Applied AI Engineer

Inara

Manchester

Hybrid

GBP 55,000 - 70,000

Full time

8 hours ago
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Job summary

Inara in Greater Manchester is seeking an Applied AI Engineer (Graph Based Agentic AI) to join the team in a hybrid role, 2–3 days a week. This hands-on position focuses on turning foundation models and LLM services into production-ready, scalable solutions for a fintech client.

You will design production-grade AI patterns, own AI architecture decisions across vendors, and act as a go-to voice for AI across the business, partnering with engineering and product teams to push capabilities from

Qualifications

  • Strong Python software engineering background with testing and deployment discipline.
  • Proven experience shipping LLMs, AI services or ML components into production.
  • Hands-on with agentic AI frameworks, orchestration libraries and workflow engines.
  • Experience building API-driven integrations with enterprise platforms.
  • Understanding of latency, scalability, observability and safety controls in prod AI.
  • Experience in governed or regulated environments with traceability.

Responsibilities

  • Design production-grade AI patterns combining LLMs, retrieval, tools and APIs.
  • Build agentic AI capabilities for customer-facing and operational use cases.
  • Own AI architecture decisions across vendors and integration methods.
  • Identify value of agentic workflows, RAG and decision support.
  • Shape engineering practices around testing, evaluation, monitoring and guardrails.
  • Upskill colleagues on AI capabilities and usage.

Skills

Python
LLMs
Production AI
API integrations
Testing & deployment
Observability
Regulated environment

Tools

Orchestration frameworks
Workflow engines
Retrieval tools

Job description

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
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