AI Engineering and Validation Senior Manager

Mgl

3h 9m ago

On-site

Full Time

Significant hands-on experience in engineering, evaluating, securing or assuring GenAI and agentic AI systems, particularly in production or security-sensitive environments
Strong understanding of cyber security fundamentals relevant to AI systems, including identity and access management, secrets management, sandboxing and containment, network egress, software supply-chain risk, monitoring and logging
Practical knowledge of AI safety and security frameworks and testing methodologies, such as the OWASP AI Testing Guide, MITRE ATLAS and established threat-modelling approaches
Hands-on experience with adversarial testing, AI red teaming or security testing, with the ability to translate threat scenarios into reproducible tests and defensible evidence
Strong hands-on programming skills and experience with modern software engineering practices, including Git, automated testing and reproducible development environments
Demonstrated ability to lead complex technical engagements, exercise sound risk judgement and drive delivery through ambiguity
Strong communication skills, with the ability to translate complex technical issues into clear risks, findings and practical recommendations for both technical and senior stakeholders
A curious and self-directed mindset, with the ability to stay current with rapidly evolving AI capabilities, safety risks and cyber threats
We recognise that no candidate will meet every requirement, candidates with strong depth in AI engineering and demonstrable cyber assurance capability, or strong cyber engineering depth with hands-on agentic AI experience, are encouraged to apply.

Required Skills

git

Required Languages

🇬🇧 English

AI Engineering and Validation Senior Manager

Mgl

3h 9m ago

On-site

Full Time

Significant hands-on experience in engineering, evaluating, securing or assuring GenAI and agentic AI systems, particularly in production or security-sensitive environments
Strong understanding of cyber security fundamentals relevant to AI systems, including identity and access management, secrets management, sandboxing and containment, network egress, software supply-chain risk, monitoring and logging
Practical knowledge of AI safety and security frameworks and testing methodologies, such as the OWASP AI Testing Guide, MITRE ATLAS and established threat-modelling approaches
Hands-on experience with adversarial testing, AI red teaming or security testing, with the ability to translate threat scenarios into reproducible tests and defensible evidence
Strong hands-on programming skills and experience with modern software engineering practices, including Git, automated testing and reproducible development environments
Demonstrated ability to lead complex technical engagements, exercise sound risk judgement and drive delivery through ambiguity
Strong communication skills, with the ability to translate complex technical issues into clear risks, findings and practical recommendations for both technical and senior stakeholders
A curious and self-directed mindset, with the ability to stay current with rapidly evolving AI capabilities, safety risks and cyber threats
We recognise that no candidate will meet every requirement, candidates with strong depth in AI engineering and demonstrable cyber assurance capability, or strong cyber engineering depth with hands-on agentic AI experience, are encouraged to apply.

Required Skills

git

Required Languages

🇬🇧 English