Sunil Rawat
Lead AI Software EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Lead Software Engineer with 7+ years in Node.js, TypeScript & Cloud
Senior Software Engineer with 6+ years of experience building scalable backend systems and cloud-native applications using Node.js, NestJS, TypeScript, and AWS. Specialized in event-driven architectures, microservices, Redis-based caching, and asynchronous processing using SQS and Lambda. Experienced in optimizing API performance, reducing infrastructure costs, and designing production-grade distributed systems. Strong frontend expertise in React with focus on scalable architecture, performance optimisation, and maintainable UI development. Recently focused on building AI-powered applications and LLM-driven APIs using Retrieval-Augmented Generation (RAG), vector search (Pinecone), semantic retrieval, and OpenAI tool/function calling for assistant-style backends.
Subharti University
MCA · Master of Computer Applications
August 1, 2018 – June 30, 2020
Happiest Minds Technologies
Module Lead | Senior Software Engineer
December 1, 2022 – Present
Noida, Uttar Pradesh, India
Shyplite
Software Engineer
June 1, 2022 – November 1, 2022
Gurgaon, Haryana, India
RNF Technologies
Software Engineer
April 1, 2021 – May 1, 2022
Noida, Uttar Pradesh, India
Xplorabox
Software Engineer
June 1, 2019 – March 1, 2021
Noida, Uttar Pradesh, India
AI Portfolio Assistant (RAG + Multi-Agent System)
January 1, 2024 – June 30, 2026
Built a multi-assistant AI backend using Node.js, OpenAI, Pinecone, and RAG. Implemented semantic retrieval using vector embeddings and cosine similarity search. Designed tool-enabled AI agents using OpenAI function calling. Developed a PDF ingestion and chunking pipeline with Pinecone vector indexing. Added real-time streaming responses using Server-Sent Events (SSE). Built a modular assistant architecture supporting multiple AI personas. Implemented dual retrieval using Pinecone vector search and local in-memory retrieval.
Cultural Fit Analysis
The candidate's project diversity, including an AI Portfolio Assistant and various full-stack applications, shows a breadth of interest and adaptability. Their experience across different companies and roles, from full-stack development to module leadership, suggests a proactive and growth-oriented mindset. The focus on AI/ML in recent experience and personal projects aligns well with an innovative culture.
Soft Skills & Operational Fit
The candidate demonstrates leadership qualities through their Module Lead role, mentoring junior engineers, and driving architecture decisions. Their experience in cross-functional collaboration and Agile/Scrum practices indicates good operational fit. The project descriptions are clear and highlight problem-solving and system design capabilities.