About Vericence
Vericence is a digital engineering and technology consulting firm helping enterprises build AI-driven platforms, modernize legacy systems, and scale innovation through cloud, data, and intelligent engineering. We partner with global organizations to deliver high-impact technology solutions and build world-class engineering teams.

Role Summary
We are seeking an Agentic AI Engineer to design and deliver AI agents that operate against live cloud infrastructure. This is a hands-on build role: you will stand up agent workflows that interpret infrastructure state and telemetry, generate and validate Infrastructure-as-Code, and execute controlled remediation and provisioning actions under human-in-the-loop approval.
This is not a research or prototyping role. The expectation is working, governed automation deployed into a real workplace within the engagement window.

Key Responsibilities
- Build and deploy agentic workflows using an LLM orchestration framework (LangGraph, CrewAI, AutoGen, Semantic Kernel,



or cloud-native equivalents such as Bedrock Agents / Azure AI Agent Service)
- Design and implement tool/function-calling layers that expose infrastructure operations to agents safely — including MCP-based tooling where applicable
- Generate, review and validate Terraform modules programmatically;
integrate policy-as-code checks (OPA/Sentinel, tflint, checkov) into agent output paths
- Integrate agents with observability and ITSM systems (DataDog, ServiceNow, PagerDuty, Jira) for alert triage and automated ticket-to-action flows
- Implement guardrails: least-privilege execution roles, approval gates, dry-run/plan-only modes, audit logging of every agent action
- Build evaluation and regression harnesses for agent behaviour (accuracy, tool-selection correctness, failure containment)
- Wire agent workflows into existing CI/CD pipelines
- Document architecture and hand over to the client's platform team at engagement close

Required Skills
Agentic AI / LLM

📌 Agentic Ai Engineer (India)
🏢 Vericence
📍 India