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Metro Bangalore, popular AI/LLM title, mid-level experience and broad skillset create high applicant competition.
Core LLM and ML engineering skills transfer across industries, though document/regulatory domain experience provides advantage.
Explicit 3+ years plus required LLM, orchestration frameworks, vector DBs and production engineering imply high strictness.
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Own development and maintenance of LLM harnesses including agent loops, tool integrations, context management, retries, and failure handling using or extending frameworks like LangChain and LlamaIndex.
Design, iterate, and version prompts with structured experiments and evaluation datasets to optimize AI feature accuracy and quality.
Build and operate Retrieval-Augmented Generation pipelines and manage embeddings and vector indexes for high-quality document retrieval and AI feature delivery.
3+ years of experience in AI or data science with hands-on development of LLM-based applications.
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related technical field.
Strong Python programming skills with experience in standard data science libraries (pandas, numpy, scikit-learn).
Proven experience in LLM harness engineering, prompt engineering, use of orchestration frameworks (LangChain, LlamaIndex, LangGraph), and vector databases.
Experienced in building production-grade AI features, comfortable writing clean, tested code with CI/CD practices.
Strong analytical and experimental mindset for iterative prompt and model evaluation using structured datasets.
Familiarity with agent frameworks, AI evaluation harnesses, cloud AWS services (Bedrock, SageMaker, OpenSearch), and lightweight ML modeling, ideally with domain knowledge in document-heavy or regulated sectors.