Architect (Temporary)

3 weeks ago


Reading Berkshire, United Kingdom Maclean Moore Ltd Full time

Role: AI Security Architect
Contract Length: Initial 6 months with further extensions to follow
Maclean Moore are working with our global consultancy client to find an AI Security Architect to Develop and implement comprehensive AI/ML security strategies, policies, standards and guidelines to protect organizational assets and ensure the secure operation of AI and ML systems.

Develop and own robust enterprise security architecture for AI/ML systems, CI/CD and data pipelines.
Participate in enterprise-wide architecture initiatives for AI/ML. Understand the workflow and pipeline architectures of ML and deep learning workloads.
Conduct security risk assessments and threat modeling for AI/ML and other business projects performed thorough design reviews and security assessments of architectures and designs, identifying vulnerabilities, threats, and risks, and providing recommendations for effective mitigation measures for common attack vectors and threats.
Support the testing of AI/ML models, LLM and development of trustworthiness, safety, fairness, bias and inappropriateness detection, as well as adversarial test specification, development, and execution.
Define and enforce robust access controls, authentication mechanisms, and encryption standards to safeguard AI/ML systems, training data, provenance, and any sensitive data.
Stay abreast of emerging AI security threats, trends, and technologies, evaluating their impact and proactively adapting security measures to mitigate potential risks.
Conduct regular training sessions and awareness programs to educate stakeholders on AI/ML security best practices, policies, and procedures.
Develop and maintain relationships between data scientists, data engineers, developers, operations (DevOps, DataOps, MLOps) and business unit leaders to govern and support scalability of the ML and AI initiatives.
Previous hands-on experience as developer, programmer or data scientist would be preferred.
Proficiency in programming languages commonly used in AI/ML, such as Python, R, C, C++, or Java, and their associated security considerations.
Previous experience with ML, LLM, deep learning and data manipulation techniques, libraries, and frameworks such as TensorFlow, PyTorch, Jax, and scikit-learn is desirable.
Experience in implementing secure coding practices, DevOps, CI/CD pipelines and familiarity with secure software development life cycle (SDLC) methodologies.
Familiarity with current and emerging regulations and standards, such as the EU AI Act, the Digital Services Act, the Digital Markets Act, GDPR and ISO 27001, and their implications for AI/ML security, data protection and privacy.
Excellent analytical and problem-solving skills, with the ability to assess complex security risks and develop effective mitigation strategies.
Strong understanding of modern software engineering, cloud services and DevOps, including knowledge of DevOps workflows and tools, such as Git, containers, Kubernetes and CI/CD orchestration tools.
Strong understanding of common security vulnerabilities and threats specific to AI/ML, including adversarial attacks, prompt injection, data poisoning and the MITRE ATLAS framework.



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