Overview

Join Barclays as a Vice President – AI Engineer role, where you will serve as a senior engineer helping to drive adoption of state-of-the-art AI technologies.

Responsibilities

• Collaboration with peers, participate in code reviews, and promote a culture of code quality and knowledge sharing.
• Stay informed of industry technology trends and innovations and actively contribute to the organization’s technology communities to foster a culture of technical excellence and growth.
• Adherence to secure coding practices to mitigate vulnerabilities, protect sensitive data, and ensure secure software solutions.
• Implementation of effective unit testing practices to ensure proper code design, readability, and reliability.
• To contribute or set strategy, drive requirements and make recommendations for change. Plan resources, budgets, and policies; manage and maintain policies/ processes; deliver continuous improvements and escalate breaches of policies/procedures..
• If managing a team, they define jobs and responsibilities, planning for the department’s future needs and operations, counselling employees on performance and contributing to employee pay decisions/changes. They may also lead a number of specialists to influence the operations of a department, in alignment with strategic as well as tactical priorities, while balancing short and long term goals and ensuring that budgets and schedules meet corporate requirements..
• If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others..
• OR for an individual contributor, they will be a subject matter expert within own discipline and will guide technical direction. They will lead collaborative, multi-year assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will train, guide and coach less experienced specialists and provide information affecting long term profits, organisational risks and strategic decisions..
• Advise key stakeholders, including functional leadership teams and senior management on functional and cross functional areas of impact and alignment.
• Manage and mitigate risks through assessment, in support of the control and governance agenda.
• Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does.
• Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business.
• Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies.
• Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives. In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions.
• Adopt and include the outcomes of extensive research in problem solving processes.
• Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills to achieve outcomes.

Nice to have

• Experience building evaluation frameworks for agentic systems including agent benchmarking, reasoning traces, and monitoring observability for multi-step AI workflows in production
• Experience in vector databases, knowledge graphs, semantic search, and memory systems for stateful agents with understanding of retrieval optimisation and context management
• Experience building AI safety/guardrails systems — content filtering, prompt injection detection, PII redaction, toxicity detection
• Knowledge of AI security frameworks — NIST AI RMF, MITRE ATLAS, OWASP LLM Top 10
• Experience with model fine-tuning (LoRA, RLHF, supervised fine-tuning) for domain-specific SLMs
• Knowledge of responsible AI practices, model governance, and security considerations for autonomous systems
• Background in financial services — understanding of regulatory requirements, data residency, and compliance obligations
• Experience with policy engines (OPA/Rego) and zero-trust identity models with OAuth2/OIDC (EntraID/Azure AD)
• Experience with cost attribution and chargeback models for shared AI infrastructure platforms