DGN Technologies Inc

Job Title: AI Ops Engineer Experience: 35 years About the Role We are seeking a hands-on and proactive AI Ops Engineer to operationalize and support the deployment of large language model (LLM) workflows, including agentic AI applications, across Marvell’s enterprise ecosystem. This role requires strong prompt engineering capabilities, the ability to triage AI pipeline issues, 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 Responsibilities Design, fine-tune, and manage prompts for various LLM use cases tailored to Marvell’s enterprise operations. Operate, monitor, and troubleshoot agentic AI applications , including identifying whether issues stem from: Prompt quality or structure Model configuration or performance Tool usage, API failures, or memory/recall issues Build diagnostics and playbooks to triage LLM-driven failures , including handling fallback strategies, retries, or re-routing to human workflows. Collaborate with architects, ML engineers, and DevOps to optimize agent orchestration across platforms like LangGraph, CrewAI, AutoGen, or similar. Support integration of agentic systems with enterprise apps like Jira, ServiceNow, Glean, or Confluence using REST APIs, webhooks, and adapters. Implement observability and logging best practices for model outputs, latency, and agent performance metrics. Contribute to building self-healing mechanisms and alerting strategies for production-grade AI workflows. Required Qualifications 3–6 years of experience in software engineering, DevOps, or ML Ops with exposure to AI/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 and asynchronous agents. Good-To-Have Glean DevRev Codium Cursor Atlassian AI Databricks Mosaic AI Role & responsibilities Preferred candidate profile