Specialist - Security And Compliance

Job Description

Technology…or technology that breathes life into work? SHL, People Science. People Answers.

This role within SHL’s Specialist - Security & Compliance function focuses on securing SHL’s adoption of Artificial Intelligence (AI), Machine Learning (ML), and Generative AI technologies across products and platforms. You will work closely with engineering, data science, DevOps, product, and cloud teams to identify risks, design secure AI architectures, and embed security controls across the AI/ML lifecycle.

You will play a key role in strengthening SHL’s AI security posture, enabling safe adoption of GenAI/LLMs, and protecting against emerging threats such as prompt injection, data leakage, model poisoning, and AI supply chain risks.

A great benefits package is offered in a culture where career development, ongoing manager assist, collaboration, diversity, and inclusivity are intrinsic to the way we work. SHL continues to invest heavily in AI and security, making this an exciting time to be part of something transformational. Hybrid working is available.

What You Will Be Doing

• Define and implement AI/ML security strategy, standards, and best practices aligned with industry frameworks (OWASP Top 10 for LLMs, NIST AI RMF).
• Perform threat modeling for AI/ML systems including LLM-based applications, model pipelines, and inference APIs.
• Identify and mitigate AI-specific threats such as prompt injection, jailbreaks, data poisoning, model inversion, and adversarial attacks.
• Conduct security assessments and reviews of AI/ML use cases, including third-party AI tools and integrations.
• Design secure AI architectures covering data pipelines, model training, model serving, and API integrations.
• Implement guardrails for LLM-based applications, including input/output validation, prompt filtering, and data protection controls.
• Perform AI red teaming and adversarial testing to validate model robustness and security.
• Integrate security controls into ML pipelines (MLSecOps), including CI/CD security, model validation, and artifact security.
• Secure AI workloads in cloud-native environments (AWS/Azure/GCP), including Kubernetes-based deployments.
• Work with CNAPP/CSPM tools to identify risks in AI workloads and cloud environments.
• Collaborate with data science and engineering teams to embed secure-by-design principles into AI development.
• Monitor AI systems for misuse, anomalies, and policy violations.
• Support incident response related to AI/ML security events and data exposure risks.
• Develop and maintain AI security policies, standards, and governance frameworks.
• Provide security guidance and awareness on AI risks to internal teams and stakeholders.
• Prepare dashboards, reports, and documentation for leadership, audits, and compliance requirements.
• Stay updated on emerging AI threats, vulnerabilities, and evolving regulatory requirements.
  
  

Essential

What we are looking for from you:

• Strong experience in Cyber Security (Application / Cloud Security) with exposure to AI/ML security.
• Good understanding of AI/ML lifecycle, including model training, evaluation, and deployment.
• Knowledge of LLM/GenAI security risks such as prompt injection, data leakage, and model abuse.
• Experience in threat modeling and secure architecture design.
• Hands-on experience with cloud platforms (AWS/Azure/GCP) and cloud-native security.
• Experience with DevSecOps / CI-CD security integration.
• Familiarity with APIs, microservices, and modern application architectures.
• Strong vulnerability management and risk assessment capabilities.
• Ability to translate complex AI risks into actionable security controls.
• Strong communication skills to work with cross-functional teams (engineering, data science, product).
  
  

Desirable

• Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch) or LLM platforms.
• Experience with OWASP Top 10 for LLMs or AI security frameworks.
• Exposure to vector databases, embeddings, and retrieval-based architectures.
• Experience in AI red teaming or adversarial ML testing.
• Knowledge of MLSecOps practices and secure AI pipelines.
• Exposure to eBPF-based runtime security (good alignment with modern cloud-native security).
• Experience supporting compliance frameworks involving AI governance.
  
  

Certifications (Preferred)

• Cloud Security Certifications (AWS / Azure)
• AI/ML certifications (Microsoft / Google / equivalent)
• CEH / OSCP (good to have)
  
  

Get In Touch

Find out how this opportunity can help you achieve your career goals by applying through our knowledgeable and friendly Talent Acquisition team. Choose a new path with SHL.

#CareersAtSHL #SHLHiringTalent #AI Security #GenAI #CyberSecurity

About Us

• We unlock the possibilities of businesses through the power of people, science and technology.
• We started this industry of people insight more than 40 years ago and continue to lead the market with powerhouse product launches, ground-breaking science and business transformation.
• When you inspire and transform people’s lives, you will experience the greatest business outcomes possible. SHL’s products insights, experiences, and services can help achieve growth at scale.
  
  

What SHL Can Offer You

Diversity, equity, inclusion and accessibility are key threads in the fabric of SHL’s business and culture (find out more about DEI and accessibility at SHL )

• Employee benefits package that takes care of you and your family.
• Support, coaching, and on-the-job development to achieve career success
• A fun and flexible workplace where you’ll be inspired to do your best work (find out more LifeAtSHL )
• The ability to transform workplaces around the world for others.
  
  

SHL is an equal opportunity employer. We support and encourage applications from a diverse range of candidates. We can, and do make adjustments to make sure our recruitment process is as inclusive as possible.

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