AI Ops/ IT Automation Engineer (Agentic AI ITSM)

Looking to build and operate nextgeneration AIdriven IT operations in a modern enterprise environment? Join us as AI Ops / IT Automation Engineer and help transform IT service delivery through agentic AI, workflow orchestration, and intelligent automation.
Motivated by our values: Customer Champions, Growth Minded, Truth Seekers, Fast Movers, High Achievers, Respectfully Candid.

We are modernizing IT operations to deliver reliable, scalable, and employeecentric IT service experience. This role will help design, build, and run agentic AI workflows that improve selfservice adoption, reduce ticket volumes, and shorten timetoresolution while maintaining strong governance, auditability, and security.

This pivotal role requires expert understanding and handson knowledge of AIassisted ITSM automation, workflow orchestration, integrations, and enterprise platforms (Microsoft 365, Azure AD/Entra ID, endpoint management, and ITSM tooling), with working experience across an agentic AI ITSM studio (Agents, Workflows, Apps, AI Functions, Integrations, Knowledge, Triggers, Models, dashboards, and human collaboration).

• Serve as an AI Ops / IT Automation Engineer responsible for AIdriven IT operations and automation
• Lead technical investigation and architecture for agentic AI use cases that improve efficiencies and end user experience
• Build, configure, and maintain AI Agents for IT incidents, service requests, and employee selfservice
• Design, build, and operate Agentic Workflows including branching logic, retries/timeouts, approvals, and humanintheloop handoffs
• Develop and manage Agentic Apps and execution flows for repeatable ITSM and infrastructure automations
• Configure and operationalize AI Functions (classification, enrichment, summarization, extraction) with validation controls and safe writeback patterns
• Implement and maintain integrations using MCP, APIs, webhooks, and eventdriven Triggers to connect ITSM, identity, endpoint, and collaboration systems
• Build and curate Knowledge sources used by agents; ensure freshness, relevance, and governance of content
• Monitor and improve operational performance using dashboards, agent interaction traces, workflow execution logs, and run analytics
• Provide technical leadership on implementing automation, education, and selfserve tooling for incident and service request reduction
• Partner with information security teams to ensure leastprivilege access, secret management (API keys), auditability, and compliance for AIinitiated actions
• Serve as a technical expert for automation platforms, ITSM tooling, and escalatio
• 3+ years of experience as AI engineer or AI Ops Engineer.
• Strong understanding of IT service management processes (Incident, Request, Change, SLAs)
• Hands‑on working knowledge of an agentic AI studio, including Agents, Agentic Workflows, Agentic Apps, AI Functions, Integrations (MCP/APIs), Triggers, Agent Interactions, and model/settings administration
• Deep experience in integrating enterprise tools such as Nexthink, Zoom Contact Center (ZCC), IAM platforms (Okta, SailPoint), ServiceNow, and similar ITSM, identity, and observability tools
• Excellent analytical skills and experience of JavaScript and automation scripting to streamline operations (Python or PowerShell is a plus)
• Strong understanding of REST/SOAP APIs, JSON, authentication, and error integration (retries, timeouts, idempotency)
• Strong oral and written communications with excellent teamwork and interpersonal skills to deliver support and enablement
• Collaborative working style to be able to partner with technology and business stakeholders across the organization and influence technology decisions
• A strong track record of executing in a dynamic and fast‑paced environment

• Hands‑on experience working on ai, ServiceNow Agentic AI, Moveworks, Aisera, Kore.ai, or similar agentic AI / intelligent ITSM platforms
• Hands‑on experience with ServiceNow or comparable enterprise ITSM tools
• Experience designing human‑in‑the‑loop automation, confidence‑based execution, approval gates, and safe fallback to L2/L3 support
• Familiarity with AI model configuration, model governance, and operational controls (latency/cost tradeoffs, model selection, environment separation)
• Experience with workflow orchestration and low‑code/no‑code automation platforms
• Experience working with Large Language Models (LLMs), including prompt design, model selection, governance in production IT operations, and implementing Retrieval‑Augmented Generation (RAG) with curated enterprise knowledge sources
• Understanding of security and compliance practices for enterprise automation (RBAC, secrets, auditing, data handling)
• Experience using collaboration and knowledge platforms such as Confluence and Jira

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