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Vetted Express Professionals
Pre-screened and vetted.
Mid-level Software Engineer specializing in backend systems for Insurance and Healthcare
Senior Full-Stack Developer specializing in cloud-native microservices and modern web apps
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices and FinTech
Junior Software Engineer specializing in full-stack web apps and REST APIs
Junior QA Engineer / SDET specializing in web, mobile, and API testing in banking
Senior Full-Stack Product Engineer specializing in AI, Cloud, and regulated domains
Mid-Level Software Engineer specializing in IoT platforms and data pipelines
Senior Backend/Infrastructure Engineer specializing in Python microservices and AWS
Mid-Level Software Engineer specializing in full-stack systems and authentication
Junior Backend/Systems Engineer specializing in distributed systems and security
Mid-Level Full-Stack Software Engineer specializing in FinTech and enterprise web apps
Senior Python Backend Engineer specializing in scalable APIs, cloud microservices, and AI/ML platforms
Senior Full-Stack Engineer specializing in Python, cloud-native microservices, and React
Senior Full-Stack Engineer specializing in SaaS, LegalTech, and Web3
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.”