AI Security Analyst

About the role

The AI Security Analyst is responsible for identifying, assessing, and mitigating security risks associated with artificial intelligence (AI), machine learning (ML), and data-driven systems. This role bridges traditional cybersecurity with emerging AI-specific threats, ensuring AI systems are secure, compliant, resilient, and trustworthy across their lifecycle. The ideal candidate has a strong foundation in cybersecurity, understands AI/ML architectures and data pipelines, and can translate technical risk into actionable guidance for engineering, product development, and leadership teams. General Responsibilities Key participant in the overall development, support and maintenance of the service performance management process Organizes the creation and maintenance of a running catalogue of existing services offered by IT Analyzes, reviews and measures service level performance against agreed upon service level agreements with the business and operating-level agreements with service providers Works closely with the business and service providers to negotiate and agree on service level requirements of any proposed new services and changes to existing services Works with the business and service providers to define the proper metrics in evaluating service delivery quality and performance levels Key participant in producing regular reports on service performance and achievement to stakeholders Organizes and maintains the service level review process with the business and service providers Initiates any actions required to maintain or improve service levels Acts as a change agent to implement and manage quality improvement processes in service delivery management Experience / Qualifications A university degree required (i.e. Bachelors degree) or equivalent relevant work experience. Business ethics - Ability to practice and behave consistently and effectively in areas of business practice and conflicts of interest Communication - Ability to communicate effectively by getting the right message across to the right people at the right time on a regular basis Customer Orientation - Ability to meet customers' expectations by identifying and anticipating customers' needs and integrating these into work; ability to develop new added value for customers and act with the customer in mind Result orientation - Ability to take steps personally to ensure that mutual goals and performance targets are met within the appropriate timeframe Teamwork - Ability to work with others and work synergistically with fellow team-members Planning and Organizing - Ability to plan, prioritize and organize work and schedules in all areas to meet requirements Problem solving - Ability to reach logical conclusions to situations by appropriately analyzing the situation. Balances the benefits, risks and consequences of actions Time Management - Ability to assessing your ability to manage your time, and the effectiveness of your team to reach department objectives Conflict management - Ability to recognize and work towards a mutually agreeable solution when confronted with conflict Resilience - Ability to work under pressure and prioritize Assess security risks across AI/ML models, training data, pipelines, APIs, and deployment environments Identify and mitigate AI-specific threats such as data poisoning, model inversion, prompt injection, model theft, and adversarial attacks Design, and implement security controls for AI systems, including access controls, monitoring, and anomaly detection Develop a systemic vulnerability monitoring process based on custom and third-party agents, and other AI models, tools, and applications used within Sensata's architecture Conduct threat modeling and risk assessments for AI-enabled applications Support secure-by-design practices throughout the AI lifecycle (design, training, testing, deployment, and retirement) Contribute to AI security standards, policies, and guardrails aligned with organizational risk tolerance Monitor AI systems for misuse, abuse, and anomalous behavior Support incident response investigations involving AI systems or automated decision-making Develop playbooks for AI-related security incidents Additional Experience/Qualifications: Bachelor's degree in Cybersecurity, Computer Science, Engineering, or equivalent experience 5 + years of experience in cybersecurity, application security, cloud security, or related fields Hands-on experience with AI/ML platforms, frameworks, or workflows (model training, inference, MLOps ) Familiarity with AI threat models and attack techniques (adversarial ML, prompt injection, model leakage) Experience securing AI in cloud-native environments (containers, CI/CD, managed ML services) Knowledge of AI governance, model risk management, or responsible AI principles Relevant certifications 1+ years experience with: Ticketing systems (Such as Service Now), SIEM tools (such as Cylance, Falcon, or Carbon Black), DLP tools (such as Proofpoint), Vulnerability