Applied AI Engineer - #2196592

Applied AI Engineer (Graph Based Agentic AI) Greater Manchester | Hybrid, only 2 to 3 days a week | £55,000 to £70,000

Real AI in production. Not pilots. Not proofs of concept gathering dust. We're partnering with an established fintech in Greater Manchester that already has production-grade AI embedded into customer journeys and internal operations, and they're only just getting started.

A newly appointed Head of Data and AI has the vision and the organisational backing to push this forward hard. A small team of agentic AI engineers is already in place, and this hire sits right at the heart of it. THE ROLE A hands-on engineering role focused purely on applied AI.

Model research and data science sit elsewhere. You'll take foundation models, LLM services, orchestration frameworks and existing ML capabilities and turn them into robust, production-ready solutions that work at scale. You'll also be a go-to voice for AI across the business.

WHAT YOU'LL DO -

• Design and build production-grade AI application patterns combining LLMs, retrieval, tools, APIs and internal platforms
• Build agentic AI capabilities for customer-facing and operational use cases, with a sharp focus on reliability, latency and observability
• Own AI architecture decisions across vendors, orchestration frameworks and integration methods
• Identify where agentic workflows, tool use, RAG and LLM-based decision support add real value
• Shape engineering practices around testing, evaluation, monitoring, guardrails and release
• Upskill colleagues, from engineers to operational teams, on what AI can do and how to use it well

WHAT YOU'LL BRING

• Strong software engineering background with excellent Python and solid discipline in testing, version control and deployment
• Proven experience shipping LLMs, AI services or ML components into production
• Hands-on experience with agentic AI frameworks, orchestration libraries and workflow engines • Strong knowledge of tool use, workflow-based agents, RAG, structured outputs, fallback handling and human escalation
• Experience building robust API-driven integrations with wider platforms and business systems
• A solid grasp of production AI concerns: latency, scalability, resilience, observability, regression testing and safety controls
• Experience in a governed or regulated environment where traceability matters

BONUS POINTS • AWS AI and ML services

• Financial services or another regulated sector
• Conversational, assistant-style or autonomous workflow experiences
• Talks, writing or open source contributions in the AI or engineering community