Sr. Agentic AI Engineer

We're looking for a Senior Agentic AI Engineer to design and build intelligent automation solutions for IT operations. You'll work on AI agents that can understand incidents and operational requests, reason over enterprise data, interact with IT systems and tools, and execute multi-step remediation workflows. The role also involves building AI-powered voice bots and conversational interfaces for IT operations and support. This is a hands-on engineering role spanning LLMs, agentic workflows, voice AI, integrations, and production systems.

Responsibilities:

• Design and build agentic AI systems for IT operations, service management, incident resolution, and workflow automation.
• Develop agents capable of reasoning, planning, tool use, orchestration, and autonomous task execution, with appropriate human-in-the-loop controls.
• Build integrations with enterprise IT systems such as ServiceNow, monitoring/observability platforms, ticketing systems, knowledge bases, APIs, and databases.
• Develop voice bots and conversational AI solutions for IT support and operational workflows, including speech-to-text, LLM reasoning, and text-to-speech pipelines.
• Design multi-step workflows for use cases such as incident triage, diagnosis, resolution, ticket automation, knowledge retrieval, and proactive IT operations.
• Build evaluation, monitoring, and guardrail mechanisms to ensure agents are accurate, reliable, secure, and production-ready.
• Optimize models and agent workflows for latency, cost, reliability, and business impact.
• Take solutions from prototype to production, including APIs, deployment, observability, testing, and continuous improvement.

Requirements:

• Strong software engineering experience with Python and production backend systems.
• Hands-on experience building LLM/generative AI applications and agentic workflows.
• Strong understanding of LLM APIs, tool/function calling, RAG, prompt engineering, structured outputs, and agent orchestration.
• Experience integrating AI systems with enterprise APIs, databases, and business applications.
• Experience with voice AI/conversational AI, including speech-to-text, text-to-speech, and voice-agent architectures.
• Experience with one or more agent frameworks such as LangGraph, LangChain, Semantic Kernel, LlamaIndex, AutoGen, CrewAI, or equivalent.
• Strong understanding of production concerns, including evaluation, observability, security, failure handling, latency, and cost optimization.
• Experience working with cloud platforms, APIs, Docker, and CI/CD.
• Ability to translate ambiguous business/IT problems into practical AI-powered solutions.