Anirudh Kansal

About Anirudh Kansal

Here are some of my core skills that I implement in my daily tasksCore skills - System Design for building scalable GenAI solutions to handle infllow in millions- Advanced scientific methods for building frugal and cost effective solutions - Research science solutions and implement existing findings as per the current literatureMoreover, 4+ Years of Experience in building:1. AI Agents, Advanced RAG with semantic chunking and reranking and Autonomous CAMEL AGI agents2. Fine-tuning LLMs using LORA/QLORA on custom parameters for specific needs. Utilising SLMs. ChatBot (A conversational assistant) powered by RAG (Retrieval augmented generation). CAG (Custom Augmented Generation), ICL (In context learning). Implementing various prompting techniques for AI agents and routers. CoT (chain of thoughts), Cod (Chain of density) ReAct prompting (Reason+Action) with ReAct agents, Self consistency and moreAlso, have previously worked as a senior software developer. Have built Django rest apis. Database shredding, redis based caching, etc. Have also worked on creating data pipelines and scrapping pipelines using Selenium and BS4. Thus, having a core engineering background with a transition into science. Skills: Generative AI, Langchain, Data Science, Transformers, LLMs, Django, Selenium, Python. Email: a•••••••@gmail.com

Experience

1. Sr Prompt Engineer - Genai

   Amazon

   Apr 2025 — Present · Bengaluru, IN

   As a Senior GenAI Engineer, I am responsible for the following day-to-day activities - 1. Architect end-to-end GenAI workflows, designing pre-processors, post-processors, and defining the optimal LLM implementation strategy for each use case.2. Build high-fidelity prompt and context engineering frameworks leveraging In-Context Learning (ICL) for large-scale production systems.3. Develop and deploy scalable Python solutions via CI/CD, supporting multi-million request inflows with reliability and cost efficiency.4. Implement ML-based clustering for stratified sampling; experiment with RAG and Hybrid RAG architectures, vector databases, and deep-research autonomous web agents.5. Apply scientific experimentation and literature-driven methodologies to optimize accuracy, reasoning robustness, trust, and risk mitigation.

Education

• Central Board of Secondary Education

  10th, Junior High/Intermediate/Middle School Education and Teaching

• Govt. polytechnic, Ambala city

  polytechnic Diploma, Mechanical Engineering

• J.C. Bose University of Science and Technology, YMCA

  Bachelor of Technology - BTech, Computer Engineering