Delivery Lead

AI Lead

The AI Lead owns Intelli Ops end-to-end AI agenda — from use case identification and prioritization through to governed delivery and client adoption. The role sets the AI strategy in collaboration with the Program Director and client leadership, then drives execution through workstream teams, the offshore factory, and vendor partners. This is not a research or advisory role. The AI Lead is accountable for use cases landing in production, delivering measurable value, and operating within regulatory and risk framework. Sufficient technical depth to assess feasibility, govern build quality, and challenge vendor claims is essential — but the role leads through others, not by building directly.

Key Responsibilities

• Define and own the Intelli Ops AI use case roadmap — identify, assess, and prioritize AI opportunities across "KYC", Estates, "CEP", and operational workstreams in collaboration with client leads and program leadership
• Lead use case discovery with client business stakeholders — structured workshops in English (French and/or Dutch a plus) to surface pain points, quantify effort, and translate business need into AI problem statements
• Own the AI delivery lifecycle: from feasibility and solution design through build governance, testing, and production deployment — applying the Intelli Ops stage-gate model to AI use cases
• Govern AI build quality — review model selection, prompt engineering, data pipeline design, and integration architecture produced by factory teams and vendors; enforce quality gates before progression
• Define and maintain the Intelli Ops AI governance framework applicable to each client — responsible AI principles, bias and fairness controls, explainability requirements, data handling standards, and human-in-the-loop design patterns aligned to client policy and EU AI Act obligations
• Act as the primary AI interface to client— presenting use case business cases, progress, risk, and outcomes to initiative leads and exec sponsors
• Manage relationships with AI vendors and platform providers; assess fit, negotiate scope, and hold delivery accountable against committed outcomes
• Track and report AI program value: use case pipeline health, delivery status, realized benefits, and risk posture to Program Director and Steering

Required Experience

• Minimum 8 years in technology delivery, with at least 4 years leading AI or advanced analytics initiatives from strategy through to production — not proof-of-concept only
• Demonstrated experience delivering AI use cases in financial services or banking — familiarity with the regulatory constraints, data sensitivity requirements, and risk appetite typical of a tier-1 bank
• Sufficient technical depth to assess AI solution design: understanding of LLM capabilities and limitations, retrieval-augmented generation, classification and extraction models, prompt engineering principles, and API-based AI integration patterns
• Experience governing AI delivery through others — setting standards, reviewing outputs from factory teams or vendors, and enforcing quality gates without doing the build personally
• Strong business case and value realization track record — has quantified AI opportunity, presented to exec stakeholders, and closed the loop on delivered benefit
• Strong written English for program documentation and exec artefacts, Fluent in French and/or Dutch (written and spoken) is a plus but not required
• Experienced in regulated delivery environments — understands what responsible AI, explainability, and human oversight mean in practice, not just in principle
• Comfortable in SI program structures — stage gates, milestone governance, PMO reporting, and multi-party delivery across client, SI, and vendor organizations

Preferred Experience

• Familiarity with EU AI Act classification, obligations, and compliance design — particularly for high-risk use cases in banking (credit, "KYC", fraud)
• Experience with Mistral AI or equivalent enterprise AI platforms in a regulated environment
• Prior delivery of NLP or document intelligence use cases relevant to banking operations — "KYC" document extraction, correspondence classification, estate processing automation
• ServiceNow AI/ML capabilities — Now Intelligence, predictive intelligence, or virtual agent design in an enterprise context

Profile

• Credible with both business and technology audiences — can discuss AI strategy with client executives and challenge a model design decision with a technical factory lead in the same day
• Pragmatic over theoretical — prioritizes use cases that can land in production within program timelines over technically interesting but low-deliverability ideas
• Governance-minded — understands that AI in a regulated bank requires more rigor, not less, and designs for that from the start rather than retrofitting controls
• Operates through influence across a complex multi-party environment — client stakeholders, offshore factory, vendors, and program leadership all pull in different directions; the AI Lead aligns them

Location and Terms

• Travel: 25-30% maybe required to program locations for stakeholder workshops, governance, milestone events, and client relationship management
• Collaboration with offshore teams (e.g. India) and vendors across time zones — flexibility required