AI Governance SME

Company Overview

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Pearls is a global, purpose-driven AI-Native digital engineering partner helping businesses re-imagine, digitalize, and accelerate. As an end-to-end digital technology partner, 10

Pearls helps businesses create future-proof, transformative digital products that leverage emerging technologies. 10

Pearls’ clients include Global 2000 enterprises, high-growth mid-size businesses, and some of the most exciting start-ups from industries like healthcare, fintech, energy, education, real estate, retail, and hi-tech. 10

Pearls has product engineering and software development centers in North America, Latin America, Europe, and South Asia, with its London office based in Paddington.

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We are seeking an experienced AI Governance SME to design and embed AI governance that lets our clients adopt AI safely and s is a client-facing role that spans the full governance lifecycle — from enacting drafted frameworks as published, self-serve guardrails placed where teams actually work, through leading the thinking on the AI governance control plane programme, to running the review path for novel and high-risk AI work jointly with client risk and security leaders.

The ideal candidate brings deep expertise in AI governance frameworks and controls, AI security and evaluation, regulatory compliance (ISO 42001, NIST AI RMF, GDPR, EU AI Act), and data governance, combined with the consulting skills to facilitate workshops, influence stakeholders at all levels, and turn policy into guardrails that engineers and citizen developers want to use. This is a unique opportunity to join a global team of over 1,300 product and engineering professionals and play a leading role in growing our AI practices.

Turn drafted AI governance framework into governance that runs itself: published, self-serve guardrails that let citizen developers and engineering teams move fast within known limits — with review reserved for the novel and high-risk — and act as the thought leader shaping the AI governance control plane programme. Good governance here is measured by how rarely people have to wait for it.

Also interface with existing Data Governance team to champion data domains valuable for AI.

• Enact the framework drafted by Risk & CISO as published, self-serve guardrails and patterns — placed where makers actually work. Communicate and evangelize AI Governance policy across the client workforce.
• Support engineers in executing the risk ladder: score each use case once (reversibility, real-world impact, regulatory exposure, auditability) so risk tier decides architecture, testing depth, oversight level and operational monitoring intensity.
• Lead the thinking on the control plane programme: define what good looks like, shape requirements across the IT-led and citizen-led estates, steer the buy/build/extend evaluation and selection, set the policies to enforce first, and stay the design authority through delivery and hand-off into operations.
• Champion data governance for AI data: work with the client’s existing data governance function so the data that is valuable to AI use cases — client data and knowledge included — is supported through their team, within their governance, catalogue and quality systems.
• Run the single review path for novel or high-risk work (new data sources, client data, autonomous agents) jointly with Risk & CISO — every approval becomes a reusable pattern. Maintain guardrails, patterns and best practices library.
• Keep the risk register (models and agents in use) and the firm-wide AI use case register current.
• Work with the client’s existing risk & compliance team to shift AI Governance policies and processes.

• AI governance —…