AI Engineer

Myn; Felixstowe; On-site; GBP 85,000 - 110,000; Full time

Job summary

Myn in the United Kingdom seeks an experienced AI Engineer to lead the integration and customization of our AI stack for the UK & IE market. You will design, test and implement practical AI solutions spanning document understanding, classification, decision support, retrieval over knowledge bases, and agentic workflows across business processes.

You will partner with Operations, Commercial, Compliance, Finance, Transformation, IT and Group teams to translate business needs into scalable AI that

Qualifications

• Experience integrating LLMs into production systems with robust prompt design and failure handling.
• Hands-on with at least one major cloud AI platform (Azure, AWS or Google).
• Strong software/backend engineering fundamentals including APIs, data pipelines, testing and CI/CD.
• Excellent communication with non-technical stakeholders across the business.
• Full production code ownership and end-to-end delivery capability.
• Curiosity to learn complex business processes quickly; English fluency required.

Responsibilities

• Design, test and implement AI solutions for UK & IE markets from prototype to production ownership.
• Identify opportunities for AI, automation and decision-support across functions and size them honestly.
• Build generative AI solutions with retrieval, tool calling, structured extraction and agent workflows.
• Own evaluation criteria, ship metrics, and compare changes against baselines.
• Manage pilots, deployments and scaling criteria; monitor cost, latency and impact.
• Collaborate with operations, commercial, compliance, finance, IT and group teams.
• Contribute to privacy, security and AI governance documentation with Group Legal & IT Security.

Skills

LLM prod.

Cloud platforms

Software engineering

Communication

Code ownership

English fluency

Tools

Azure AI

AWS Bedrock

Google Vertex

Job description

The Role

You will take our AI stack and lead its development and customisation for the UK & IE market.

This is a builder and do-er role. You will design, test and implement practical and compliant AI solutions across the business. This could include document understanding, classification and decision support, retrieval over our own knowledge and procedures, intelligent automation, and agents capable of carrying out multi-step business processes end to end.

You are not being asked to train models from scratch. You are being asked to make models that already exist behave reliably enough for people to trust them in real business processes, particularly where accuracy, compliance and good decision-making matter.

Working closely with Operations, Commercial, Compliance, Finance, Transformation, IT and Group teams, you will turn business needs into scalable solutions.

Key Responsibilities

• Develop and customise AI solutions for the UK & IE market, from prototype through to production ownership.
• Be curious and prepared to self-learn to use generative-AI to build agents that make a difference to our business.
• Identify AI, automation and decision-support opportunities across the business, including Operations, Commercial, Compliance and Finance, and size them honestly before building.
• Design solutions using generative AI and large language models — retrieval, tool calling, structured extraction from business and customs documentation, and agentic workflows where they genuinely fit.
• Own the evaluation. Define how we know a solution is working before it ships, and how we know a change has not made it worse. This is treated as core to the role, not an afterthought.
• Manage pilots and implementation, and set the criteria for killing a pilot as clearly as the criteria for scaling it.
• Monitor performance, inference cost, latency and business impact.
• Collaborate with local teams, Group functions and technology partners.
• Contribute to privacy, security and AI governance compliance, working with Group Legal and IT Security. You should understand how the EU AI Act applies to what you build, and be able to produce the documentation that goes with it.

Requirements

Essential

• Demonstrable experience integrating large language models into production systems — prompt and context design, retrieval‑augmented generation, structured output, and handling failure gracefully.
• Practical experience with at least one major cloud AI platform (Azure AI, AWS Bedrock, or Google Vertex).
• Solid software/backend engineering fundamentals — APIs, data pipelines, testing and CI/CD. Most of this job is engineering.
• Strong communication skills — you will spend real time with subject‑matter experts across the business who understand their processes deeply but may not have a technical or AI background.
• Full production code ownership. Not familiarity.
• You do not need to arrive with customs experience, but you should be curious and able to learn complex business processes quickly.
• Professional fluency in English.

Desirable

• Evaluation engineering: building eval harnesses and regression suites for non‑deterministic systems, LLM‑as‑judge approaches, and human‑in‑the‑loop review design. This is the single strongest signal we look for and we will weight it heavily.
• Context engineering: designing and version‑controlling what a model sees — retrieval strategy, memory, tool descriptions, and policy layers that constrain what an agent is allowed to do.
• Agent orchestration frameworks and standards (LangGraph, MCP, Temporal or equivalent), and experience with long‑running or multi‑step agent workflows.
• Observability and cost control for inference at volume.

What Success Looks Like in Your First Year

By month three:

You understand our business and priority processes well enough to identify where AI can genuinely add value, challenge what we ask for, and you have shipped one small, useful thing.

By month six:

At least one AI solution is live, measured against a baseline, and demonstrably better than what it replaced.

By month twelve:

There is a working evaluation process others can use, a ranked pipeline of next opportunities, and at least two colleagues outside IT operating what you have built without you in the room.