Key Responsibilities

Governance Architecture & Platform Engineering

- Architect and implement an Agentic AI Governance layer, including an agent registry, tool/connector catalog, identity-scoped permissions, and real-time guardrails on LLM and tool-call outputs across student journey workflows.
- Design and maintain an AI Use-Case Registry & Inventory, providing central intake, vendor AI inventory tracking across CRM/LMS/SIS, unique use-case IDs, lifecycle state tracking, and entity-level visibility.
- Build a Risk Tier Classification Engine supporting automated and policy-driven multi-tier assignment, risk scoring, escalation triggers, and support for multi-tenancy and cross-domain risk axes.




- Design and maintain Logging & Traceability infrastructure capturing prompts/hashes, model version, output type, override flags, and timestamps, ensuring a full audit trail for the multi-tier use cases.
- Architect Kill-Switch & Rollback Controls, including documented per-use-case and per-vendor-feature disable paths, rollback documentation, kill-switch owner assignment, and auditability of disable events.
- Evaluate and recommend the most appropriate AI governance, evaluation, and observability tools and frameworks, balancing scalability, integration, and maintenance considerations.

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📌 Governance AI (Hyderabad)
🏢 ValueLabs
📍 Hyderabad