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Vetted Vector Databases Professionals
Pre-screened and vetted.
Junior Full-Stack Software Engineer specializing in web apps and AI-powered RAG systems
Ankit Kumar Nath
Mid-Level Full-Stack Developer specializing in web, mobile, and AI-powered applications
“Full-stack engineer who built a live-streaming edtech platform at KratosIQ, owning the entire frontend and the backend streaming layer. Notably migrated the system from a P2P mesh to an SFU architecture to handle scaling under heavy load, and delivered measurable React performance gains (450ms to 40ms render time) validated via Lighthouse and web vitals.”
Sai Krishna mekala
Mid-level Full-Stack Software Engineer specializing in cloud microservices and AI search
“Robotics software engineer focused on backend/integration for indoor autonomous mobile robots, with hands-on ROS 2 experience integrating Nav2/AMCL/TF2 and LiDAR/camera pipelines. Emphasizes production readiness—robust failure recovery, QoS-tuned distributed communication, and strong observability (logging/health checks)—validated through Gazebo simulation, sensor-data replay debugging, and Docker-based CI/CD deployment.”
Atharva Joshi
Mid-level GenAI Engineer specializing in RAG systems and AI agents
“LLM/agentic systems builder who has deployed production solutions for a resource management firm, using an MCP-driven architecture with Neo4j + Elasticsearch and a ChatGPT frontend to generate candidate/company “SmartPacks” and answer entity Q&A. Also built a LangGraph/LangSmith-orchestrated multi-agent workflow that automates data-infra change requests end-to-end (impact analysis, SQL + tests, and PR creation), and delivered a ~60% latency reduction through TTL-based context caching while improving accuracy via a business data dictionary.”
Othmane Benyoucef
Executive AI & Data Engineering Leader specializing in LLM, RAG, and agentic AI systems
“Founder of a consultancy for 14 years with extensive experience managing multiple clients and projects simultaneously. Interested in leveraging AI to solve operational challenges and is seeking exposure to the venture capital/studio/accelerator ecosystem despite no direct VC experience.”
Shravan Yadav
Mid-level Software Engineer specializing in cloud and FinTech systems
“Backend/AI engineer who has built and operated production Node.js/Express services on AWS (Postgres/Redis) and has hands-on experience shipping an AI-powered support agent using RAG (Pinecone + LLM) with grounding checks and evaluation for hallucination rate. Demonstrates strong production reliability/performance debugging, including reducing peak latency from ~2s back to sub-300ms through query and caching optimizations, plus designing agent workflows with retries and human-in-the-loop escalation.”
Ashutosh Srivastava
Senior Engineering Manager specializing in AI platforms and cloud-native backend systems
“Player-coach engineering leader who stayed hands-on (coding/reviews) while leading delivery, including designing an event-driven AI workflow engine with explicit state modeling and robust retries. Built near real-time enterprise analytics for campaign measurement and drove reliability/process improvements (observability, incident runbooks, release management). Introduced lightweight CI/CD and automated testing to cut release time by ~40% while maintaining quality.”
Mid-level Data Scientist specializing in Generative AI, RAG systems, and MLOps
Mid-Level Software Engineer specializing in cloud-native microservices and distributed systems
Mid-level Software Engineer specializing in AI and cloud-native data platforms
Mid-level Full-Stack Software Engineer specializing in cloud microservices and GenAI
Mid-level GenAI/ML Engineer specializing in RAG, semantic search, and LLM systems
Mid-level Machine Learning Engineer specializing in LLMs, Generative AI, and MLOps
Mid-level Full-Stack Software Engineer specializing in cloud, microservices, and AI integration
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level Generative AI Engineer specializing in LLM, RAG, and multimodal enterprise solutions
Senior Full-Stack Software Engineer specializing in AI-native enterprise products
Mid-level AI Engineer specializing in LLM agents and production ML systems
Sai Krishna Sriram
Mid-level Generative AI & ML Engineer specializing in production LLM and RAG systems
“AI/ML engineer who shipped a production blood-test report understanding and personalized supplement recommendation product, using a LangGraph multi-agent pipeline on AWS serverless with OCR via Bedrock and RAG over vetted clinical research. Also built end-to-end recommender system pipelines at ASANTe using Airflow (ingestion, embeddings/features, training, registry, batch scoring/monitoring) with KPI reporting to Tableau, with a strong focus on safety, evaluation, and measurable reliability.”
Dhruv Kamalesh Kumar
Mid-level Generative AI Engineer specializing in LLM agents and RAG applications
“GenAI builder and technical lead with ~2 years of hands-on production experience, including GENIE (a GenAI sandbox for ~44,000 Massachusetts public-sector employees) and A-IEP, a multilingual platform helping parents understand complex IEP documents (cut processing from ~15 minutes to ~2 and used by 1,000+ parents). Strong in RAG/agentic architectures, AWS serverless + Step Functions orchestration, and rigorous evaluation/guardrails for reliable real-world deployments.”
Sahil Gupta
Junior AI Software Engineer specializing in LLM agents, RAG, and healthcare NLP
“Backend engineer who built an agentic LLM system for private equity/finance that answers questions over enterprise contracts and documents using a vector-db RAG pipeline. Differentiator is a trust-focused citation framework (with highlighted source text) to reduce hallucinations in high-stakes workflows, plus strong DevOps experience deploying microservices on Kubernetes with Helm/GitOps and building Kafka real-time pipelines.”