Job Description

About the Role

We are seeking an exceptionally skilled

Artificial Intelligence Security Engineer

to lead the security design and governance of our AI/ML ecosystem across multi-cloud environments. This is not a traditional security engineering role -- it requires a rare combination of deep cybersecurity expertise and applied machine learning security knowledge.

The successful candidate will shape the secure adoption of AI across sensitive domains, working closely with AI researchers, cloud architects, compliance officers, and product security teams.

Key Responsibilities

Design, implement, and continuously evolve

security controls for AI/ML pipelines

spanning data ingestion, feature engineering, model training, deployment, inference, and monitoring. Architect secure

multi-cloud AI platforms

(AWS Sagemaker, GCP Vertex AI, Azure ML) with strong identity, encryption, and compliance frameworks. Proactively defend against

adversarial ML attacks

(model inversion, prompt injection, evasion, poisoning) by developing and operationalising advanced countermeasures. Lead

threat modelling for AI-driven systems

, integrating traditional cyber risks with novel AI-specific threat vectors. Ensure

responsible and compliant AI usage

by embedding privacy-preserving techniques (federated learning, differential privacy, homomorphic encryption). Establish automated

security-as-code

guardrails within MLOps/CI/CD pipelines, including red-teaming of ML models. Conduct

AI-specific penetration testing

and model robustness evaluations. Translate regulatory and ethical requirements (UK GDPR, EU AI Act, ISO/IEC 42001, NIST AI RMF) into

operational security controls

. Collaborate with

data governance and risk teams

to ensure traceability, explainability, and audit readiness of AI models. Lead

research and innovation

in emerging AI security trends, contributing to publications, open-source tools, or industry working groups.

Required Qualifications

8+ years in cybersecurity, with at least

3+ years in AI/ML security

. Proven hands-on experience with

AI/ML platforms across AWS, Azure, and GCP

. Strong background in

adversarial machine learning

and

defensive ML techniques

. Proficiency in

Python

(PyTorch, TensorFlow, Scikit-learn) and experience with

secure ML frameworks

. Practical expertise with

data security technologies

(Cloud DLP, KMS, HSM, Confidential Computing). Experience embedding

security into CI/CD and MLOps pipelines

(Kubeflow, MLflow, Argo, GitOps). Knowledge of

federated learning

and

privacy-preserving AI

. Familiarity with

regulatory and ethical frameworks

(UK GDPR, EU AI Act, ISO 27001, NIST AI RMF, CIS benchmarks). Strong knowledge of

network security, cloud IAM, encryption, and PKI

.

Preferred Qualifications

MSc/PhD in Artificial Intelligence, Cybersecurity, or related discipline. Research or published work in

AI security, adversarial ML, or privacy-preserving ML

. Certifications:

CISSP or GCP/Azure/AWS Security Specialist

. Experience in highly regulated industries (Finance, Healthcare, Government). Hands-on work with

zero-trust architectures

for AI applications. Knowledge of

quantum-safe cryptography

applied to AI workloads.

What We Offer

Opportunity to work at the forefront of AI and cybersecurity. Collaborative environment with cross-functional teams of engineers, researchers, and security specialists. Competitive salary, benefits, and professional development opportunities. Flexibility with hybrid or remote work options.

Why This Role Is Unique

This is one of the first roles in the UK market that demands

deep expertise at the intersection of AI and security

. The ideal candidate will be equally comfortable reviewing ML model code, architecting secure multi-cloud AI platforms, and guiding compliance with the EU AI Act.

Job Type: Full-time

Pay: 35,000.00-42,000.00 per year

Work Location: Hybrid remote in Bristol BS14 9HL