Asreetha Mukkara - AI Engineer - Sequoia Applied Technologies

Summary

Results-driven AI Engineer specializing in Agentic AI, Retrieval-Augmented Generation, and Large Language Models. Expertise in developing innovative pipelines and integrating advanced AI models to enhance bioinformatics workflows.

Overview

1

year of professional experience

Work History

AI Engineer

Sequoia Applied Technologies

06.2025 - Current

GenXflo

Developed GenXflo, a no-code bioinformatics platform that transforms visual workflow graphs into production-ready Nextflow DSL2 pipelines, enabling researchers to efficiently design and deploy complex workflows without coding expertise.
Built a Retrieval-Augmented Generation (RAG) pipeline that retrieves relevant tool documentation, component schemas, and workflow context to generate grounded bioinformatics tool configurations and reduce LLM hallucinations.
Developing an agentic AI pipeline builder that translates natural-language requirements into workflow DAGs, discovers compatible components through MCP tools, and iteratively corrects pipeline validation errors.
Integrated OpenAI and Gemini models with FastAPI, structured outputs, MongoDB caching, and deterministic validation, enhancing reliability and consistency of AI-generated responses in bioinformatics applications.
Implemented human-in-the-loop controls to validate AI-generated pipelines and require user approval before applying workflow changes.

Education

Bachelor of Technology - ISE

Jain University

Bengaluru, India

04.2001 -

Skills

Generative AI: Agentic AI, Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), Prompt Engineering, Model Context Protocol (MCP), Tool Calling, Structured Outputs, Human-in-the-Loop (HITL), LLM Evaluation

Languages & Frameworks: Python, FastAPI

Databases & Infrastructure: PostgreSQL, Docker, Docker Compose, REST APIs, Microservices