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# Artificial Intelligence Engineer - Java/Python

- **Company:** Halian .
- **Location:** Reading, UK
- **Experience:** Expert
- **Salary:** £95,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Software as a Service, Continuous Integration, Data Stores, Distributed Systems, Python (Programming Language), NoSQL, Performance Tuning, Software Deployment, Software Engineering, SQL Databases, Cloud Platform System, Large Language Models, Prompt Engineering, Backend, Kubernetes, Docker, Microservices
- **Published:** May 20, 2026
- **Apply:** https://find.jobs/jobs-near-me/artificial-intelligence-engineer-java-python-reading-berkshire/2776957309-2/

## About the Role

* 5+ years in software engineering, with strong experience in Python and/or Java
 * Hands-on experience working with LLMs (prompt engineering, fine-tuning, embeddings, vector databases, RAG)
 * Experience building and deploying applications in cloud environments (Azure preferred, AWS/GCP also considered)
 * Strong understanding of APIs, microservices, and distributed systems
 * Familiarity with tools like Docker, Kubernetes, and CI/CD pipelines
 * Experience working with data stores (SQL/NoSQL) and large datasets
 * Bonus: experience with AI frameworks (LangChain, LlamaIndex, etc.)

## Description

We're hiring the first dedicated AI Engineer to join a fast-growing (~200 people) SaaS organisation making a real-world impact. This is a rare opportunity to shape the AI strategy, design production-grade systems, and bring cutting-edge LLM-powered solutions into a live product environment.

The Role

You'll sit at the intersection of AI, backend engineering, and cloud systems, designing and deploying intelligent features that directly impact users.

Expect to:

 * Design and implement LLM-based applications (RAG pipelines, agents, copilots)
 * Build scalable backend services using Python and Java
 * Integrate AI into existing cloud-native SaaS platforms
 * Own the full lifecycle: experimentation prototyping production
 * Optimise model performance, cost, and latency in real-world environments
 * Collaborate across engineering, product, and data teams to identify high-impact AI use cases


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