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Vetted Multi-Agent Systems Professionals
Pre-screened and vetted.
Mid-level Software Engineer specializing in AI/ML and agentic systems
Junior ML/Software Engineer specializing in LLM systems, RAG, and MLOps
Mid-level Robotics Software Engineer specializing in autonomy, motion planning, and embedded AI
Senior Machine Learning Scientist specializing in forecasting, optimization, and agentic LLM systems
Junior AI Engineer specializing in LLM systems, RAG pipelines, and inference optimization
Senior AI/ML Engineer specializing in Generative AI, LLMs, and Computer Vision
Mid-level Software Engineer specializing in AI/GenAI and cloud-native backend systems
Mid-level Machine Learning Engineer specializing in MLOps and multimodal AI
Junior AI/ML Engineer specializing in RAG, multi-agent systems, and enterprise NLP
Senior Data Scientist and ML Engineer specializing in NLP, LLMs, and AI systems
Junior Software Engineer specializing in backend systems, AI agents, and EdTech platforms
Mid-level Software Engineer specializing in backend systems and AI platforms
Mid-level AI Software Engineer specializing in LLMs and healthcare AI
Mid-level AI/ML Engineer specializing in Generative AI and cloud MLOps
Mid-Level Machine Learning Engineer specializing in LLMs and RAG systems
Junior Machine Learning Engineer specializing in deep learning and healthcare AI
Junior AI/ML Engineer specializing in RAG and multi-agent LLM systems
Mid-level AI/ML Engineer specializing in GenAI, RAG, and multi-agent LLM systems
Mid-level Full-Stack AI Engineer specializing in agentic RAG and LLM fine-tuning
Kruti Mehta
Mid-level Software Engineer specializing in backend systems and FinTech analytics
“Engineer with a pragmatic, high-leverage approach to AI-assisted development: uses AI and multi-agent workflows aggressively for implementation and internal tooling, while maintaining strict human oversight for user-facing features. Stands out for treating agents like junior engineers, breaking work into actionable tasks, and combining robust testing, local E2E validation, and feature-flag rollouts to safely ship production code.”
sathwik kuchana
Mid-level AI Engineer specializing in Generative AI, LLMs, and RAG on AWS
“Built and deployed an LLM-powered clinical decision support and risk monitoring platform for mental health at Valuai.io, emphasizing low-latency, evidence-grounded responses and crisis-safe behavior with clinician escalation. Strong production agent-orchestration background (LangChain/CrewAI) plus rigorous evaluation (clinician-in-the-loop + evaluator agent) and large-scale synthetic testing; also applied multi-agent workflows to document verification and fraud detection during an AI internship at Nixacom.”
Maneesh Ujji
Junior Machine Learning & Data Science professional specializing in AI agents and applied ML
“IT Analyst/research background with hands-on experience deploying and hardening a multi-agent AI support/triage system (ticket ingestion + knowledge-base retrieval) with strong emphasis on reliability and observability. Has debugged real production issues spanning backend services and network latency (sync failures/partial writes) and is comfortable in Linux environments; also has academic exposure to robotics simulation and ROS2.”
Abhish Khanal
Senior Robotics Researcher specializing in Embodied AI and learning-augmented planning
“Robotics software engineer with experience spanning safety-critical embedded medical hardware (low-cost neonatal baby warmer with PID temperature regulation) and advanced multi-robot planning research (belief-space planning with abstraction + MCTS to handle uncertainty). Strong ROS/ROS2 practitioner (Nav2/SLAM Toolbox/MoveIt) who builds custom packages (e.g., Insta360 panoramic imaging) and is hands-on debugging real robots from SLAM/frontier exploration to multi-robot collision avoidance and real-time performance.”