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Mid-level seniority increases applicants, but niche LLM/vector DB skills and non-metro lesser-known company reduce competition.
Highly specialized LLM, vector DB, and agent frameworks require domain-specific experience, limiting transferability.
Explicit 5+ years and many mandatory LLM, vector DB, and production deployment skills.
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Own and develop the LLM Process Synthesizer to convert action events into verifiable process specifications using tools like Claude and structured outputs.
Build and optimize agentic workflows with LangChain/LangGraph including tool-calling agents and human confirmation flows.
Design, implement, and maintain retrieval architectures and RAG systems using embeddings, vector databases, and manage AI evaluation frameworks and cost/latency optimizations.
5+ years of relevant experience in Software Engineering, AI/ML, or Generative AI development.
Strong proficiency in Python and experience building production-grade LLM applications.
Experience with Anthropic Claude, OpenAI APIs, LangChain/LangGraph, RAG systems, and vector databases (pgvector, Qdrant, Pinecone, Weaviate).
Bachelor's degree in B.Tech/B.E. (CSE, IT, ECE) or equivalent.
Experienced in end-to-end AI system design and deployment on AWS with Docker and PostgreSQL-based infrastructure.
Skilled in AI evaluation methodologies including grounding checks, hallucination control, and AI observability.
Familiar with process mining or workflow modeling and knowledgeable about embedding fine-tuning, model monitoring, and data privacy/security best practices.