Vice President AI Product - Smarter

About Us

Mubadala Investment Corporation (MIC) is a global investor, owned by the Government of Abu Dhabi, with USD 300+ BN assets under management, five global offices and business investments in 50+ countries. We innovate and invest across the world to create lasting value for our shareholders, our partners, and future generations.

MIC has recognized that the next frontier in competitive advantage will be driven by the adoption of AI and Machine Learning technologies. In response, a new AI Enablement Unit is has been formed to lead the effort to define and implement an AI strategy and embed AI into the fabric of the MIC organization.

MIC has the ambition of embedding AI in everything that we do. As part of this journey, the AI Enablement Team is building an AI Product team that will deploy and maintain Generative AI and Machine Learning solutions to drive value creation across our business and corporate functions.

To meet this ambition, we are looking for an individual to lead the AI Product team during an exciting period of transformative change and growth; you will play a lead role in the deployment and maintenance of AI products to solve real world business challenges.

The responsibilities include building and embedding AI capabilities to drive value creation for our Corporate Platforms (Human Capital, Legal, Finance, Communications and other support functions). You will work closely with our internal technical teams to deploy enabling AI solutions – this will include driving technical sprint planning & delivery, training & change management activities.

• Set AI product strategy & roadmap:
  Translate business objectives into prioritized use cases with clear ROI and OKRs.
• Architect scalable AI solutions:
  Standardize patterns (RAG, agents, APIs) to reuse across Business and Corporate Platforms.
• Data Contracts:
  Define the right datasets; enforce governance, lineage, PII controls, and quality contracts with the data engineering team.
• Run model lifecycle & ML-Ops:
  Work closely with the AI Lab team to establish CI/CD, experiment tracking, evals, A/B tests, rollbacks, and model registries.
• Deliver through agile execution:
  Operate intake, scoping, sprint planning, manage dependencies and meet delivery SLAs.
• Ensure responsible, secure AI:
  Apply safety, bias, privacy, and legal reviews; set guardrails and human-in-the-loop flows.
• Drive change & enablement:
  Work closely with AI transformation team to publish playbooks, run training, measure adoption and track capability uplift.
• Measure value & performance:
  Define KPIs (accuracy, cycle time, adoption, $ impact); and iterate to targets.
• Govern build/buy & vendors:
  Evaluate platforms, negotiate contracts, manage costs, and ensure interoperability/exit plans.
• Align stakeholders & communicate:
  Partner with that AI strategy and transformation team to align exec sponsors and platform leads; run steering forums and surface delivery risks.

To succeed within this role, you will bring a strong mix of practical experience, technical skills, and business skills, including the following:

• Demonstrated experience leading the development and delivery of enterprise AI/ML and GenAI products from concept through to production and adoption.
• Proven ability to define and own AI product strategy, vision and roadmap, translating business priorities into scalable product solutions.
• Experience successfully delivering multiple enterprise AI products and managing significant product budgets and investment decisions.

• Strong understanding of the end-to-end AI product lifecycle, with experience working across engineering, data science and technology teams in agile environments.
• Practical exposure to LLMs, RAG, agentic AI, data engineering and both cloud and on-premise environments.
• Strong understanding of MLOps practices, including CI/CD, model registries, evaluation frameworks, monitoring and rollback processes.
• Able to engage credibly with highly technical teams while translating technical considerations into clear product and business decisions.

• Experience embedding governance, security and Responsible AI principles throughout the AI product lifecycle.
• Demonstrated experience designing or implementing PII/privacy controls, model-risk processes, human-in-the-loop mechanisms and appropriate audit trails.
• Ability to balance innovation and speed of delivery with organisational policy,…