AI Security Analyst

Accountabilities:

• • Monitor enterprise AI usage across CASB, SWG, OAuth, endpoint, DLP, and other security telemetry to identify unauthorised AI applications, browser extensions, and API-based agents.
  • Classify AI security findings according to risk and escalate unauthorised or potentially harmful deployments for investigation and containment.
  • Investigate alerts involving autonomous agents and AI-powered workflows, including anomalous tool chains, unexpected data access, credential misuse, and emerging agent-based attack patterns.
  • Document investigation findings and coordinate remediation with automation, identity, security operations, and engineering teams.
  • Monitor AI usage and DLP logs for potential sensitive-data exfiltration through prompts, uploads, plugins, connectors, and other AI interfaces.
  • Tune and validate AI-specific DLP and detection controls to ensure they operate effectively and identify relevant security risks.
  • Monitor developer-facing AI tools for policy compliance, credential exposure, non-human identity risks, and other security concerns.
  • Partner with engineering teams to establish and maintain appropriate security guardrails for code-assistance and agentic development tools.
  • Maintain and validate AI activity logging, retention, and audit controls to ensure sufficient visibility and traceability.
  • Collect, organise, and maintain evidence supporting AI security audits, ISO 42001 certification activities, AI impact assessments, and regulatory readiness initiatives.
  • Analyse false-positive and false-negative trends and recommend improvements to detection thresholds, rules, and investigation logic.
  • Identify recurring security patterns and contribute them to automation and security-response playbooks.
  • Collaborate with Security Operations, Identity, Legal, AI/ML Engineering, and governance stakeholders to align findings with incident response and risk-management processes.
  • Translate technical security findings into clear, risk-based narratives for governance forums, leadership, and executive reporting.

  Requirements:

  • 3–5+ years of experience in security analysis, SOC, GRC, or a closely related cybersecurity role.
  • Working knowledge of SIEM platforms such as Splunk, Microsoft Sentinel, or Google Chronicle, as well as DLP and CASB technologies.
  • Understanding of AI and LLM security risks, including prompt injection, AI-enabled data exfiltration, model or agent misuse, and shadow AI.
  • Familiarity with non-human identity concepts, including service accounts, API keys, OAuth tokens, and their associated security risks.
  • Understanding of threat detection methodologies and frameworks such as MITRE ATT&CK; exposure to MITRE ATLAS or the OWASP LLM Top 10 is strongly preferred.
  • Ability to interpret security logs, API telemetry, and structured or unstructured investigation data.
  • Basic scripting or query skills in Python, SQL, SPL, KQL, or comparable technologies for security investigations and reporting.
  • Strong written documentation skills and the ability to communicate complex technical findings through clear, risk-based narratives.
  • Familiarity with cloud environments such as AWS, Azure, or GCP.
  • Demonstrated, hands-on AI security experience in at least one relevant area, such as AI/LLM risk testing, prompt-injection investigation, AI-specific data-exfiltration analysis, shadow AI discovery, CASB/SWG-based application discovery, non-human identity investigations, or agentic AI/MCP security.
  • Practical experience should include a specific example of identifying a security issue, investigating its underlying cause, and contributing to an outcome or remediation.
  • Exposure to agentic AI or MCP-based architectures from either a security or engineering perspective is valuable, including experience with technologies such as LangChain, AutoGen, CrewAI, or MCP servers.
  • Hands-on exposure to AI governance frameworks such as ISO 42001, NIST AI RMF, or EU AI Act risk classifications is advantageous, particularly through audit evidence collection or control testing.
  • Experience with security platforms such as Netskope, Zscaler, Wiz, Orca Security, Microsoft Purview, Abnormal Security, Bolster AI, or comparable technologies is a plus.
  • Exposure to ML-based anomaly detection or NLP-driven log analysis is beneficial.
  • Security certifications such as Security+, CISSP Associate, or relevant AI/ML security credentials are advantageous.
  • Strong analytical, investigative, problem-solving, and cross-functional collaboration skills.

  Benefits:

  • Remote working opportunity from India.
  • Opportunity to work at the intersection of cybersecurity, AI, governance, and emerging technology.
  • Exposure to enterprise-scale AI security, threat detection, data protection, and identity-security challenges.
  • Collaboration with multidisciplinary teams spanning security operations, engineering, identity, legal, automation, and governance.
  • Opportunities to contribute to AI governance and compliance initiatives, including ISO 42001 and emerging AI regulatory requirements.
  • Professional growth through hands-on work with evolving AI security technologies, frameworks, and attack patterns.
  • Inclusive and collaborative working environment.
  • Equal opportunity employment and reasonable accommodation for qualified individuals, in accordance with applicable requirements.