AI Governance Engineer - BPL

To build and maintain the systems that collect, store, process, and analyse data such as data pipelines, data warehouses, and data lakes, ensuring all data is accurate, accessible, and secure.

Responsibilities

• Build and maintain data architectures and pipelines that enable the transfer and processing of durable, complete, and consistent data.
• Design and implement data warehouses and data lakes that manage appropriate volumes and velocity while adhering to required security measures.
• Develop processing and analysis algorithms suitable for the data complexity and volumes.
• Collaborate with data scientists to build and deploy machine learning models.
• Contribute or set strategy, drive requirements, and make recommendations for change.
• Plan resources, budgets, policies, and manage and maintain policies and processes, delivering continuous improvements and escalating breaches.
• If managing a team, define jobs and responsibilities, plan department needs and operations, counsel employees on performance and pay decisions.
• Lead a number of specialists to influence operations in alignment with strategic and tactical priorities, balancing short- and long-term goals, and ensuring budgets and schedules meet corporate requirements.
• Demonstrate clear leadership behaviours: listen authentically, energise and inspire, align across the enterprise, develop others.
• Advise key stakeholders, including functional leadership teams and senior management, on functional and cross‑functional impact and alignment.
• Manage and mitigate risks through assessment, supporting the control and governance agenda.
• Collaborate with other areas of work to keep up to speed with business activity and strategies.
• Create solutions based on sophisticated analytical thought and compare and select complex alternatives.
• Conduct in‑depth analysis with interpretative thinking to define problems and develop innovative solutions.
• Seek out, build, and maintain trusting relationships and partnerships with internal and external stakeholders using influencing and negotiating skills to achieve outcomes.

Leadership & Expectations

Either as a people leader or as an individual contributor, the role requires demonstrable leadership or subject‑matter expertise. People leaders shall create an environment for colleagues to thrive and deliver consistently excellent standards, demonstrating the four LEAD behaviours (Listen, Energise, Align, Develop). Individual contributors shall guide technical direction, lead collaborative multi‑year assignments, train and coach less experienced specialists, and provide information affecting long‑term profits, organisational risks, and strategic decisions.

Qualifications

• Solid Python and software engineering background, building scalable, production‑grade systems.
• Experience implementing policy‑as‑code, governance‑as‑code, or rules‑as‑code frameworks, designing and embedding these approaches within large‑scale environments.
• Experience with CI/CD pipelines, automated testing, deployment pipelines, and integration in modern engineering environments.
• Knowledge of MLOps, LLMOps, model registries, evaluation frameworks, and observability.
• In‑depth understanding of AI governance, model risk, technology risk, data privacy, security, and auditability.
• Ability to demonstrate risk and oversight, change and transformation, business acumen, strategic thinking, and digital and technology skills.
• Knowledge of cloud architecture, ideally AWS or Azure.

Working Arrangement

The role is based in London. The successful candidate will work from the Barclays offices at 1 Churchill Place or 7 Westferry Circus and will be expected to be present in the office for up to three days per week as part of a hybrid working pattern.