Ai Engineer

Morgan McKinley
Yorkshire And Humberside, HU4 6QN, United Kingdom
5 days ago
Job Type
Permanent
Work Pattern
Full-time
Work Location
On-site
Seniority
Senior
Education
Degree
Security Clearance
Required
Posted
26 May 2026 (5 days ago)
Senior AI Developer - Generative & Agentic AI

We are partnering with a global technology consultancy delivering next-generation engineering solutions across digital transformation, cloud, automation, integration, low-code, and AI application development. With an international presence and enterprise-scale clients, the business helps organisations modernise operations and accelerate innovation through digital-first technology solutions.

The Role

An exciting opportunity has arisen for an experienced AI Developer to help build core services, features, and capabilities for an enterprise-grade Generative & Agentic AI platform within a large-scale, regulated environment.

This role combines strong software engineering expertise with DevOps capability and hands-on experience integrating Large Language Models (LLMs) into secure, scalable enterprise systems. You'll work closely with architects, platform engineers, and product teams to operationalise AI services and contribute to the evolution of modern AI engineering practices.

Key Responsibilities
  • Develop and optimise Python-based AI components, including prompt orchestration, output validation, and evaluation tooling.

  • Work with Generative and Agentic AI patterns, including LLM integration, RAG architectures, prompt-driven workflows, and AI service orchestration.

  • Integrate AI capabilities with enterprise systems, observability tooling, and security frameworks.

  • Design and maintain CI/CD pipelines within cloud-native engineering environments.

  • Support benchmarking, evaluation, experimentation, and cost optimisation for LLM workloads.

  • Contribute to scalable RAG implementations and enterprise data access patterns.

  • Help define reusable APIs, engineering standards, and platform documentation.

  • Troubleshoot and optimise distributed systems and cloud-based services.

  • Collaborate across engineering, platform, architecture, and product teams to deliver reliable AI services.

Required Skills & Experience
  • Strong commercial Python engineering experience, including FastAPI.

  • Strong Java development experience within production environments.

  • Hands-on experience with Generative AI, Agentic AI, and Large Language Models.

  • Experience evaluating LLM performance and handling prompt engineering complexities.

  • Strong DevOps and CI/CD experience with a focus on automation and observability.

  • Experience working within regulated or security-conscious enterprise environments.

  • Knowledge of authentication, secrets management, network security, and model governance.

  • Experience developing and deploying AWS services, including:

    • EC2

    • EKS

    • S3

    • SQS

    • DynamoDB

    • Bedrock

    • AgentCore

Desirable Skills
  • Experience with Kong API Gateway, Kong Mesh, and Flux CD.

  • RESTful API and microservices development.

  • Terraform and GitOps workflows.

  • Exposure to prompt evaluation, observability, or AI red-teaming tools.

  • SQL and NoSQL database experience.

  • Understanding of vector search technologies and Retrieval-Augmented Generation (RAG) patterns.

About You
  • A proactive self-starter who takes ownership and drives solutions independently.

  • Comfortable operating in fast-evolving technical environments where best practice is still emerging.

  • Strong communicator able to collaborate across engineering, data, and product functions.

  • Naturally curious about emerging AI technologies and how they can be applied securely and effectively.

  • Passionate about automation, scalability, and continuous improvement.

Related Jobs

View all jobs

AI Engineer

Opus Recruitment Solutions London, United Kingdom
£60,000 – £70,000 pa Remote

AI Engineer

Hays Technology Manchester, United Kingdom
On-site Clearance Required

AI Engineer

Understanding Recruitment E16Bd, E1 6BD, United Kingdom
£60,000 – £70,000 pa Hybrid

AI Engineer

Understanding Recruitment M11Ad, M1 1AD, United Kingdom
£60,000 – £70,000 pa Hybrid

AI Engineer

Boss Professional Services London, United Kingdom
£80,000 – £100,000 pa Permanent

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Where to advertise data science jobs UK in 2026: the specialist boards, communities and channels that actually reach senior and lead data science talent. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Data Science Jobs UK 2026: What to Expect Over the Next 3 Years

Data Science Jobs UK 2026: roles, salaries and the trends shaping UK data science hiring over the next three years — from MLE crossover to GenAI workflows. Data science has spent the past decade being described as the sexiest job of the twenty-first century. By 2026, the reality is both more nuanced and more interesting than that label ever suggested. The discipline has matured, fragmented, deepened, and in some respects reinvented itself — and the jobs market has changed with it in ways that create genuine opportunity for those who understand what employers actually want, and genuine difficulty for those still operating on assumptions formed five years ago. The data science jobs market of 2026 is not simply a larger version of what it was three years ago. The generalist data scientist — equally comfortable wrangling data, building models, and presenting insights to the board — is giving way to a more specialised landscape where employers know exactly what problem they are trying to solve and are looking for candidates with the specific depth to solve it. Machine learning engineering, causal inference, experimentation, AI product development, and domain-specific applied science have all emerged as distinct career tracks within what was previously a single, loosely defined profession. At the same time, the arrival of large language models and the broader AI capability wave has both threatened and created data science roles in equal measure. Some of the work that junior data scientists spent their early careers doing — data cleaning, exploratory analysis, basic model building — is being partially automated by AI tooling. But the demand for practitioners who can evaluate AI systems rigorously, apply statistical thinking to complex business problems, and build the data foundations on which AI depends has grown considerably. The candidates who will thrive over the next three years are those who understand where the discipline is heading — which specialisms are attracting the most investment, which technologies are reshaping what data scientists are expected to build and know, and how to position a data science career that will remain valuable as the field continues to evolve around them. This article breaks down what the UK data science jobs market is likely to look like through to 2028 — covering the titles emerging right now, the technologies driving employer demand, the skills that will matter most, and how to position your career ahead of the curve.