Senior Software Engineer​/Senior AI Engineer

Senior AI Engineer

Are you excited about building intelligent systems powered by cutting-edge AI technologies? Do you enjoy designing models that turn complex data into impactful solutions?

Embedded Innovation Teams are cross-functional squads embedded within our segments to rapidly turn internal AI experimentation into validated, reusable solutions, building the capabilities we need to deliver customer value and growth. We work problem-first rather than tool-first, directly inside segment and function teams, improving the internal workflows that help our people deliver better outcomes for customers, faster.

As a Senior AI Engineer, you will build and ship AI-powered features as part of a cross-functional Innovation Squad, working inside a business function. You will deliver the set technical direction to production standard, working autonomously within a defined problem, building and testing tool use, retrieval pipelines, and agent workflows, integrating AI capabilities into enterprise systems, and contributing to evaluation, observability, and guardrails.

You will hold a high bar on code quality, flag risks and blockers early, and work alongside host-function stakeholders to make sure what you build fits real workflows, not assumed ones. You'll also support handover and capability-building so the solution is owned and operable after the squad moves on.

• Build prototypes and proofs of concept and ship agentic AI solutions to production standards within a defined technical approach.
• Implement and test tool use, retrieval pipelines, and agent workflows.
• Contribute to evaluation, observability, and guardrails for agentic systems.
• Integrate AI capabilities into existing enterprise workflows and systems.
• Maintain high code quality and documentation so patterns can be reused.
• Flag technical risks and blockers early.
• Interface with technical peers to finalise requirements and complete moderately complex bug fixes.
• Build solutions for reuse, contributing to patterns, reference implementations and starter kits so work done in one function can be picked up by another.
• Instrument solutions to capture outcome data against baselines.
• Work alongside host-function stakeholders to ensure the build fits real workflows, not assumed ones.
• Support handover and capability-building in the host function so the solution is owned and operable after the squad moves on.
• Keep abreast of new technology developments.
• Take on related responsibilities as the squad's needs evolve.

• Engineering experience: 3+ years in software engineering, with hands-on experience building LLM-powered applications in production (RAG, tool-augmented agents, or agentic workflows).
• Education:
  
  BS in Engineering, Computer Science, or equivalent.
• Ways of working:
  Comfortable working autonomously within a defined problem and pushing back when something doesn't make sense, and delivering in short, time-boxed cycles where validated outcomes matter more than perfect solutions.
• Agentic AI / LLMs:
  Building RAG pipelines, tool-augmented agents, and agentic workflows; familiar with prompt engineering, context management, evaluation, and observability.
• Agent fundamentals:
  Understands how agents use memory, tools, and retrieval to complete multi-step tasks.
• Enterprise integration:
  Integrating AI into existing systems via APIs and data pipelines.
• Cloud: AWS, Azure or GCP.
• Delivery: CI/CD, modern SDLC, TDD and code review.
• Data:
  Working with relational, columnar and vector stores, grounded in sound data-modelling principles.
• Languages:
  
  Python, Java, Type Script/JavaScript, SQL and relevant AI SDKs.
• Communication:
  Clear written and verbal communication with technical peers and stakeholders.
• Measurement:
  Instrumenting…