Head of Artificial Intelligence (Agentic AI Platform)
NorthStar HR Consultants
5 - 10 years
Pune
Posted: 12/02/2026
Job Description
Job Description - Director / Head of Agentic AI Platform & Digital Workers
Job Location - Pune, Maharashtra
Experience - 12+ years
Salary Budget - INR 60 lacs
Our client is hiring a Senior Engineering Leader to build from scratch, own, and scale an enterprise-grade Agentic AI Platform (Agentic AI Fabric) and a portfolio of production Digital Workers (agents) that execute real workflows safely across enterprise systems.
What this leader will own -
1) Build and own the platform (Agentic AI Fabric)
- Agent runtime/orchestration patterns for multi-step workflows (state, retries, queues/backpressure, approvals/HITL)
- Tool/action gateway and registry (governed connectors, allow lists, parameter validation, rate limits, rollback)
- Knowledge/RAG layer (ingestion pipelines, provenance, access controls, grounding and traceability)
- LLMOps/evaluations (versioned prompts/tools/policies, regression gates, safe rollouts, rollback)
- Observability and cost governance (telemetry, budgets/alerts, cost-per-transaction, SLOs/runbooks)
- Multi-cloud-ready architecture patterns (AWS first; extend to Azure later)
2) Build and scale agents as products
- Deliver a production-grade MVP agent and expand a portfolio of Digital Workers
- Establish a Next Agent Kit to accelerate subsequent agents (templates, tool patterns, eval harness, rollout checklists)
3) Enterprise agent security baseline (must-have)
This leader must set and enforce controls for:
- PII/PHI boundary controls and safe logging/data minimization
- Prompt/tool injection defenses
- Knowledge base poisoning protections (provenance, approvals/versioning, trust filters)
- Tool supply-chain integrity (registry governance, version pinning, scanning/SBOM)
- Privilege escalation controls and step-up approvals / separation of duties
Why this is a senior role
This is not an innovation lab position. It requires:
- shipping production systems under enterprise constraints,
- handling security/compliance scrutiny,
- orchestrating cross-functional teams (engineering, security, SMEs, delivery),
- and building something reusable and scalable (platform + agents).
Ideal candidate profile (what good looks like)
Must have
- 1218+ years in engineering/product/platform development
- 5+ years leading teams and complex delivery programs
- Track record building enterprise products/platforms (not just projects): multi-tenant SaaS, internal developer platforms, automation/workflow platforms, data/AI platforms
- Strong cloud architecture experience (AWS and/or Azure), including IAM/security, networking, and observability
- Hands-on familiarity with LLM applications (RAG + tool calling + evals/monitoring), and the realities of production deployment
- Experience with
Strongly preferred
Agent frameworks & orchestration
- Hands-on experience with agent/workflow orchestration frameworks such as LangGraph, CrewAI, AutoGen, and/or similar (e.g., LlamaIndex agents), including multi-step tool calling and human-in-the-loop patterns.
Automation/workflow platforms
- Experience with workflow automation / integration platforms such as n8n (or comparable low-code workflow engines) to rapidly compose actions and integrate enterprise systems.
Tool integration standards (optional)
- Familiarity with MCP-style tool servers/tool gateways and agent interoperability concepts (A2A-ready patterns), even if not fully implemented end-to-end.
- Has built or scaled a platform where customers/users rely on it daily (SLOs, on-call, release governance)
- Has shipped AI-assisted or autonomous workflow systems that integrate with enterprise apps (ITSM/CRM/ERP)
- Has worked in regulated contexts (BFSI/healthcare) or delivered audit-grade systems
Nice-to-have
- Familiarity with agent frameworks, interoperability concepts (A2A/MCP patterns), secure tool execution
- Experience packaging offerings / enabling GTM narratives for enterprise stakeholders
- Inference engineering and cost/performance optimization
- Experience building and operationalizing evaluation frameworks for LLM/agent workflows
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