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Vetted LangGraph Professionals
Pre-screened and vetted.
Director-level Applied ML Engineer specializing in GenAI, LLM systems, and MLOps
Junior Software Engineer specializing in backend AI systems
Senior Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level Full-Stack Software Engineer specializing in web platforms and AI
Senior Software Engineer specializing in Python backend, microservices, and cloud/DevOps
Junior AI/ML Engineer specializing in Generative AI production systems
Mid-level AI Engineer specializing in LLM safety, red teaming, and evaluation
Mid-Level Full-Stack Software Engineer specializing in GenAI and cloud-native systems
Junior Full-Stack AI Developer specializing in multi-agent LLM systems on AWS
Junior AI/ML Engineer specializing in LLM applications, RAG, and multimodal computer vision
Mid-Level ML/AI Engineer specializing in LLMs, RAG, and multi-agent systems
Senior Data Engineer specializing in Machine Learning and Healthcare Data Platforms
Mid-level AI Engineer specializing in agentic LLM workflows and RAG systems
Jatin Soni
Mid-level Software Engineer specializing in Generative AI and scalable backend systems
“Backend/AI engineer with production experience in legal tech: built a high-scale licensing/subscription API (FastAPI/Postgres/Stripe) and shipped a RAG-based chatbot for an eDiscovery platform. Designed a robust legal document ingestion workflow that processes thousands of documents into a searchable vector index with clear retry/escalation logic, and has demonstrated measurable Postgres performance wins (200ms to 10ms) using EXPLAIN ANALYZE and composite indexing.”
Prasad Sadineni
Mid-level AI Engineer specializing in LLM fine-tuning, RAG, and agentic systems
“Building and deploying production in-house, domain-specific LLM chatbots for enterprises that cannot use third-party GPT tools due to internal policies. Focused on reducing latency and improving domain awareness using fine-tuning, continual learning, and advanced RAG/agent retrieval strategies, with experience orchestrating multi-agent workflows via LangChain/LlamaIndex and vector DBs (FAISS, Weaviate, Chroma).”