Artificial Intelligence Engineer

Experis UK; Newcastle upon Tyne; On-site; GBP 50,000 - 70,000; Full time

Job summary

Experis UK is seeking an Applied AI Engineer for their Newcastle location. In this role, you will integrate AI/ML components into applications, design RAG solutions, and evaluate LLM performance. The ideal candidate has hands-on experience with AI systems, strong understanding of ML models, and excellent debugging skills. You will work closely with a dynamic team, ensuring solutions meet high standards of reliability and security, with a focus on mission-critical environments. SC clearance is required or must be obtained.

Qualifications

• Experience building or integrating AI/ML systems into real-world applications.
• Strong understanding of LLMs, ML models, and core statistical concepts.
• Experience evaluating AI systems and improving reliability and performance.
• Ability to debug complex, non-deterministic behaviours.
• Strong communication skills to explain AI trade-offs and risks.

Responsibilities

• Integrate AI/ML components into applications and operational workflows.
• Design and implement RAG solutions.
• Evaluate LLM performance and implement mitigation strategies.
• Test, debug, and improve non-deterministic AI systems.
• Collaborate with engineers, data scientists, and stakeholders.

Skills

Building or integrating AI/ML systems

Understanding of LLMs and ML models

Evaluating AI systems

Debugging complex behaviours

Strong communication skills

Tools

Python

Job description

Applied AI Engineer – Defence & Security

Location: Newcastle

SC Cleared / Eligible

The Opportunity

Join a forward-leaning engineering team applying cutting‑edge AI in real‑world, mission‑critical environments. This role focuses on integrating AI capabilities into production systems, ensuring they are reliable, secure, and deliver measurable impact.

What You’ll Do

• Integrate AI/ML components into applications and operational workflows
• Design and implement Retrieval‑Augmented Generation (RAG) solutions
• Evaluate LLM performance, identify failure modes, and implement mitigation strategies
• Test, debug, and improve non‑deterministic AI systems
• Balance AI approaches with deterministic or statistical methods where appropriate
• Collaborate with engineers, data scientists, and stakeholders to deliver production‑ready AI solutions

What You’ll Need

• Experience building or integrating AI/ML systems into real‑world applications
• Strong understanding of LLMs, ML models, and core statistical concepts
• Experience evaluating AI systems and improving reliability and performance
• Ability to debug complex, non‑deterministic behaviours
• Strong communication skills to explain AI trade‑offs and risks

Bonus Skills

• Hands‑on experience with RAG architectures and LLM tooling
• Experience working in regulated or high‑assurance environments
• Familiarity with AI safety, risk, and governance considerations
• Background in software engineering (Python or similar)

Security Requirement

SC clearance (or willingness/eligibility to obtain) is required.