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# Senior AI Engineer

- **Company:** Randstad UK
- **Location:** London, UK (Remote available)
- **Experience:** Expert
- **Salary:** £112,320.0 - £125,840.0
- **Contract:** Temporary contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Cloud Computing, Computer Programming, Extract Transform Load (ETL), Dynamical Systems, Design of User Interfaces, Python (Programming Language), Machine Learning, Cloud Platform System, Large Language Models, Deep Learning, Generative AI, Backend, Build Management, Front End Software Development, Artificial Intelligence Governance, Data Pipelines
- **Published:** October 15, 2026
- **Apply:** https://www.reed.co.uk/jobs/senior-ai-engineer/57462381

## About the Role

* 2-5 years' hands-on software/ML engineering experience delivering production AI solutions (no PhD required).
 * Strong programming skills in Python (Java experience also accepted).
 * Hands-on experience building GenAI applications, LLM workflows, and data pipelines.
 * Cloud experience across AWS or Azure ecosystems along with data orchestration tools (e.g., Airflow).
 * Practical understanding of AI safety, prompt injection handling, and PII/MNPI compliance guardrails.

If you have 2-5 years' experience in ML/AI engineering, strong skills in Python, cloud environments, and AI guardrail security, alongside immediate availability - please apply for this opportunity or please share: your latest CV to .

## Description

* AI Guardrails & Governance: Design and implement backend security guardrail capabilities to sanitize sensitive data (PII and MNPI) and prevent prompt injection risks in production LLM workflows.
 * GenAI Workflows & Scalable Solutions: Build and deploy enterprise-level GenAI, ML, and deep learning solutions using Python or Java.
 * Gen UI/UX & Frontend Integration: Design and implement user interfaces and frontends for AI guardrail requirements (~20-25% of the role).
 * Cloud Infrastructure & Data Pipelines: Build with AWS and Azure services to construct ETL workflows and dynamic systems using orchestration platforms like Apache Airflow.
 * Production Operations: Support production applications, maintain SLAs, and create continuous evaluation metrics for ML solution performance.