Description

You will own the operational aspects of AI and ML systems.

Responsibilities

  • Develop and manage AI/LLM workflows and operational use cases.
  • Implement incident triage, log summarization, and root cause analysis for AI systems.
  • Trace issues across multi-step pipelines and asynchronous agents.
  • Leverage agentic AI architectures for complex workflow automation.
  • Script automation tasks using Python and interact with RESTful APIs.

Required Skills

  • 3-6 years of experience in software engineering, DevOps, or ML Ops.
  • Strong foundation in prompt engineering and LLMs (GPT, Claude, LLaMA).
  • Practical understanding of AIOps platforms or operational AI use cases.
  • Exposure to agentic AI architectures (LangGraph, AutoGen, CrewAI).
  • Proficiency in scripting using Python.
  • Experience with RESTful APIs and basic system debugging.
  • Familiarity with Aiml, Llm, Devops, Gpt, Claud, Ml technologies.
  • Ability to trace issues across complex pipelines.

Key Skills
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