Vice President, Infrastructure Solution Engineer
On-sitePune, Maharashtra, India
Job Summary
Build and maintain Python-based AI workflows using LLM frameworks like LangGraph and LangChain to integrate with providers such as OpenAI and Azure OpenAI. Implement agentic patterns including multi-agent orchestration, stateful graph-based workflows, and human-in-the-loop flows while translating business SOPs into structured, executable agent workflows. Identify manual, repetitive business processes and architect automation solutions using AI agents equipped with relevant tools, ensuring agents operate with appropriate guardrails and fallback paths. Monitor agent performance, analyze failure modes, and iterate on prompts, routing, and tool definitions to drive high-ROI automation. Decompose complex requirements into well-scoped technical tasks and debug issues across the stack, from Oracle query plans to LLM hallucinations. Produce clear technical documentation for agents, workflows, and API contracts.
Required Qualifications
- Bachelor's or higher degree in computer science/ engineering or a related discipline, or equivalent work experience required
- Solid Python proficiency: familiarity with async/await, type hints, virtual environments, and packaging
- Hands-on experience with at least one LLM orchestration framework (LangChain, LangGraph, LlamaIndex, or equivalent)
- Experience consuming LLM APIs (OpenAI, Azure OpenAI, Anthropic, Cohere, etc.) and working with prompt engineering best practices
- Exposure to agentic AI concepts: tool-calling, function calling, ReAct patterns, RAG, vector stores
- Familiarity with FastAPI or similar Python API frameworks for serving AI pipelines
- Demonstrated ability to break down ambiguous business problems into technical requirements
- Strong debugging and troubleshooting instincts across multiple layers of a system
- Comfort reading and interpreting SOPs, business process documents, and workflow diagrams
- Familiarity with Git, CI/CD basics, Docker, and working in a team-based agile environment
- Ability to communicate technical concepts to non-technical stakeholders clearly
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