Headline

AI Engineer 🧑‍💻 | AI Product Engineering| Building Agentic AI Applications

About

I’m an AI Engineer focused on building practical Agentic AI systems that turn LLM capabilities into working products. My work centers around RAG, agentic AI, multi-agent workflows and MCP-powered tools with a strong focus on the engineering needed to take AI features from prototype to deployment. I primarily work with Python & SQL and have hands-on experience with: • RAG pipelines, semantic search, query rewriting and reranking • LangGraph agents and multi-agent workflows • MCP / FastMCP and tool-using AI systems • LLM APIs including OpenAI, Anthropic, Groq and Gemini • FastAPI, Pydantic and REST APIs • PostgreSQL, pgvector, Supabase and vector databases • Docker, Linux and deployment workflows • LangSmith for tracing, evaluation and improving AI system quality I've worked as an AI Engineer Intern and Machine Learning Intern where I worked on AI research assistants, document intelligence, retrieval systems and ML-based applications. I enjoy taking ownership of problems end-to-end—from understanding the requirement and designing the workflow to building the backend, integrating models and tools, evaluating the system, deploying it and debugging real-world issues. Beyond implementation, I’m interested in the product side of AI: understanding user problems, translating business requirements into technical solutions, prioritizing what is worth building, communicating clearly with technical and non-technical stakeholders and iterating based on feedback. I enjoy working in environments where engineering, product thinking and execution overlap—where the goal is not simply to build an AI feature, but to build something useful, reliable and aligned with the actual needs of users and the business. I’m particularly interested in early-stage AI startups where I can work close to the product, communicate directly with the team, take ownership of problems, ship quickly and learn new technologies as the product evolves. 📌 Currently open to AI Engineer / Founding AI Engineer / AI Product Engineer / AI Engineering opportunities, including early-stage roles and opportunities where I can contribute across AI engineering, product development and execution.

Location

Mumbai Metropolitan Region

AI stack

claude code

langchain

langgraph

langsmith

CrewAI

Supabase

Work experience

Artificial Intelligence Intern at Stealth Startup (AI), Jun 2026 - Sep 2026 · 4 mos, Mumbai Metropolitan Region, • Built and deployed a production AI Assistant using LangGraph, RAG, FastAPI and Pydantic, translating product requirements into an end-to-end AI workflow and collaborating with engineering and product stakeholders to iterate on functionality and user needs. • Developed a document intelligence pipeline supporting PDF, DOCX and TXT using semantic chunking, OCR and Pinecone, improving retrieval latency by 10% while evaluating technical trade-offs, implementation effort and product requirements across document processing and retrieval approaches. • Designed stateful LangGraph workflows with conditional routing and query rewriting, improving multi-hop answer accuracy by 25% on internal evaluation datasets and working with the team to identify workflow improvements based on system performance, user requirements and practical use cases. • Implemented LangSmith tracing, latency and traffic alerts, LLM-as-a-Judge and evaluation workflows to monitor AI quality, investigate failure cases and support data-driven product and engineering decisions across retrieval and generation performance.

Machine Learning Intern at aiadventures, Feb 2025 - Apr 2025 · 2 mo, Pune India, • Built transformer-based NLP pipelines using PyTorch and Hugging Face Transformers for text classification, summarization and conversational AI, working closely with senior engineers to translate application requirements into practical ML workflows and evaluate results against task-specific objectives. • Deployed Scikit-learn classification models in collaboration with senior engineers, reducing prediction error by 15% compared with existing models and improving the accuracy and efficiency of downstream analytical workflows.

Data Analyst Intern at aiadventures, Jun 2024 - Jan 2025 · 8 mos, • Engineered SQL queries and Pandas transformations for automated feature extraction, reducing data preparation time by 30% and enabling faster model development and experimentation cycles. • Built automated data preprocessing workflows using Pandas and NumPy, reducing data preparation time by 35% through reusable transformations, feature scaling and streamlined preprocessing pipelines.

Education

AI Startup School, Building early stage Startups, Y Combinator

Bachelor's Degree, AISSMS Institute of Information Technology