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Mid-level 3+ years requirement plus Bangalore location and moderate employer brand increases competition.
Core LLM and prompt engineering skills are broadly transferable across industries despite insurance domain preference.
Explicit 3+ years plus mandatory LLM frameworks, vector DBs and production engineering skills create strict filters.
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Build and maintain LLM harnesses, agent loops, tool integrations, and prompt engineering efforts to deliver AI features end-to-end.
Design and iterate retrieval-augmented generation (RAG) pipelines and manage embeddings and vector indexes to support AI productization.
Perform data parsing, accuracy validation, light ML tasks, and analysis to ensure AI feature quality and meet delivery commitments.
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or related technical field.
3+ years of AI or data science experience with hands-on LLM-based application development.
Strong Python skills including pandas, numpy, scikit-learn; experience with LLM APIs (e.g., Anthropic, OpenAI, Bedrock) and orchestration frameworks (LangChain, LlamaIndex, LangGraph).
Work Experience Required: 3+ years in AI or data science relevant to LLM application development.
Experienced in building and iterating agent harnesses and prompt engineering with strong analytical skills for data-driven AI design decisions.
Comfortable delivering production-quality code with engineering best practices (code review, CI/CD) in professional AI product environments.
Familiarity with RAG pipelines, embeddings, vector DBs, and light ML modeling, preferably with exposure to cloud AI services and structured evaluation methods.