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Vetted Vector Databases Professionals
Pre-screened and vetted.
Iaroslav Kuznetsov
Mid-level Machine Learning Engineer specializing in AdTech and scalable data systems
“Built and scaled an internal AI code-search/assistant agent that expanded from engineering-only to broader internal users, tackling legacy code and inconsistent standards to make a RAG pipeline production-ready. Uses a metrics-driven approach (user feedback + automated Python evaluation for retrieval relevance and latency) and has handled high-pressure outages, including moving parts of the stack off AWS and adopting Milvus on internal infrastructure for resilience.”
Rutu Ketankumar Shah
Mid-level Software Engineer specializing in AI automation and backend systems
“Hands-on automation and QA-focused developer using AI agents, MCP tools, and LLMs to streamline business workflows. Built agents for automated Jira bug logging, executive summary dashboards, and a rule-explainer that translates technical business rules into plain language for end users, while also supporting Selenium-to-Playwright migration and guiding peers on AI implementation.”
Sarang Pratham
Junior Software Engineer specializing in data engineering and GenAI
“Built and deployed a production LLM-powered recruitment chatbot that automates key recruiting steps (sourcing, candidate engagement, screening). Strong in agent orchestration with LangGraph, including guided graph-based workflows, context-aware routing, and reliability measures like clarifying steps plus human-in-the-loop evaluation.”
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).”
Aditya Reddy Gunda
Intern AI/ML & Data Engineer specializing in deep learning, NLP, and cloud data pipelines
“AI/ML practitioner with production experience building a RAG-powered contextual customer support agent, optimizing for low latency using vector databases and smaller LLMs. Also deployed a fraud detection model on Kubernetes with auto-scaling for heavy transactional loads, and improved chatbot accuracy by 15% through metric-driven testing and evaluation. Partners with Marketing on personalization/recommendation initiatives with measurable outcomes tied to customer feedback.”
Entry-Level Full-Stack AI Engineer specializing in RAG pipelines and enterprise SaaS
Entry-level Tech Lead and UI/UX Designer specializing in AI and web development
Junior Full-Stack Software Developer specializing in cloud-native apps and data/AI
Junior Full-Stack AI Engineer specializing in React, Next.js, and AI-powered products
Junior Machine Learning Engineer specializing in LLMs, RAG, and fine-tuning
Mid-level Software Engineer specializing in full-stack and FinTech systems
Mid-Level Full-Stack Software Engineer specializing in AWS and RAG pipelines
Mid-level AI/ML Engineer specializing in LLMs and RAG systems
Senior AI/ML Engineer specializing in NLP, LLMs, speech, and computer vision
Senior AI/ML Engineer specializing in NLP, LLMs, speech, and computer vision
Junior Software Engineer specializing in AI/ML, data pipelines, and real-time dashboards
Senior AI/ML Engineer specializing in NLP, LLMs, speech, and computer vision
Senior AI Engineer specializing in LLMs, agentic systems, and ML infrastructure
Mid-level Machine Learning Engineer specializing in Generative AI and healthcare NLP
Ramis Hasanli
Intern Cybersecurity Engineer specializing in AI agents and production workflows
“Built and deployed an AI customer representative for iCore used at the IEE convention (2025), serving 100+ users in a day; implemented RAG with a vector database and scaled reliability via Docker and Google Cloud. Also has hands-on experience with multiple agent orchestration stacks (LangChain/LangGraph, Google AI Agent Development Kit, OpenAI SDK, Composio) and has delivered stakeholder-driven apps using prototyping and MVP scoping.”
AungKaung Khant
Junior Software Engineer specializing in full-stack web and IoT development
“Computer Science student and indie hacker who builds open-source products in public, including a Chrome extension called "Add to ChatGPT" that reached 30+ installs in its first week. Has hands-on experience with full-stack social platform development and AI-integrated side projects, with a strong pattern of self-teaching, rapid shipping, and iterative bug fixing.”
Entry-Level Software Engineer specializing in backend services and applied ML
Richa Chanpuriya
Mid-level Backend/Agentic AI Engineer specializing in GenAI automation and RAG systems
“Built and shipped a production AI-driven privacy automation system that autonomously navigates data broker sites to submit opt-out/data deletion requests end-to-end, including robust CAPTCHA detection/solving (e.g., reCAPTCHA/hCaptcha/Cloudflare) via 2Captcha. Experienced in orchestrating stateful LLM agent workflows with LangGraph and hardening them for production with strict state management, retries/fallbacks, validation layers, and database-backed observability/audit logs, collaborating closely with legal/compliance stakeholders.”