Prateek R.
Engineer Developer - Artifical Intelligence and Machine Learning @Motherson Technology Services
Signup · Get unlimited contacts
WORK HISTORY
Engineer Developer - Artifical Intelligence and Machine Learning @Motherson Technology Services
Currently working on multiple Generative AI and NLP projects.Development with Bloom, Llama, Gemma, Mistral, Stable Diffusion, Open AI and Zephyr Instruct and chat models. RAG implementation using llama-index, langchain, Amazon Bedrock/QR & D using GANs, CGANs, DCGANs and LLMs.Skills: Prompt engineering, LlamaIndex, DS.Py, LangChain, GraphRAG, AI Agents, LangSmith, FAISS and PineCone Vector stores, Unsloth Fine-Tuning: LoRa, QLoRA
EDUCATION
Cambridge School Greater Noida
Class 10th, Science
Anglia Ruskin University
Bachelor of Engineering - BE Hons, Computer Engineering
Delhi Public School Noida
Class 12th, Physics, Chemistry, Math and Computer Science
ABOUT PRATEEK R.
I am an AI/ML Engineer specializing in Generative AI, Agentic Systems, and large-scale LLM-driven applications, with a strong focus on building production-grade solutions that deliver measurable business impact.Over the past 3+ years, I have designed and deployed end-to-end intelligent systems across enterprise environments, combining multi-agent orchestration, Retrieval-Augmented Generation (RAG), and knowledge-driven architectures. My work sits at the intersection of applied AI and real-world problem solving, translating complex business requirements into scalable, reliable AI systems.At Motherson Technology Services Limited (MTSL), I have led the development of multiple high-impact AI platforms, including:• A multi-agent NL2SQL analytics system for CAPEX forecasting, integrating knowledge graphs and self-correcting agent loops• An enterprise Knowledge Management System with hybrid semantic search, RBAC via metadata filtering, and multilingual agentic interfaces• “Legal Lens,” a contract intelligence platform for clause extraction, comparison, and contextual Q&A using LLMs• Advanced RAG systems for warranty analytics, surfacing root-cause insights from global dataMy core expertise includes:• Agentic AI and multi-agent workflows (LangGraph-based orchestration)• LLM systems design (prompt engineering, fine-tuning including LoRA/QLoRA)• RAG pipelines with hybrid search (vector and keyword)• Knowledge graphs and contextual reasoning systems• Cloud-native AI deployments on Azure and AWSI work extensively with frameworks such as LangChain, LangGraph, and LlamaIndex, and have hands-on experience with models across GPT, LLaMA, Mistral, and other open-source ecosystems. My approach emphasizes system design, reliability, and alignment with business objectives rather than isolated model experimentation.Earlier, at Temporal Research Ltd, I developed Generative AI solutions for audit automation, achieving significant cost reductions through intelligent process transformation.I am particularly interested in the evolution of Agentic AI systems, where autonomous workflows, reasoning loops, and tool-augmented LLMs move from experimentation to production-grade decision systems.I am currently focused on advancing scalable, secure, and interpretable AI architectures that can operate reliably in enterprise environments.
This profile is compiled from publicly available professional sources. Unifers is not affiliated with or endorsed by LinkedIn. Request removal of this profile.