Job Description :

Bachelor's degree with a minimum of 5 years of directly relevant work experience.

Tech Stack & Skills :

- Experience with LangChain, LangGraph, Semantic Kernel or AutoGen

- RAG (Retrieval Augmented Generation)

- Agentic AI observability

- Databricks, Snowflake, or similar platforms

- OpenAI

- Manage LLMOps/MLOps practices

Key Responsibilities :

- Design and implement scalable multi-agent services to automate complex decision-making processes for enterprise applications.

- Develop and optimize Retrieval Augmented Generation (RAG) pipelines to improve the accuracy and relevance of AI-generated outputs.

- Architect and maintain high-performance vector database integrations to ensure efficient data retrieval and semantic search capabilities.

- Collaborate with data engineering teams to leverage Databricks for large-scale data processing and model training workflows.

- Integrate Large Language Models (LLMs) into production environments using LangChain and LangGraph to build resilient, stateful AI applications.

- Monitor and refine model performance to ensure high reliability and low latency in production-grade AI services.