AI Cybersecurity Consultant

Who We Are

At Kyndryl, we design, build, manage and modernize the mission-critical technology systems that the world depends on every day. So why work at Kyndryl? We are always moving forward - always pushing ourselves to go further in our efforts to build a more equitable, inclusive world for our employees, our customers and our communities.

The Role

As an AI Cybersecurity Consultant, you'll help protect confidentiality, integrity, and availability in a world where AI is increasingly embedded in business processes, developer workflows, and security tooling. Your expertise will be used to evaluate, design, and implement security controls that protect AI systems end-to-end, including data, models, prompts, pipelines, infrastructure, integrations, and user experiences.

You'll work closely with clients to understand their AI goals and risk appetite, then assess current maturity across AI governance, Responsible AI, security-by-design, and MLOps/LLMOps controls. You'll translate that into actionable guidance, control designs, and measurable roadmaps that teams can implement.

This is not a "powerpoint-only" role. You will contribute hands-on by helping teams implement guardrails such as secure AI reference architectures, threat modeling and AI red teaming approaches, model and prompt security patterns, secure RAG designs, identity and secrets controls for AI services, monitoring and detection for AI misuse, and incident response playbooks tailored to AI-specific attack paths.

You will also help customers use AI to improve security in a controlled and auditable way. This may include introducing AI-assisted SOC workflows for triage and enrichment, automating parts of risk assessment and reporting, accelerating detection engineering, and defining governance for AI usage in security to ensure it is safe, transparent, and aligned with compliance needs.

• Minimum of 3+ years of experience in information security consulting and implementation, with a strong understanding of security principles, practices, and technologies
• Bachelor's degree in Telecommunications Engineering, Computer Science, Information Systems, or another STEM discipline (or equivalent professional experience).
• Solid cybersecurity foundations, demonstrated through project experience in areas such as IAM, application/API security, cloud/infrastructure security, data protection, logging/monitoring, incident response, or governance and risk.
• Experience participating in security and risk assessments and translating results into implementable controls, roadmaps, and operational procedures.
• Strong communication skills, both written and verbal, with the ability to explain security risks and recommendations to technical and non-technical audiences.
• Motivation and ability to learn quickly in fast-evolving domains; prior exposure to AI-enabled solutions is valued, but not mandatory.

• Master's degree or formal training in AI/Data Science (or equivalent practical experience building or securing AI-enabled solutions).
• Practical exposure to AI/ML or GenAI systems (e.g., LLM-based applications, RAG patterns, model deployment/hosting, prompt/tool orchestration) and an understanding of typical security risks and failure modes.
• Experience contributing to Responsible AI practices, such as governance, model risk management, human oversight, transparency, evaluation, and documentation.
• Familiarity with AI security and governance frameworks (e.g., NIST AI RMF) and awareness of regulatory and privacy expectations relevant to AI deployments.
• Experience with security automation and analytics (SIEM/SOAR, detection engineering, threat intelligence pipelines) and the ability to introduce automation responsibly.
• Scripting/programming for security and automation (Python is a plus) and the ability to prototype proof-of-concepts or accelerators.