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Vetted Large Language Models (LLMs) Professionals
Pre-screened and vetted.
Senior Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Junior Software Engineer specializing in Generative AI and Cloud Microservices
Junior Software Engineer specializing in cloud-native backend and LLM applications
Mid-Level Full-Stack Software Engineer specializing in GenAI and cloud-native systems
Mid-Level Software Engineer specializing in ML and Generative AI applications
Mid-level Full-Stack Developer specializing in modern web apps and cloud platforms
Director-level XR Engineer specializing in AI-powered AR/VR training systems
Mid-level Data Analyst specializing in analytics, AI, and business intelligence
Mid-level Generative AI Engineer specializing in LLMs, RAG, and NLP systems
Senior Software Engineer specializing in backend ML and Generative AI platforms
Mid-level ML Engineer specializing in AI systems and LLM infrastructure
Senior Machine Learning Engineer specializing in Generative AI and MLOps
Sangram Jagtap
Mid-Level Full-Stack Software Engineer specializing in web platforms, cloud, and test automation
“Full-stack engineer with hands-on ownership of production systems, including a Kafka-based notification/alerting platform (Node.js + React) deployed on AWS with Docker/GitHub Actions, achieving ~95% email delivery reliability. Demonstrates strong operational maturity (observability, CI/CD, zero-downtime migrations) and experience shipping in ambiguous environments (SJSU project) with evolving requirements.”
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.”
Lando Ringel
Senior Unity Developer specializing in AR/VR, AI, and game systems
“Game developer with a distinctive niche in integrating LLM-driven dialogue directly into Unity gameplay, including a full web-hosted architecture using llama.cpp, FastAPI, and cloud GPUs for real-time NPC interaction. Also brings VR/mobile optimization experience from a drone simulation project at GovScio, combining AI systems thinking with practical 3D environment and performance work.”
Yasaswini Majety
Intern AI/ML Engineer specializing in LLMs, RAG, NLP, and MLOps
“Built and deployed a production RAG-based internal document Q&A system using LangChain, vector search, and a dockerized FastAPI LLM service. Focused on reliability by systematically reducing hallucinations and improving retrieval through prompt grounding/abstention strategies, chunking and top-k tuning, and iterative evaluation with logged metrics and manual validation.”
Venkata Bayarapuneni
Junior Full-Stack Developer specializing in JavaScript, Python, and cloud-deployed web apps
“Built and deployed a production LLM-powered travel assistant (Globe Trote) that automates end-to-end trip planning using a multi-step agent pipeline with RAG, external API calls, and enforced structured JSON outputs. Focused on reliability (validation, retries, fallback prompts, logging) and reported a ~30–40% reduction in irrelevant/generic responses after adding retrieval grounding.”