AI Security Engineer (Consultant)

Maple Logic; York and North Yorkshire; On-site; GBP 30,000 - 45,000; Full time

Job summary

A technology consulting firm in the United Kingdom is seeking an AI Security Engineer (Consultant) to secure LLM systems and AI products. This entry-level, full-time role involves threat modeling, designing security controls, and collaborating with technical teams. Ideal candidates should have a background in application or product security, familiarity with LLMs, and excellent communication skills. This opportunity allows individuals to work at the forefront of AI security while helping organizations adopt safer practices.

Qualifications

• Background in application, cloud, or product security, with an interest in AI systems.
• Hands-on familiarity with LLMs and related tooling.
• Practical mindset suitable for implementing design controls.

Responsibilities

• Threat model LLM and agent workflows, identifying risks.
• Design and test guardrails for prompt injection and data security.
• Conduct AI-focused security reviews and red teaming.

Skills

Application security

Cloud security

Product security

LLMs familiarity

Clear communication

Job description

Join to apply for the AI Security Engineer (Consultant) role at Maple Logic.

Role Overview

We are looking for an AI security engineer to help our clients secure LLM systems, agents, and AI‑powered products — from threat modeling and red teaming to designing practical guardrails and controls.

You will help organizations move faster with AI without taking unnecessary risks, combining a strong security mindset with a pragmatic, product‑aware approach.

Responsibilities

• Threat model LLM and agent workflows, including abuse cases and data‑leakage risks.
• Design and test guardrails for prompt injection, data exfiltration, and unsafe actions.
• Run AI‑focused security reviews, red teaming exercises, and tabletop simulations.
• Work with engineers to implement mitigations in code, infrastructure, and processes.
• Help teams establish guidelines and checklists for building AI features securely.

Qualifications

• Background in application, cloud, or product security, with an interest in AI systems.
• Hands‑on familiarity with LLMs, agents, or related tooling — comfortable experimenting and reading docs or code.
• Practical mindset: design controls that teams can actually adopt.
• Clear communicator able to work with engineers and non‑technical stakeholders and explain risk without hype.
• Keeps up with evolving AI security landscape — new attacks, mitigations, and best practices.

Seniority Level

Entry level

Employment Type

Full‑time