Senior Applied AI Engineer; Manager TC

Senior Applied AI Engineer (Manager)

You will work across a diverse portfolio of clients spanning Financial Services, the Public Sector, and the Private Sector. Our Applied AI Engineering teams deliver production‑grade AI systems in regulated financial institutions as well as government, health, infrastructure, consumer, industrial and energy organisations. This cross‑sector model gives you broad exposure to different regulatory environments, data landscapes and operating models, while building deep engineering capability that transfers across industries.

London CP / Manchester / Birmingham / Edinburgh / Belfast

Hybrid with client‑site travel

Permanent, full‑time

As AI complexity and regulatory expectations rise, FS clients need technical leaders who can architect, govern and operate AI ’s engineering‑led approach — and our collaboration with Microsoft/OpenAI via Azure OpenAI Service — positions our teams to deliver safe, reliable solutions embedded in enterprise environments. You will guide squads and shape architectures to meet these demands.

Lead technical delivery across solution threads: set technical direction, mentor engineers, and ensure systems are production‑ready (reliability, observability, security, runbooks). Continue your development through the Applied AI Engineering Academy focused on advanced patterns and engineering leadership.

• Shape engineering approaches; engage senior stakeholders; articulate trade‑offs; ensure engineering quality across squads and complex client environments.

• Architect enterprise‑grade AI services (agents, RAG pipelines, orchestration layers, platform components); ensure operational readiness; drive Responsible AI, evaluation and best practices.

• Mentor engineers; lead technical reviews; establish reference architectures and reusable accelerators; contribute to internal knowledge sharing and external thought leadership.

• Deep software/systems engineering (Python/Type Script, distributed systems, CI/CD).
• Applied‑AI expertise: LLM/RAG engineering; evaluation; telemetry/drift monitoring; versioning and release management.
• Cloud architecture (Azure/AWS/GCP), Kubernetes/Docker, serverless, IAM and network security.
• Data engineering depth (Spark/Databricks; ETL/ELT); cloud‑native data + AI architectures.
• Enterprise integration and SRE principles (SLIs/SLOs, runbooks, rollback).
• Consulting leadership: stakeholder, budget and risk management; team leadership.

• Graph/big‑data stacks; streaming; cloud architect certifications and Responsible AI governance credentials.

Hybrid with periodic client travel across the UK (and occasional international travel).