.png){kind=logo}
Vetted FAISS Professionals
Pre-screened and vetted.
Mid-Level Full-Stack Software Engineer specializing in healthcare web apps and LLM integrations
Mid-level AI/ML Engineer specializing in LLM agents, RAG pipelines, and AI automation
Junior Machine Learning Engineer specializing in LLMs and multimodal AI
Mid-level Full-Stack Developer specializing in Java/Spring Boot, React, and AI/ML APIs
Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP/RAG
Mid-level Generative AI Engineer specializing in LLMs, RAG, and MLOps
Mid-level Full-Stack Developer specializing in React, Node.js, and AI automation
Junior Generative AI Engineer specializing in LLM systems and RAG
Entry-Level Software Engineer specializing in healthcare data and AI-enabled tools
Senior Data Scientist / ML Engineer specializing in NLP, speech AI, and computer vision
Mid-level AI/ML Engineer specializing in Generative AI, NLP, and RAG systems
Mid-level Software Engineer specializing in Python automation and GenAI on AWS
Junior Machine Learning Engineer specializing in Generative AI and LLM agents
Mid-Level Full-Stack Software Engineer specializing in web apps and AI-powered tools
Junior AI Engineer specializing in production RAG systems and GPU-accelerated inference
Lalith Kambala
Junior Full-Stack Engineer specializing in AI-powered web applications
“Full-stack product engineer who has shipped AI-powered job board moderation and validation features end to end across React/TypeScript, serverless backends, and Postgres. Stands out for combining UX polish, LLM-backed workflow design, and reusable async infrastructure patterns to improve reliability, speed of delivery, and user participation.”
Junior Software/AI Engineer specializing in LLM agents and RAG systems
Tejaswi devarapalli
Junior Software Engineer specializing in backend systems and AI infrastructure
“Built both a full-stack AWS file-processing pipeline and a production AI document Q&A system ('smart-doc'). Stands out for combining strong cloud engineering with practical LLM/RAG architecture, including hybrid retrieval, reranking, structured outputs, confidence-based retries, and production monitoring.”
Mounika Allu
Junior Full-Stack Engineer specializing in web applications and AI-assisted workflows
“Frontend-focused candidate with hands-on experience building a technically demanding AI-assisted survey/copilot interface at VSorts.ai while working as a research assistant at ODU. They show strong practical judgment around React architecture, TypeScript safety, and performance tuning, including diagnosing context-driven re-render issues and improving UX in real-time interactive applications.”
Shyamalan Kannan
Entry-level Software Engineer specializing in backend, AI systems, and full-stack development
“Solo builder of two technically ambitious products: Ghosted, a full-stack job search platform for international candidates navigating H-1B sponsorship data, and ContextForge, a Claude Code marketplace plugin that gives coding agents persistent memory and targeted codebase retrieval. Particularly strong in AI agent infrastructure, retrieval reliability, and end-to-end product ownership, with a fast release cadence and a habit of turning real failure modes into shipped improvements.”
Muhammad Midhat
Senior Full-Stack/Backend Engineer specializing in APIs, distributed systems, and AI integrations
“AI/backend engineer who has built and scaled production LLM-powered SaaS features (document assistant + compliance review agent) on a Node.js/TypeScript + Postgres/Redis stack deployed to GCP Kubernetes. Demonstrates strong production reliability chops—async queueing, autoscaling, observability, and database tuning—with quantified wins (p95 latency -60%, query 4s to <200ms) and robust AI guardrails (strict RAG, schema validation, citations, HITL).”
Sadir Ahmed Zidan
Junior AI/ML Engineer specializing in LLMs, RAG, and computer vision
“AI engineer with hands-on experience shipping production systems across semantic search, RAG/LLM applications, and computer vision. Built a personalized e-commerce search platform with measurable relevance and latency gains, and deployed grounded GenAI chat systems that significantly reduced hallucinations while lowering support burden. Also brings edge-deployment experience in monocular depth estimation and 3D reconstruction, suggesting strong breadth across modern applied AI.”