Key Responsibilities

Design and develop LLMpowered agents and intelligent workflows to solve complex business problems.
Build and optimize RetrievalAugmented Generation (RAG) pipelines using embeddings and vector databases.
Engineer highquality prompts, including fewshot learning, structured outputs, and tool/function calling.
Implement texttoSQL and automated insight generation pipelines for analytics use cases.
Design and maintain evaluation frameworks to measure model accuracy, latency, reliability, and cost.
Collaborate closely with backend and platform teams to productionize, scale, and monitor AI systems.
Continuously experiment, debug, and improve model behavior through structured testing and iteration.

Required Skills

Strong handson experience in Python.
Practical experience working with LLM APIs (e.g., OpenAI, Anthropic).
Experience with LLM orchestration frameworks such as LangChain, LlamaIndex, or similar.
Solid understanding of embeddings, semantic search, vector databases, and RAG architectures.
Strong debugging, experimentation, and problemsolving mindset in applied AI systems.

Preferred / GoodtoHave Skills

Experience with MLOps / LLMOps tooling such as MLflow, Langfuse, Weights & Biases (W&B).
Exposure to multiagent systems and agent coordination patterns.
Domain experience in analytics, data platforms, or pharma/life sciences.
Knowledge of cost optimization techniques, model selection, and routing strategies across multiple LLMs.

Notice Period : Immediate to 30 Days

Location : PAN India

Data Scientist