.png){kind=logo}
Vetted Vector Databases Professionals
Pre-screened and vetted.
Mid-Level Full-Stack Software Developer specializing in Cloud Infrastructure and React/Node.js
Junior Software Engineer specializing in distributed systems and cloud infrastructure
Mid-level AI Engineer specializing in LLM automation and RAG systems
Mid-Level Backend Software Engineer specializing in AWS microservices and AI/automation
Junior AI Engineer specializing in RAG systems and full-stack development
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices and FinTech
Mid-Level Machine Learning Engineer specializing in LLMs and RAG systems
Junior Machine Learning Engineer specializing in deep learning and healthcare AI
Junior AI/ML Engineer specializing in RAG and multi-agent LLM systems
Mid-Level Full-Stack Software Engineer specializing in cloud microservices and mobile apps
Mid-level AI/ML Engineer specializing in cloud AI, MLOps, and NLP
Mid-level AI/ML Engineer specializing in MLOps, streaming data, and NLP/CV
Mid-level Backend Software Engineer specializing in AI-powered microservices and cloud infrastructure
Mid-level AI Engineer specializing in LLMs, RAG, and enterprise analytics
Mid-level Full-Stack AI Engineer specializing in agentic RAG and LLM fine-tuning
Mid-level Machine Learning Engineer specializing in distributed AI systems
Mid-level Full-Stack Software Engineer specializing in AI-powered document platforms
Naveen Kancharla
Mid-level AI & Backend Engineer specializing in RAG systems and scalable APIs
“Built and deployed a production LLM-powered document Q&A system using a strict RAG pipeline (LangChain-style orchestration + FAISS) to help users query large internal document sets. Demonstrates strong reliability focus through hallucination mitigation, curated offline evaluation with grounding checks, and production monitoring (latency/fallback rates) plus stakeholder alignment via demos and business metrics.”
Swarag Reddy Pingili
Junior AI/ML Software Engineer specializing in LLM agents and RAG systems
“AI/back-end engineer at Canon who helped build and operate an internal production LLM platform that acts as a secure middle layer between users and models, defending against jailbreaks/prompt injection while enabling RAG, memory, and grounded responses over company data. Experienced with LangChain/LangGraph orchestration, vector DB retrieval, and reliability practices (testing, monitoring, adversarial prompts) to run high-throughput, low-latency AI workflows in production.”