AI Ops Engineer

16 hours ago

Pune, Maharashtra, India Jade Global Full time ₹ 20,00,000 - ₹ 25,00,000 per year

AI Ops Engineer2

Job TitleAI Ops EngineerExperience35 yearsAbout the RoleWe are seeking a hands-on and proactive AI Ops Engineer to operationalize andsupport the deployment of large language model (LLM) workflows, including agentic AIapplications, across Marvells enterprise ecosystem.This role requires strong prompt engineering capabilities, the ability to triage AI pipelineissues, and a deep understanding of how LLM-based agents interact with tools,memory, and APIs. You will be expected to diagnose and remediate real-time problems,from prompt quality issues to model behavior anomalies.

Key ResponsibilitiesDesign, fine-tune, and manage prompts for various LLM use cases tailored to Marvellsenterprise operations.Operate, monitor, and troubleshoot agentic AI applications, including identifying whetherissues stem from:Prompt quality or structureModel configuration or performanceTool usage, API failures, or memory/recall issuesBuild diagnostics and playbooks to triage LLM-driven failures, including handling fallbackstrategies, retries, or re-routing to human workflows.Collaborate with architects, ML engineers, and DevOps to optimize agent orchestrationacross platforms like LangGraph, CrewAI, AutoGen, or similar.Support integration of agentic systems with enterprise apps like Jira, ServiceNow, Glean, orConfluence using REST APIs, webhooks, and adapters.Implement observability and logging best practices for model outputs, latency, and agentperformance metrics.Contribute to building self-healing mechanisms and alerting strategies for production-gradeAI workflows.Required Qualifications

36 years of experience in software engineering, DevOps, or ML Ops with exposure toAI/LLM workflows.Strong foundation in prompt engineering and experience with LLMs like GPT, Claude,LLaMA, etc.Practical understanding of AIOps platforms or operational AI use cases (incident triage,log summarization, root cause analysis, etc.).Exposure to agentic AI architectures, such as LangGraph, AutoGen, CrewAI, etc.Familiarity with scripting (Python), RESTful APIs, and basic system debugging.Strong analytical skills and the ability to trace issues across multi-step pipelines andasynchronous agents.

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