At a Glance
- Tasks: Implement and deliver a proactive AI Assurance Framework across complex systems.
- Company: Join a leading organisation focused on ethical AI governance.
- Benefits: Enjoy 25 days holiday, bonuses, private health insurance, and flexible working.
- Other info: Opportunities for professional development and a supportive work environment.
- Why this job: Make a real impact in AI safety and ethics while working on exciting projects.
- Qualifications: Experience in AI risk assessments and knowledge of Defence AI standards required.
The predicted salary is between 63000 - 77000 £ per year.
We are seeking a specialist AI Assurance Practitioner to implement, operationalise, and deliver a proactive, risk-based AI Assurance Framework across complex, high-consequence operational and enterprise systems. As our client transitions toward continuous, proportionate AI governance, you will provide critical subject matter expertise to embed prescriptive AI assurance across the full capability lifecycle. Working directly with engineering and delivery teams, senior project owners, and enterprise risk authorities, you will ensure AI-enabled systems are safe, secure, ethical, and operationally effective.
Key Responsibilities
- Policy Implementation & Operationalisation: Translate overarching defence AI policies, standards (such as JSP 936), and industry frameworks (e.g., ISO 42001) into practical, repeatable assurance processes, checklists, templates, and guidance.
- Intake, Triage & Risk Categorisation: Manage the intake and registration pipeline for emerging AI initiatives, assessing system context, consequence, and novelty to determine proportionate tiers of assurance.
- AI Ethical & Risk Assessments: Guide multidisciplinary delivery teams through system boundary definition, hazard identification, ethical impact assessments, control design, residual risk scoring, and formal risk ownership.
- Technical Evidence & Model Review: Interrogate AI system specifications, data provenance, training pipelines, model documentation, algorithmic bias assessments, and data sufficiency to constructively challenge incomplete evidence.
- Specialist Assessment Coordination: Scope and coordinate deeper technical assurance for high-risk capabilities, including model evaluations, adversarial robustness/red-teaming, and cyber/safety stress tests.
- Governance, Escalation & Reporting: Maintain the central AI assurance risk register, elevate critical residual risks through established governance boards, and compile evidence to support senior leadership assurance statements.
- Process Alignment & Integration: Align AI assurance workflows with established digital delivery mechanisms, Secure by Design (SbD) frameworks, safety cases, and technical test/trials pathways.
- Enduring Capability & Knowledge Transfer: Deliver coaching, guidance, and upskilling to internal delivery teams and emerging assurance personnel to build sustainable in-house AI evaluation capability.
Requirements
Essential
- Security Clearance: Valid UK National Security Vetting SC Clearance with eligibility and willingness to undergo Developed Vetting (DV).
- Defence AI Standards: Practical working knowledge of UK Defence AI standards and policies (specifically JSP 936 or equivalent regulated sector frameworks).
- AI Risk & Governance: Proven track record conducting AI impact assessments, ethical risk evaluations, and establishing controls for algorithmic models and automated decision-making.
- Technical Understanding of AI/ML: Grounded technical comprehension of machine learning architectures, data pipelines, model drift, data provenance, validation metrics, and performance evaluation.
- Assurance & Compliance Frameworks: Exposure to emerging international AI standards and frameworks, such as ISO/IEC 42001, NIST AI RMF, or IEEE standards.
- Stakeholder Management: Demonstrated ability to act as an independent challenger while collaborating effectively across diverse teams: data scientists, systems engineers, safety managers, legal advisors, and senior operational stakeholders.
Desirable
- Experience with Secure by Design (SbD), system safety engineering, or defence test and evaluation processes.
- Hands-on experience planning or executing model red-teaming, adversarial testing, or synthetic data verification.
- Background working within UK Defence, national security, aerospace, or other high-reliability regulated sectors.
Benefits
- 25 days holiday increasing annually up to a maximum of 30 days
- Annual bonus - all employees are eligible (following successful completion of probationary period) - level varies by position and is dependent on company performance
- Discretionary bonus for exceptional performance
- 5% matched pension
- Private Health Insurance
- Employee Ownership Trust - from day 1 employees share in the benefits of the company
- Support for flexible working
- 2 paid charity days a year
- 16 weeks of full pay Maternity leave
- 2 weeks full pay Paternity leave
- Support with your professional development including training and certifications and attendance at conferences
- Diverse and interesting projects which give you an opportunity to make a difference
- Choice of laptop and screen
AI Assurance Practitioner in England employer: DIGI2AL
Digi2al Ltd is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration within the maritime technology sector. Located at the heart of the Royal Navy's operations, employees benefit from unique opportunities for professional growth, access to cutting-edge technology, and the chance to make a meaningful impact on national security through strategic leadership in software architecture and AI adoption.
StudySmarter Expert Advice🤫
We think this is how you could land AI Assurance Practitioner in England
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We think you need these skills to ace AI Assurance Practitioner in England
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at DIGI2AL.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at DIGI2AL and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
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How to prepare for a job interview at DIGI2AL
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If DIGI2AL uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
