HCLTech—Technical Specialist

Job description

Description: Job Summary Senior subject-matter expert for the operations, observability, and lifecycle management of AI agents in production (“AgentOps” / LLMOps). Owns the frameworks and practices to safely deploy, monitor, evaluate, and continuously improve live agents — ensuring reliability, safety, cost-efficiency, and business-KPI performance across the Intel Agent Factory. Key Responsibilities - Define and operate the AgenticOps framework: agent registry, versioning, guarded rollout, and rollback for production agents. - Establish continuous evaluation and monitoring: quality, autonomy, safety (guardrails, Model Armor), latency, cost, and reuse metrics. - Implement observability and tracing for multi-agent systems (Agent Engine Observability, Cloud Monitoring/Logging/Trace). - Own the 5-gate validation-to-production process and post-release escape management for delivered agents. - Design human-in-the-loop (HITL) supervision, feedback loops, and automated pre-production simulations for safe rollout. - Track and report agent business KPIs (CSAT, TAT, MTTR, cost savings) via AgentScore / Agent 360 dashboards. - Drive cost governance for agent runtimes: model tiering, context caching, batch/flex inference, budget caps and alerts. - Collaborate with DevOps SME (deploy) and AI & Data SME (grounding) to close the build-deploy-operate-improve loop; advise Intel on AgenticOps ownership transfer. Skill Requirements - Strong LLMOps / MLOps / AgentOps experience operating GenAI or agentic systems in production. - Hands-on with Google Cloud agent runtimes: Vertex AI, Agent Engine, and observability tooling. - Agent evaluation and safety: eval frameworks, guardrails, Model Armor, HITL, prompt/robustness testing. - Monitoring, tracing, and reliability engineering (SRE) for AI workloads. - Cost governance and performance tuning for LLM/agent workloads. - Proficiency in Python; strong grasp of agent lifecycle and governance. Other Requirements - Experience with ADK, A2A, MCP, and multi-agent orchestration in production. - BigQuery/Looker for agent analytics and KPI dashboards. - Responsible-AI, model governance, and audit/compliance frameworks. - Prior enterprise-scale AI platform operations experience. - 9–12+ years in ML/AI platform operations, SRE, or LLMOps with production agentic/GenAI exposure (Tier 5–6). - Google Cloud Professional (ML/DevOps) certification preferred. - Offshore (India) with US overlap, or Onsite (USA) as required.