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# Senior AI Engineer

- **Company:** 83zero Ltd
- **Location:** Nottingham, UK
- **Experience:** Expert
- **Salary:** £130,000.0 - £182,000.0
- **Contract:** Contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon S3, Data Control, Identity and Access Management, Software Architecture, Software Engineering, Unstructured Data, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Agentic-AI, Amazon Bedrock, Production Code, Machine Learning Operations, Functional Programming
- **Published:** October 22, 2026
- **Apply:** https://www.totaljobs.com/job/senior-ai-engineer/83zero-limited-job108215707

## About the Role

* A strong software engineering background and a track record of shipping AI/LLM systems into production.
 * Strong hands-on experience deploying AI/ML workloads on AWS. Amazon Bedrock experience would be a significant advantage.
 * Practical experience with RAG, embeddings and processing unstructured data.
 * Confidence designing for security, privacy, tenant isolation and auditability.
 * The ability to lead through technical expertise, explain trade-offs clearly and bring an existing team with you.

Additional experience that would be useful

Agentic workflows and tool use; prompt and context engineering; structured outputs and function calling; NLP, topic modelling and classification; multimodal processing; and optimisation of LLM cost, latency and throughput.

Working arrangement

This is a contract position, mainly remote, with some on-site time in Cardiff required. You must have the right to work in the UK.

## Description

We're looking for a senior, hands-on AI Engineer to build production AI features and provide technical direction to an existing engineering team.

You'll write significant production code, shape architecture and help the team make sound decisions on models, tooling and build versus buy. You'll need the experience to challenge an approach, explain the alternatives and help deliver the solution.

The work

 * Take AI features from prototype through to secure, reliable production deployment.
 * Design and deploy AI/ML workloads on AWS, using services such as Amazon Bedrock or SageMaker, alongside S3, IAM and Lambda.
 * Assess commercial APIs, hosted models and open-weight alternatives against capability, cost, latency and data controls.
 * Build RAG pipelines, covering retrieval, chunking, embeddings, grounding and citations.
 * Develop document ingestion and extraction pipelines across PDFs, Office documents, images and tables.
 * Build evaluation frameworks to test accuracy, hallucination risk and model or prompt regressions.
 * Guide engineers through architectural decisions, technical collaboration and hands-on delivery.