AI Ops Platform Engineer

Job Title

AI Ops Engineer – AI Ops Platform Engineer

Role Purpose

To lead and manage engineering teams, providing technical guidance, mentorship, and support to ensure the delivery of high‑quality software solutions, driving technical excellence, fostering a culture of innovation, and collaborating with cross‑functional teams to align technical decisions with business objectives.

Join us as an AI Ops Engineer, to build and run an enterprise AI Factory within our Card Merchant Services organisation, enabling AI‑driven change across the merchant payments lifecycle.

Accountabilities

• Lead engineering teams effectively, fostering a collaborative and high‑performance culture to achieve project goals and meet organizational objectives.
• Oversee timelines, team allocation, risk management and task prioritization to ensure the successful delivery of solutions within scope, time, and budget.
• Mentor and support team members’ professional growth, conduct performance reviews, provide actionable feedback, and identify opportunities for improvement.
• Evaluate and enhance engineering processes, tools, and methodologies to increase efficiency, streamline workflows, and optimize team productivity.
• Collaborate with business partners, product managers, designers, and other stakeholders to translate business requirements into technical solutions and ensure a cohesive approach to product development.
• Enforce technology standards, facilitate peer reviews, and implement robust testing practices to ensure the delivery of high‑quality solutions.

Expectations

• Contribute to or set strategy, drive requirements and make recommendations for change.
• Plan resources, budgets and policies; manage and maintain policies/processes; deliver continuous improvements and up‑cycle breaches of policies/procedures.
• Define jobs and responsibilities, plan for the department’s future needs and operations, counsel employees on performance and contribute to employee pay decisions and changes.
• Influence the operations of a department, balance short‑ and long‑term goals, and ensure budgets and schedules meet corporate requirements.
• Demonstrate the four LEAD behaviours: Listen and be authentic; Energise and inspire; Align across the enterprise; Develop others.
• If acting as an individual contributor, serve as a subject‑matter expert in the discipline, guide technical direction, lead collaborative, multi‑year assignments, and coach less experienced specialists.
• 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.
• Collaborate with other areas of work to keep up to speed with business activity and strategies.
• Create solutions based on sophisticated analytical thought, comparing and selecting 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.
• Demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship, and the Barclays Mindset of Empower, Challenge and Drive.

Key Responsibilities

• Accountable for the end‑to‑end operationalisation of AI, spanning model, prompt and agent lifecycles – deployment, monitoring, guardrails and cost optimisation – ensuring AI solutions are production‑ready, auditable, compliant and scalable across merchant payment use cases.
• Accountable for the end‑to‑end engineering of GenAI and ML platforms, embedding governance, observability and operational resilience by design, while enabling teams to deploy and run AI solutions with clarity, assurance and accountability at scale.

Qualifications and Experience

• Supporting production‑scale LLMOps / AgentOps lifecycles, including CI/CD for models, prompts and agents; versioning; structured evaluation; controlled releases; and monitoring of drift, hallucination and agent behaviour.
• Contributing to the build and operation of cloud‑based AI platforms on AWS, including services such as Amazon Bedrock and agent orchestration capabilities, alongside solid Python development skills and an understanding of secure API and microservices design.
• Supporting AI platforms with embedded governance approaches, including policy‑as‑code, guardrails, alignment to model risk frameworks, and maintaining lifecycle traceability with audit‑ready evidence.
• Applying observability and reliability practices to AI platforms, contributing to service level measures and monitoring latency, cost, quality and failure modes, supported by tools such as CloudWatch and OpenTelemetry.
• Understanding of AI cost and performance considerations, including working with token usage, model selection, caching approaches and balancing trade‑offs between latency, cost and output quality.
• Retrieval‑Augmented Generation (RAG) and vector database implementation, with practical experience using technologies such as OpenSearch, FAISS or similar to support scalable, production‑ready retrieval workflows.
• Data pipeline engineering, building and operating AI‑ready pipelines using AWS Glue, S3 and related services to support model training, inference and evaluation.
• Advanced observability and reliability engineering, including experience with CloudWatch, OpenTelemetry and established production resilience patterns for AI workloads in critical banking systems.
• Other highly valued skills may include knowledge of self‑serve self‑host deployment solutions, requirement for cultural alignment with Barclays, and experience of engineering teams in large scale banking environments.
• Key critical skills relevant for success include risk and controls, change and transformation, business acumen, strategic thinking and digital and technology capability. Role‑specific technical skills are also required.

Location and Working Pattern

Location: London. Hybrid working pattern with 3 days per week office‑based presence expected.

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