Principal Software Engineer​/Principal AI Engineer

Principal Software Engineer / Principal AI Engineer

Are you excited about building intelligent systems powered by innovative AI technologies? Do you enjoy creating solutions that turn complex data into impactful outcomes?

Embedded Innovation Teams are cross‑functional squads embedded within our segments to rapidly turn internal AI experimentation into validated, reusable solutions. 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 Principal AI Engineer/Principal Software Engineer, you will be the technical lead for an embedded Innovation Squad, owning technical execution from discovery through to production. You will assess and harden existing AI prototypes, deliver new ones, and establish the agentic AI patterns, orchestration, tool use, memory, and retrieval that other squads reuse. You will work directly with internal stakeholders and end users in the host function, finalising requirements, making the architectural calls, and codifying validated solutions into reusable patterns, reference implementations, and starter kits.

You may also provide sizing, infrastructure, and budget recommendations, and you will mentor and elevate the engineers around you.

• Own technical execution from discovery to production; build, assess, and harden prototypes and proofs of concept, and deliver new ones.
• Design and govern reusable agentic AI patterns (orchestration, tool use, memory, retrieval).
• Ensure delivery meets architecture, security and data‑governance standards; recommend infrastructure, hosting and data residency.
• Codify validated solutions into patterns, reference implementations, and starter kits so they can be picked up and scaled across other functions.
• Provide design input, finalise requirements, and work directly with internal stakeholders and end users in the host function.
• Write specifications, fix complex bugs, and design complex data models.
• Act as the primary technical contact for external resources and the squad's go‑to on coding and AI.
• Establish baselines and report measurable outcomes for every initiative.
• Maintain visibility of in‑flight AI pilots within the function to prevent duplication and surface candidates for reuse.
• Ensure alignment with enterprise non‑negotiables: security, compliance and central technology infrastructure standards.
• Continuously evaluate emerging technologies and mentor and elevate team members.
• Take on related responsibilities as the squad's needs evolve.

• Engineering experience: 10+ years in software engineering, with hands‑on AI system design, build or integration, and a track record of taking AI prototypes to production in enterprise environments.
• Education:
  
  BS in Engineering, Computer Science or equivalent; advanced degree preferred.
• Agentic AI / LLMs: LLM orchestration, prompt engineering, context‑window management and production guardrails; MCP, tool‑augmented agents and RAG at enterprise scale.
• Enterprise integration:
  Integrating AI into enterprise systems via APIs and data pipelines, with strong security, data governance and residency practices.
• Cloud: AWS, Azure or GCP, including managed AI/ML services.
• Delivery:
  Agile, CI/CD, modern SDLC and TDD.
• Data and architecture:
  Modelling across relational, columnar and vector stores, grounded in sound architectural principles.
• Ways of working:
  Thrives in ambiguity, framing the problem, extracting defined spec, and prioritises shipping validated outcomes over perfect solutions, moving pilots to production at pace.
• Languages:
  
  Python, Java, Type Script/JavaScript, SQL and relevant AI SDKs.
• Leadership and delivery management:
  Plans and sequences work, manages scope, dependencies and priorities, removes blockers, and drives delivery to keep innovation moving.
• Communication and influence:
  Presents concisely to senior management, host‑function stakeholders and cross‑functional teams, and builds buy‑in and drives technical decisions across.
• Commercial awareness:
  Budget‑aware; partners with internal and external resources, including managed…