We’re seeking a visionary Senior Platform & AI Governance Architect to lead the design and implementation of a secure, scalable, and compliant Agentic AI platform — one that powers intelligent workflows across complex, multi-tenant environments.

If you’re passionate about shaping the future of AI at scale — where security, governance, and performance go hand-in-hand — this is your moment.

? What You’ll Own

You’ll architect and operationalize a next-generation AI Governance & Platform Engineering framework that enables safe, auditable, and enterprise-ready AI deployment. Your work will directly impact how teams across the organization build, deploy, and monitor AI agents — from ideation to production.

? Key Responsibilities

- Design and implement a multi-tier AI governance layer , including agent registries, tool/connector catalogs, identity-scoped permissions, and real-time guardrails across mission-critical workflows.
- Build and maintain an AI Use-Case Registry & Inventory with lifecycle tracking, vendor AI visibility, and unique use-case IDs for audit and compliance.
- Develop a Risk Tier Classification Engine to automate risk scoring, escalation triggers, and support for multi-tenancy and cross-domain risk modeling.
- Architect Logging & Traceability infrastructure capturing prompts, model versions, outputs, overrides, and timestamps — ensuring full auditability across use cases.
- Implement Kill-Switch & Rollback Controls with documented disable paths, owner assignments, and audit trails for rapid incident response.
- Champion native integrations with Microsoft and Databricks ecosystems — including Purview, Azure AI Foundry,



Copilot Studio, Unity Catalog, and MLflow — to reduce technical debt and improve maintainability.
- Drive multi-entity governance , ensuring data isolation, entity-level stewardship, and cross-entity auditability without data commingling.
- Define human oversight & escalation workflows , including routing logic, named owners, and cross-entity decision paths.
- Own deployment governance with 5-gate freeze rules, ADR integration, approval workflows, and exception management.
- Ensure compliance with FERPA, GLBA, SOC 2 Type II , and other regulated frameworks through policy-as-code and automated attestation.
- Deliver executive dashboards for spend visibility, risk posture, review cadence, and AI Control Authority reporting.
- Translate governance strategy into actionable technical designs, collaborating with Infrastructure, InfoSec, Compliance, and Engineering teams.

✅ Required Qualifications

- 6+ years of hands-on experience in platform engineering, solutions architecture, AI/ML engineering, or integration architecture — ideally in regulated or enterprise environments.
- Deep practical experience with AI/LLM engineering fundamentals : prompt versioning, tool calling, RAG, evaluation design, hallucination detection, and agent tracing.




- Proven track record in integration architecture — APIs, webhooks, iPaaS, MCP servers, and SaaS connectors.
- Strong cloud expertise across Azure , including Kubernetes, networking, secrets management, observability, and CI/CD pipelines.
- Solid grasp of security fundamentals : RBAC, SSO, OAuth, service principals, PII handling, data masking, and audit logging.
- Proficiency in SQL and data analytics — dashboards, cost attribution, trace analysis, event modeling, and warehouse/lakehouse concepts.
- Experience with governance & compliance frameworks — SOC 2, GDPR, retention policies, approval workflows, and evidence collection.
- Demonstrated product mindset — experience building tenant-level reporting, customer-facing controls, enterprise admin UX, or release gates.
- Solid understanding of enterprise systems architecture , interoperability, and the ability to evaluate and select AI governance tooling.

? Preferred Qualifications

- Experience designing or implementing AI governance frameworks (e.g., agent registries, risk tiering engines, deployment gate workflows) in production.
- Hands-on experience with Microsoft & Databricks-native AI/governance tools : Purview, Azure AI Foundry, Copilot Studio, Unity Catalog, MLflow.
- Familiarity with regulated-sector compliance (e.g., FERPA, GLBA).
- Built kill-switch, rollback, or incident-response mechanisms for AI or SaaS systems.
- Exceptional communication and documentation skills — able to articulate risk tradeoffs and governance recommendations to both technical and executive audiences.

📌 AI Platform Engineer (Governance Architecture & Platform Engineering) (Hyderabad)
🏢 ValueLabs
📍 Hyderabad