Security Engineer III

Position: Security Engineer

Location: Hyderabad/Remote

Availability: Immediate joiner

Package: 12 LPA max

Experience: 4+yrs

What Youll Do

In this role you will:

• Design and implement the end-to-end security architecture for the Knowledge Platform — spanning identity, access control, secret management, agent governance, and data protection.
• Build the identity and SSO integration layer: platform user store and profile model, federated SSO via SAML 2.0 and OIDC, RBAC role taxonomy enforcement, platform secret store with envelope encryption, per-user data source credential vault, and token validation middleware for the API gateway.
• Design and implement the AI agent access controls and guardrails framework: agent registry as a first-class governed identity catalog, on-behalf-of (OBO) execution model, contextual action policies, agent context scope enforcement, runtime context guardrails, per-agent rate limits, and structured agent interaction logging.
• Build and enforce RBAC and ABAC systems for human users and AI agents — ensuring the platform treats agent access as structurally distinct from human access, with intersection enforcement when an agent operates on behalf of a user.
• Implement and own the platform secret store: envelope encryption, audit-logged credential access, zero-plaintext credential guarantees, and PAT / token revocation with < 60s propagation.
• Drive the PII detection, data classification, and sensitivity management pipeline: semantic classifier, sensitive tier tagging, lineage-driven classification propagation, masking and anonymisation detection, automated enforcement rule configuration, and audit and lineage trail.
• Build and manage comprehensive audit logging for all security-relevant events: credential access, agent interaction records, entity visibility classification changes, and access policy decisions.
• Lead security testing and vulnerability assessments; own security penetration testing for design partner beta and general availability.

Who Youll Work With

On our team, we:

• Are part of global engineering organization, responsible for building the technologies that power VantageCloud, our unified data and AI platform.
• Operate at the intersection of cloud computing, advanced analytics, and AI-driven automation to help enterprises unify and analyze data across hybrid and multi-cloud environments.
• Solve highly complex challenges in scalability, performance, interoperability, and intelligent automation to enable customers to turn data into insights and innovation.
• Collaborate across research, architecture, platform engineering, and product teams to shape the future of enterprise AI.
• This position reports into the AI engineering leadership team within global engineering organization.

What Makes You a Qualified Candidate

• Experience with IAM / RBAC / ABAC systems and cloud security (AWS, Azure, or GCP).
• Knowledge of security best practices and data governance frameworks.
• Experience with audit logging and compliance systems.
• Ability to design secure distributed systems.
• Hands-on experience with identity federation protocols: OAuth 2.0, SAML 2.0, and OIDC.
• Familiarity with agentic AI security challenges — agent permissioning, on-behalf-of execution, runtime guardrails — is a strong differentiator.

What Youll Bring

• Bachelors or Masters degree in Computer Science, Cybersecurity, or a related field.
• 4–7+ years in security engineering, IAM, or cloud security roles with a track record of shipping in production environments.
• Deep expertise in IAM systems: RBAC, ABAC, OAuth 2.0, SAML 2.0, OIDC, and enterprise IdP integration (Okta, Azure AD/Entra ID, Ping, ADFS).
• Experience with secret management systems (HashiCorp Vault, AWS Secrets Manager, Azure Key Vault, or equivalent) — including envelope encryption patterns.
• Experience securing distributed cloud-native systems: API gateways, service-to-service authentication, Zero Trust network patterns.
• Hands-on experience with audit logging, compliance frameworks (SOC 2, GDPR, EU AI Act), and data governance requirements.
• Experience designing or evaluating security controls for AI agent systems — agent identity, execution boundaries, and policy enforcement at runtime.
• Strong understanding of data sensitivity classification, PII detection approaches, and lineage-driven enforcement.
• Experience with penetration testing methodologies and vulnerability assessment tools.
• Excellent communication skills — able to articulate security architecture decisions to engineers, architects, and enterprise customers.