Abdul Rahman

Results-driven AIML Engineer with 2.8+ years at Amazon, specialising in production-grade Generative AI systems, LLM-powered multi-agent pipelines, classical ML, and data analytics. Deployed RAG-based AI agents in Amazon QuickSuite cutting manual review by ~40%, built ML models influencing $1.2M+ in sourcing decisions, and conducted deep-dive analytics to help stakeholders identify the right products for Amazon catalog entry. Proficient in LangChain, LangGraph, HuggingFace, FAISS, FastAPI, Python, and SQL.

Seeking a GenAI/LLM Engineer role to build intelligent, scalable AI systems.

AIML Quality Analyst (GenAI & ML Focus) - Amazon - Chennai, India

(2022-08)

Phase 2 – GenAI Agent Development (Jan 2024 – Present)

• Architected and deployed RAG-based AI agents within Amazon QuickSuite to automate quality-validation workflows, cutting manual review effort by ~40% across the catalog operations team.
• Integrated LLM-powered agents (using open-source models via HuggingFace) with internal knowledge bases, enabling natural-language querying of catalog policies and defect patterns — reducing average query resolution time by ~35%.
• Designed multi-turn conversational pipelines with context-aware memory using vector stores, improving agent response relevance and reducing escalations to senior analysts by ~25%.
• Collaborated with cross-functional teams (data engineering, product) to define prompt templates, evaluation rubrics, and guardrails for production LLM outputs, ensuring

B.E. - Electronics & Communication Engineering - Anna University, Chennai (2022)