Senior AI Assurance Lead

Access UK; Kuala Lumpur; Hybrid; MYR 180,000 - 240,000; Full time

Benefits offered by this job

25 days leave

Health contribution

Charity days

Job summary

Access UK is seeking a Senior AI Assurance Lead to help us adopt and govern AI responsibly across products, software development and business processes. You will coordinate risk-based assurance, assess new AI use cases, and drive measurement of control effectiveness while working with Cyber, Product, Engineering, IT and Legal teams.

You will help build a sustainable AI assurance programme, identify material changes in systems and data, and coordinate reassessment or action with cross-functional

Qualifications

• Experience providing risk-based assurance for AI systems across products and processes.
• Ability to coordinate across cyber, product, engineering, IT and legal teams as needed.
• Familiarity with governance frameworks for AI and risk-based controls.

Responsibilities

• AI discovery, inventory and intake processes, defining required information for assessment.
• Lead initial AI risk assessments using the agreed methodology and tooling.
• Place AI systems into proportionate monitoring cycles with automation to reduce manual effort.
• Coordinate AI security testing and control assurance with specialist teams and document results.

Skills

AI risk management

Risk-based assurance

Automation tooling

Stakeholder coordination

Tools

Assurance tooling

AI testing frameworks

Job description

We're looking for people to join the Access family, who share our passion for believing in better, and who will help us continue to grow.

Love Work. Love Life. Be You. - is central to our success and how we give our customers the freedom to do more of what's important to them.

What does Access offer you?

We offer a blended approach to office working, encouraging you to collaborate and connect in one of our thriving offices. We deliver on what we say, taking the development of our people seriously. We'll work with you to progress your success plan and provide opportunities to accelerate your career.

On top of a competitive salary, our wellbeing days taking you to 25 days leave a year and a health contribution, you'll also be able to choose from a range of benefits to suit you. We're an organisation that likes to give back, so you'll also have three charity days allocated to support a cause that matters to you.

Role purpose

As our Senior AI Assurance Lead, you will play a key role in helping Access adopt and use AI responsibly. You will coordinate practical, risk-based assurance for AI systems used across our products, software development, business processes and standalone tools. Using agreed processes and assurance tooling, you will assess new or materially changed AI use cases, coordinate proportionate testing and monitoring, and provide clear evidence of risk and control effectiveness.

You will work closely with system owners and specialists across Cyber, Product and Engineering, IT&O, Third-Party Risk Management and In-House Legal. You will not be expected to own every technical control, investigation or governance decision. Instead, you will bring the right people together, maintain a reliable assurance record and ensure material concerns are escalated through established routes.

This is an opportunity to help build a sustainable programme of continuous AI assurance, prioritised by risk and supported by automation wherever practical. You will help identify material changes in systems, models, data, integrations, usage and external threats, then coordinate reassessment or control action where needed.

This is an assurance role, rather than a policy ownership or dedicated security operations position. In-House Legal retains responsibility for the overarching AI governance framework and legal interpretation, while technical and operational teams remain responsible for designing, operating and remediating their controls. You will provide the coordination, challenge and insight that help those teams make well-informed decisions.

What you'll be doing

1. AI discovery, inventory and intake

   Coordinate the intake of new or materially changed AI systems and confirm that each has a clear business owner, technical contact and accountable risk owner.

   Work with Product, Engineering, IT and business teams to understand the purpose, intended use and key dependencies of each system.

   Maintain accurate records in the AI inventory or assurance platform, following up gaps and unregistered use through agreed routes.

   Define the minimum information and evidence needed for proportionate assessment, drawing on subject matter experts where required.

2. Initial AI risk assessment

   Lead proportionate initial assessments for new or materially changed AI systems using the agreed methodology and tooling.

   Assess the use case, data, model, architecture, integrations, users and operational context, bringing in privacy, security, legal or technical specialists where needed.

   Document the initial risk profile, evidence gaps, required controls, monitoring needs and any residual risk decisions.

   Escalate higher-risk or novel cases to the appropriate governance, legal, security or risk authority rather than attempting to resolve them alone.

3. Continuous AI risk monitoring

   Place approved systems into a proportionate monitoring cycle based on risk and criticality.

   Configure and maintain practical monitoring rules, thresholds and reporting within the selected assurance tooling, using automation to reduce manual effort.

   Review material alerts and changes to models, data, prompts, agents, integrations, permissions or usage, and coordinate reassessment where warranted.

   Maintain an auditable assurance history and track material findings, exceptions and agreed actions with the teams responsible for remediation.

4. AI security testing and control assurance

   Plan and coordinate proportionate assurance testing, performing defined checks directly and engaging specialist teams for deeper technical testing.

   Assess relevant AI security risks, including prompt injection, information disclosure, insecure integrations, unsafe tool use, excessive agency and inappropriate access.

   Review evidence that agreed guardrails, access controls, logging, human oversight, data protections and fail-safe arrangements operate as intended.

   Help develop reusable test procedures for common AI services and architectures, improving consistency and reducing duplicated effort