Production AI Engineer - Vice President

Description

This pivotal Vice President role sits in the company's Technology organisation in the Applications Development job family. It is an engineering-first position that combines software craftsmanship, AI-native development and large-scale distributed systems.

The role is part of a multi-year transformation. You will help shape what production engineering means as autonomous agents, generative AI and self-healing infrastructure become standard, and you will help advance AI engineering practice across the company's technology hub.

You will need a broad understanding of several functional areas and how they connect, along with a clear view of the business impact of your technical work. You will own full end-to-end projects, negotiate well with internal stakeholders, and plan actions and resources for your area over the short and medium term.

Responsibilities

• Design, build and maintain production-grade software, focusing on reliability, scale and operational excellence across the company's global technology estate.
• Build autonomous agentic AI workflows that can reason, plan and act in production with little human involvement.
• Use advanced prompt engineering to bring large language models into operational tooling, incident response pipelines and developer productivity platforms.
• Lead the creation of AI-native observability tools, using agents to spot anomalies, forecast failures and fix problems before end users are affected.
• Write clean, well-tested, well-documented code across the full stack, and promote code review, pair programming and test-driven development.
• Drive continuous delivery and automation across supported applications through root cause analysis reviews, knowledge management, performance tuning and user training.
• Run and improve CI/CD pipelines, Infrastructure-as-Code tooling and GitOps workflows so software ships quickly and safely at scale.
• Work with platform, data and product engineering teams to build AI into the production lifecycle, from deployment through to decommissioning.
• Apply the Agile Framework through either SCRUM or Kanban and make sure it fits with wider organisational processes.
• Work in a heavily regulated financial setting, understanding compliance rules and how they shape system design and data handling.
• Coach and mentor colleagues on AI engineering, prompt design patterns and agentic system architecture, encouraging continuous learning and technical quality.
• Share progress and project status widely across the organisation and manage stakeholders throughout delivery.
• Build a culture of openness and new ideas that helps the team get more done.

Requirements

• Proven experience in a critical software or production engineering role with high business impact, and a strong programming base in Java, Python, Go or similar.
• Hands-on work with AI and machine learning engineering, including LLM APIs (OpenAI, Anthropic, Gemini or open-source alternatives), embedding models and vector databases.
• Proven prompt engineering skill: designing, iterating and evaluating prompts for production uses such as classification, summarisation, code generation and autonomous decision-making.
• Experience designing and deploying agentic systems with frameworks such as LangChain, LangGraph, AutoGen, CrewAI or similar, including multi-agent orchestration and tool-use patterns.
• Strong engineering skills and a solid grasp of the Software Development Lifecycle, GitOps and modern DevSecOps practice.
• Solid working knowledge of core computer science topics such as networking, operating systems, virtualisation and containerisation.
• A polyglot full-stack mindset and the ability to pick up new languages and skills quickly.
• Strong debugging and analytical skills, with the ability to find root causes across networking and infrastructure, application and database layers.
• Experience delivering software using Agile methods (SCRUM or Kanban) is a must.
• Experience of senior stakeholder management.
• Clear, concise written and verbal communication, consistently demonstrated.
• Ability to work in a global setting with on-shore, near-shore and off-shore matrix reporting lines.
• Operational experience running services at scale on Docker and Kubernetes, with a service mesh such as Istio or similar, is highly desirable.
• Operational experience with CI/CD orchestration tools and Infrastructure-as-Code tools such as Terraform, CloudFormation or Pulumi is highly desirable.
• Operational experience using middleware such as MQ or Apache Kafka to run services at scale is desirable.
• Strong experience with end-to-end observability stacks such as Datadog, AppDynamics or Dynatrace is desirable.
• A degree in Computer Science, Mathematics, Physics or a related technical subject is desirable.
• Learnability: you pick up new skills, frameworks and ways of working fast, which matters a great deal in AI engineering.
• Teachability: you take feedback openly, look for mentorship and use guidance to grow faster.
• Flexibility: you work well with ambiguity and change direction smoothly when requirements, technology or priorities shift, without losing pace or quality.
• Engineering mindset: you break problems down, form hypotheses and test solutions carefully.
• Product thinking: you see code as a tool for users and business outcomes, and balance elegance with practical delivery.
• Collaboration: you build trust across engineering, product, operations and leadership, and raise the output of the whole team through generosity and clear communication.
• Curiosity: you ask why before how and explore what AI and production systems can do, out of genuine interest.
• Ownership: you take end-to-end responsibility for your work, from design through deployment to post-incident review.

Conditions

Full-time role.

Hybrid working, with up to 2 days a week working from home, in a business casual office setting.

Equal opportunity policy information is published by the company.

Benefits

• Competitive base salary, reviewed annually.
• Discretionary annual performance bonus.
• 27 days of annual leave plus bank holidays.
• Private medical care and life insurance.
• Employee assistance programme.
• Pension plan.
• Paid parental leave.
• Discounts on products and services for employees, their families and friends.
• Access to a range of learning and development resources.