PrasadC

@prasad_ai_dev

Generative AI Engineer

Großbritannien
Englisch
Einige Informationen werden in englischer Sprache angezeigt.
Über mich
Hi, I'm Prasad, a London-based Generative AI Engineer specializing in production-grade LLM, RAG, and agentic systems. I build secure, scalable architectures using Azure OpenAI, AWS Bedrock, LangChain, and vector databases. My track record includes 95%+ accurate multi-modal extraction, AI assistants managing 30k+ monthly interactions, and reducing infrastructure costs by 98%. From hybrid retrieval pipelines to autonomous automation platforms, I engineer safe, corporate-ready AI solutions. Let's design an optimized infrastructure that scales with your company.... Mehr lesen

Kompetenzen

p
prasad_ai_dev
PrasadC
offline • 
Durchschnittliche Antwortzeit: 1 Stunde

Meine Dienstleistungen

KI-Implementierung und -Bereitstellung
I will build a production ready hybrid rag pipeline and ai chatbot

Portfolio

Arbeitserfahrung

Axiata

Engineer Data Engineering & AI

Axiata • Vollzeit

Aug 2025 - Mar 2026 • 7 mos

• Designed and delivered production-ready RAG systems using Azure OpenAI, LangChain, Qdrant, and Python, serving engineering teams across multiple business units and reducing engineering information discovery time from hours to seconds. • Designed hybrid retrieval pipelines across enterprise documents, combining keyword and dense vector search, improving retrieval precision by 35% and contextual relevance. • Built enterprise knowledge mining and retrieval solutions, integrating human-in-the-loop evaluation frameworks to improve response quality and reduce hallucinations. • Designed Generative AI architectures for RFP/RFI solutions, aligning model selection, inference optimization, and scalability requirements.

Fiverr

Python Developer

Fiverr • Freiberufler

Mar 2020 - Jan 2023 • 2 yrs 10 mos

• Delivered 20+ Python-based automation, ML, and NLP systems for diverse clients, including supervised text classification and document processing pipelines. • Designed model validation workflows with performance monitoring and evaluation metrics to ensure production readiness.