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Vetted LangChain Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in NLP, transformers, and RAG systems
Mid-level AI/ML Engineer specializing in LLMs, RAG, and enterprise AI
Mid-level Software Engineer specializing in full-stack AI and LLM applications
Mid-level Full-Stack Software Engineer specializing in AI platforms and LLM applications
Staff Software Engineer specializing in cybersecurity and AI platforms
Senior Data/GenAI Engineer specializing in cloud-native ML, RAG, and real-time data platforms
Mid-level Full-Stack Developer specializing in React, Node.js, and Spring Boot
Junior AI/ML Engineer specializing in agentic AI and cloud optimization
Mid-level Software Development Engineer specializing in backend systems and ML platforms
Mid-Level Software Engineer specializing in cloud-native backend and distributed systems
Mid AI/ML Engineer specializing in LLM systems and inference optimization
Junior AI/ML Engineer specializing in LLM agents and full-stack AI systems
Senior Software Engineer specializing in scalable backend and distributed systems
Senior AI Infrastructure & Backend Engineer specializing in LLM systems
Executive engineering leader specializing in SaaS platform transformation and AI
Senior AI Infrastructure Engineer specializing in LLM systems and real-time ML platforms
Peeyush Dyavarashetty
Intern AI/ML Engineer specializing in GenAI, LLMs, and agentic RAG systems
“AI/LLM practitioner who built a GPT-2-like language model from scratch at the University of Maryland using PyTorch and multi-GPU distributed training, with experiment tracking in Weights & Biases. As an AI Operations intern at ScaleUp360, delivered multiple production-style AI agent automations (Gmail classification and Fireflies-to-Claude workflows that extract and assign CEO tasks) and set up measurable evaluation using test cases and classification metrics.”
Surya Singh
Mid-level AI/ML Engineer specializing in FinTech and fraud detection
“ML/backend engineer with PayPal experience building high-stakes production systems, including a GenAI internal support assistant and a real-time fraud scoring pipeline. Strong in Python/FastAPI, model-serving infrastructure, RAG architecture, and production observability, with clear readiness to transition those backend patterns into a TypeScript stack.”