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Vetted Retrieval-Augmented Generation Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in Generative AI agents and workflow automation
Mid-Level Full-Stack Engineer specializing in AI/ML and cloud-native web apps
Junior Software Engineer specializing in full-stack development and applied ML
Mid-level Software Engineer specializing in distributed systems and cloud microservices
Mid-level Full-Stack Software Engineer specializing in cloud-native healthcare and FinTech systems
Mid-level Machine Learning Engineer specializing in MLOps and Generative AI
Mid-level AI Engineer specializing in Computer Vision, NLP, and Generative AI
Mid-level AI/ML Engineer specializing in LLM fine-tuning and RAG for healthcare
Mid-level Data Analyst/Data Engineer specializing in machine learning and NLP
Mid-level AI Engineer specializing in retail personalization and LLM-powered systems
Junior Machine Learning Software Engineer specializing in cloud-deployed predictive models
Mid-level Data Scientist specializing in ML, NLP, and analytics for FinTech
Junior Machine Learning Engineer specializing in healthcare AI and GenAI RAG
Mid-level Full-Stack Software Engineer specializing in FinTech and cloud-native systems
Senior Full-Stack Software Engineer specializing in cloud-native FinTech and data pipelines
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.”
sai anuragh Sangoju
Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP
“Built and deployed a production LLM-powered university support chatbot on Azure using a RAG pipeline, focusing on reducing hallucinations, improving latency, and handling ambiguous queries via confidence checks and clarification prompts. Also has hands-on orchestration experience (Airflow/Azure Data Factory), including hardening a demand-forecasting ingestion workflow with sensors, retries, and automated alerts, and uses a metrics-driven testing/monitoring approach for reliable AI agents.”
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.”
revanth polthi
Mid-level Data Scientist specializing in Generative AI and MLOps
“GenAI/LLM engineer with production experience at Allstate building an end-to-end document intelligence workflow for insurance operations—automating document intake, classification, and risk signal extraction. Emphasizes high-reliability design for regulated/high-stakes outputs using schema enforcement, confidence thresholds, validation rules, and human-in-the-loop routing, with metric-driven offline evaluation and production monitoring.”
Mid-level Data Scientist & AI Engineer specializing in NLP, computer vision, and MLOps