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Vetted Retrieval-Augmented Generation Professionals
Pre-screened and vetted.
Tharun Chowdary Malepati
Mid-level AI/ML Engineer specializing in GenAI, NLP, and production MLOps
“AI/LLM engineer who built and deployed a production healthcare RAG chatbot ("DoctorBot") with strict medical safety guardrails, an 85% confidence-gated verification layer, and latency optimizations that cut responses from ~8s to ~2–3s. Also worked on finflow.ai to generate finance/banking test cases from BRDs, collaborating closely with non-technical domain stakeholders, and has hands-on orchestration experience with LangChain/LangGraph and agentic evaluation/monitoring practices.”
Ankit Venkatesh
Mid-level AI Engineer specializing in full-stack AI and automation systems
“AI/ML engineer with hands-on experience owning production deployments from discovery through post-launch stabilization, including real-time computer vision/OCR systems and LLM-powered RAG workflows. Stands out for translating messy customer workflows into reliable backend services, debugging non-deterministic retrieval issues, and hardening AI systems with validation, monitoring, and human-review fallbacks.”
Sam Nick
Senior AI/ML Engineer specializing in Generative AI, LLMs, and NLP
“ML/AI engineer with hands-on experience building healthcare and fraud-detection systems from experimentation through deployment, monitoring, and retraining. Stands out for combining real-time IoT pipelines, cloud-native MLOps, and GenAI/RAG in regulated healthcare settings, with reported impact including reduced emergency response times and a 25% reduction in manual diagnosis time.”
Jenay Brown
Mid-level Cloud Support specialist with AWS infrastructure, networking, and serverless experience
“Early-career automation/workflow builder who has owned small-scale end-to-end implementations (discovery through stabilization), using tools like Zapier, Google Sheets, and Airtable with strong validation and troubleshooting habits. Built and tested a production-style RAG application on AWS Bedrock (S3 + Knowledge Bases + embeddings + OpenSearch + retrieve-and-generate) with a Streamlit UI to deliver more grounded, context-aware document Q&A.”
Junior AI Engineer specializing in LLM agents, RAG, and MLOps
Mid-level Generative AI Engineer specializing in LLMs and RAG for enterprise and FinTech
Junior Machine Learning Engineer specializing in computer vision and LLM/VLM systems
Junior Applied AI Engineer specializing in conversational and voice agent platforms
Mid-level Full-Stack ML Engineer specializing in Graph RAG and knowledge graphs
Entry-Level AI/ML Engineer specializing in LLM apps and RAG pipelines
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and agentic automation
Junior Software Engineer specializing in cloud-native backend services and LLM applications
Mid-level Robotics Software Engineer specializing in autonomous systems and computer vision
Director-level AI & Data Consultant specializing in LLM/RAG, analytics, and growth
Junior Machine Learning Engineer specializing in LLMs and conversational AI
Entry-Level Full-Stack Software Engineer specializing in cloud-native microservices
Mid-level Data Scientist specializing in fraud detection and credit risk ML
Junior AI Engineer specializing in LLM agents, RAG, and computer vision
Mid-level Software Engineer specializing in cloud-native full-stack and AI applications
Mid-Level Java Full-Stack Developer specializing in Spring Boot microservices and cloud
Junior Full-Stack Software Engineer specializing in AI and RAG applications