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Mid-level experience and metro location increase applicant density, but niche LLM-agent skillset reduces competition.
Core LLM agent skills transferable, but FinTech data and regulatory requirements increase domain specificity.
Explicit years plus mandatory LLM orchestration and observability requirements enforce strict shortlisting.
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Lead design, development, and deployment of scalable multi-agent AI systems integrating large language models for autonomous agentic workflows.
Build production-grade LLM workflows focusing on latency, cost, inference accuracy, and integrate them into financial analysis and decision-support applications.
Implement evaluation frameworks and security protocols to ensure predictable outputs, data privacy compliance, and mentor junior engineers while guiding the LLM infrastructure roadmap.
At least 4 years of professional software engineering or data science experience with production-grade software systems.
Minimum 2 years hands-on experience with orchestration frameworks like LangChain, LangGraph, ADK or equivalents for production applications.
Experience with function-calling integration (Model Context Protocol) connecting LLMs to data/microservices and setting up LLM observability frameworks (e.g., LangSmith, Phoenix, Arize).
Location requirement: Ahmedabad, India. Prior FinTech or financial API domain experience is highly preferred but not strictly mandatory.
Experienced in architecting and optimizing large-scale multi-agent AI systems for autonomous operation with strong production deployment skills.
Technically adept in advanced Retrieval-Augmented Generation (RAG) techniques and familiar with financial data contexts or interest in professional financial planning concepts.
Capable of owning technical mentorship and collaboration across product and data platform teams with a track record in high-impact applied AI products in FinTech or related sectors.