Used Chroma's vector store to store and retrieve embeddings from large text datasets for accurate context generation.

Deployed a generative model (e.g., GPT) for generating relevant answers, using context retrieved via LangChain.

Applied RAG strategy to combine retrieval of documents and generation of coherent text for precise, up-to-date responses.

Leveraged LangGraph to build agentic workflows, where AI agents autonomously select and chain tools for complex tasks based on context and goal-driven reasoning.

Streamline document ingestion by transforming raw data into embeddings, then indexing them with Chroma for fast retrieval.

Enabled fine-tuning of the generative model using the retrieved context, optimizing the system’s ability to answer specific queries.

Maintained RESTful APIs serving 1M+ requests per day.

Troubleshoot and debug complex issues across the entire stack, identifying root causes and implementing solutions.

Test software thoroughly using unit, integration, and end-to-end tests, ensuring reliability and robustness before deployment.

Write clean, maintainable code by adhering to best practices, coding standards, and effective version control techniques.

Deployed applications to AWS (ECS, Lambda, API Gateway, RDS) with automated Terraform scripts.

Utilized CI/CD automation (Jenkins, GitHub Actions, Docker, Kubernetes), reducing deployment time.

Collaborate in cross-functional teams, working with product managers, designers, and other engineers to deliver quality software.