI initiatives deliver measurable value to the business, aligning with customer needs and long-term company goals. You will bridge the gap between the technical AI team, stakeholders, and end-users, ensuring smooth execution and successful delivery of AI solutions.
Key Responsibilities:
- Leadership: Manage and mentor an expanding team of Data Scientist and Dev Ops Engineers, fostering a collaborative and high-performance culture.
- AI Product Strategy: Define and drive the overall AI product strategy, ensuring alignment with business objectives and customer needs.
- Stakeholder Management: Interface with business stakeholders and collaborate with cross-functional teams, including engineering, data science, operations, and senior leadership, to prioritise AI initiatives and ensure clear communication.
- Roadmap Planning: Develop, manage, and communicate the AI product roadmap, balancing short-term deliverables with long-term innovation.
- Project Management: Oversee the end-to-end lifecycle of AI products, from ideation and design through to development, deployment, and iteration, ensuring timely delivery within scope.
- Data-Driven Decision Making: Leverage data insights to inform product decisions and measure the success of AI-driven solutions.
- Partner Collaboration: Work closely with external technology partners, such as Microsoft and AWS, to integrate AI technologies, ensuring seamless collaboration.
- Compliance and Ethical Standards: Ensure that AI products adhere to industry regulations, company policies, and ethical AI standards.
- Market and User Research: Understand market trends, customer needs, and business opportunities to drive the development of AI products that solve real-world problems.
- Performance Monitoring: Define success metrics and KPIs to track the performance of AI products, driving continuous improvement and optimisation.
Key Skills and Experience:
- Product Management Expertise: Proven experience in product management, ideally in AI, machine learning, or data-driven products.
- AI & Data Science Knowledge: Strong understanding of AI/ML concepts, including model development, data pipelines, and deployment.
- Technical Acumen: Ability to collaborate effectively with technical teams, with a solid grasp of cloud platforms (e.g., AWS, Azure), APIs, and AI development processes.
- Agile Methodologies: Experience managing projects using agile frameworks, including Scrum or Kanban, and tools like Jira or Trello.
- Problem-Solving: Ability to think critically and solve complex problems by leveraging AI technologies in innovative ways.
- Collaboration & Communication: Exceptional interpersonal and communication skills, with the ability to liaise between technical and non-technical teams.
- Data-Driven Mindset: Strong analytical skills with experience using data to inform product decisions, measure outcomes, and optimise processes.
Qualifications:
- Bachelor’s degree in Computer Science, Data Science, Engineering, Business, or a related field (Master’s degree preferred).
- Certification in Product Management (e.g., Pragmatic Institute, AIPMM) is a plus.
- Certifications or courses in AI/ML are beneficial.
- Experience working with cloud platforms such as AWS, Azure, or GCP.
Personal Attributes:
- Visionary: A forward-thinker who can envision and articulate how AI can drive business transformation.
- Leadership: Strong leadership and decision-making skills, able to inspire and align cross-functional teams.
- Detail-Oriented: Meticulous attention to detail, ensuring high-quality AI product delivery.
- Adaptability: Ability to thrive in a fast-paced environment, adjusting priorities as needed.
- Curiosity: A passion for AI, machine learning, and innovation, always eager to learn and apply new knowledge.
- Resilience: Demonstrates persistence in overcoming challenges and maintaining focus on achieving business objectives.