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Vetted Vector Databases Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in NLP, GenAI, and fraud/risk analytics
Senior Software Developer specializing in cloud-native microservices and GenAI/ML
Mid-level AI/ML Engineer specializing in LLMs, NLP, and MLOps
Mid-level GenAI/MLOps Engineer specializing in banking and healthcare LLM applications
Mid-level Machine Learning & AI Engineer specializing in LLMOps, digital twins, and RL
Mid-Level Full-Stack Engineer specializing in AI/ML and cloud-native web apps
Mid-level Software Engineer specializing in distributed systems and cloud microservices
Mid-level Machine Learning Engineer specializing in MLOps and Generative AI
Mid-Level Software Engineer specializing in ML and healthcare data systems
Senior Full-Stack Engineer specializing in AI-native SaaS and cloud infrastructure
Senior DevOps & Cloud Engineer specializing in Kubernetes, multi-cloud, and LLMOps
Sree Gautham Alluri
Mid-level Robotics & AI Developer specializing in autonomous navigation and LLM-powered robotic systems
“Robotics Support Engineer at HAI Robotics supporting a 385-robot warehouse fleet at a Shein client site. Built a production automation and reporting workflow to diagnose and resolve abnormal shelf locations, cutting incidents from ~250/day to ~25/day while providing actionable root-cause data to client/ops/maintenance. Hands-on ROS 2 (Humble) debugging across Nav2/localization/TF and sensor integration issues including QoS and firmware coordination.”
Adithya Gururaj
Junior AI Engineer specializing in agentic AI, RAG, and voice/telephony systems
“LLM/agent engineer who has built production multi-agent systems (LangChain/LangGraph) for enterprise workflows like email and calendar automation, with a strong focus on latency, tool-calling accuracy, and evaluation via LangSmith. Also worked on AI long-term memory using knowledge graphs at VEAI and communicated the approach and tradeoffs to CEO/CTO stakeholders.”
Vamsidhar Vuddagiri
Mid-level AI/ML Engineer specializing in LLMs, MLOps, and Azure
“AI/ML engineer who led Impacter AI’s production deployment of a specialized outreach LLM (CharmedLLM) fine-tuned on GPT-4.1, cutting API costs ~40% while boosting outreach effectiveness ~60%. Built the supporting MLOps and data infrastructure (MLflow, Kubernetes, PySpark, Kafka) and has agentic AI experience from University of Dayton, using LangChain + RAG and vector search (Pinecone) to improve reliability and reduce hallucinations.”
Mid-level AI Engineer specializing in LLM, RAG, and multi-agent systems
Principal Software Architect specializing in Healthcare IT and cloud-native systems
Executive AI/ML & Platform Technology Leader specializing in LLMs, GraphRAG, and security
Senior Full-Stack Engineer specializing in Python and AWS-native application development
Executive Engineering Leader (CTO/SVP) specializing in high-load platforms and GenAI/LLM 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.”