Posted:1 day ago|
Platform:
On-site
Full Time
We are seeking a hands-on and proactive AI Ops Engineer to operationalize and
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.
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
strategies, retries, or re-routing to human workflows.
· Collaborate with architects, ML engineers, and DevOps to optimize agent orchestration
· 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.
· 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.
Interested Candidates can share the resume: vikas.m@tekgence.com
Tekgence Inc
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