Petrogate has been appointed on an exclusive basis to identify a Chief AI Officer to own end-to-end AI strategy and delivery for a diversified enterprise scaling GenAI across products and internal operations. This is a board-facing build-and-run role with direct P&L impact.
Client: Confidential • Location: Dubai/Abu Dhabi (global remit) • Employment: Permanent, Executive
The mandate in one line
Turn AI from experiments into a repeatable platform + product capability that measurably improves revenue, margin, and risk posture within 12–18 months.
What success looks like (outcomes, not tasks)
Strategy to operating model: Enterprise AI strategy translated into a funded roadmap, org design, and a central AI platform (model gateway, retrieval, guardrails, observability) used by multiple business units.
Measurable value: 3–5 production use-cases (e.g., agentic customer support, knowledge search, underwriting/claims assist, document automation) each with signed-off KPIs (revenue lift, cycle-time reduction, cost per interaction).
Risk & governance: Company-wide policies and controls for safety, privacy, PDPL/data-residency, and model risk management; quarterly assurance reporting to the board.
Cost discipline: Clear FinOps for AI—token/GPU budgets, vendor strategy, and unit-economics targets.
Talent & culture: A high-calibre team (platform, ML, data, applied science, prompt/retrieval engineering) with hiring plan, career ladders, and vendor ecosystem in place.
Change management: Adoption playbooks for business units; training and enablement that moves usage beyond pilots to BAU.
Core responsibilities
Own the AI vision and multi-year roadmap aligned to corporate strategy; present progress and risks to the CEO/board.
Stand up the enterprise AI platform (build/buy) covering inference, retrieval, guardrails, evals, and observability; set SLOs for latency, cost, and quality.
Prioritise and sponsor high-value product & ops use-cases; enforce stage-gate discipline from discovery → pilot → scale.
Establish governance: model inventory, evals, red-teaming, PDPL/data-residency, third-party risk, and audit evidence.
Shape the commercial model with vendors/hyperscalers; negotiate capacity, pricing, and IP terms.
Lead and mentor a cross-functional organisation; upskill executives and business leaders on AI economics and risk.
Ideal candidate profile
12–15+ years across data/ML/platform with executive ownership of AI products at scale; has shipped production GenAI in complex/regulatory environments.
Proven builder of platforms (RAG, model routing, eval/guardrails, observability) and of products that hit commercial KPIs.
Executive communicator who can defend budgets with numbers and manage board-level risk conversations.
Balanced background across technology, product, and governance; credibility with Engineers and CFO/Legal alike.
Global mindset; experience in GCC or other data-sovereign markets is advantageous. STEM MSc/PhD preferred.
First 90 days (expectations)
Day 30: Current-state assessment, risk register, vendor map, and a ranked use-case portfolio.
Day 60: Platform blueprint (people/process/tech), target architecture, and first two use-cases in build.
Day 90: Operating cadence live (steerco, metrics), platform MVP in limited production, and signed business cases for Q2–Q3 scale-up.
Reporting & team
Reports to: CEO (or Group CTO with direct board access).
Directs: Head of AI Platform, Head of Applied AI, AI Governance Lead, and a blend of internal squads/partners.
Compensation
Executive base + performance bonus + long-term incentives (equity or cash LTI). Full relocation and family benefits available.