Vetted Education Professionals

“Full-stack engineer with about 3 years of experience who is deeply hands-on with AI-assisted development and agentic systems. Built TubeAgent using LangChain, Ollama, FAISS, and Llama 3, and has demonstrated measurable impact by cutting review time by 90% and reducing deployment time from 30 minutes to under 5 minutes at NC State. Combines practical experimentation with strong architectural thinking around resilient, composable AI systems.”

“Research-focused software engineer who builds performance-critical Python/C++ systems emphasizing correctness, state-transition precision, and distributed coordination. Created an automated simulation-based testing/validation framework for quantum programs that caught subtle logic/type errors early, reduced debugging time, and improved developer confidence through strong observability and scalable test generation.”

“Master’s-level IoT course project that the candidate helped evolve into a research lab effort by “ROSifying” a soil-fertility detection rover (autonomous navigation within a GPS geofence, sensor fusion, and rover-to-base-station telemetry via NRF24 to a Raspberry Pi dashboard). Also built a ROS/Gazebo vision-based teleoperation system using a SigLIP hand-gesture model mapped to geometry_msgs/Twist, and improved stability by instrumenting and filtering a latency-prone perception-to-control pipeline.”

“Graduate robotics engineer from Boston University who led development of a perception-to-decision pipeline for a multi-robot, perception-driven navigation and coordination system. Strong in ROS/ROS2 C++ on Linux, with hands-on experience hardening real-time behavior on hardware (timing sync, QoS/queue/executor tuning) and validating via Gazebo/Webots plus real-robot testing; also uses Docker and basic CI for regression checks.”

“Robotics software engineer with internship experience at Lucid Motors building a mapping/localization pipeline that fuses LiDAR, camera, and GPS into high-fidelity 3D maps for autonomy/ADAS. Strong in SLAM and multi-robot systems—has modified ROS/ROS2 SLAM packages (FAST-LIO2, LIO-SAM) at the source level, optimized real-time multi-drone coordination for low-latency data sharing, and used Gazebo + Docker to simulate and deploy research robotics stacks.”

“Recent J&J intern who built a conversational RAG agent and led a shift from a monolithic model to a modular RAG workflow, cutting response time from several days to under a second by tackling data fragmentation, context retention, and embedding/latency optimization. Also worked on a large (7B-parameter) multimodal VQA pipeline for healthcare research and stays current via NeurIPS/ICLR and open-source contributions.”

Apoorv Bankey

Screened

Mid-level Backend Engineer specializing in distributed systems and FinTech

New York City, NY6y exp

“Engineer who uses AI and multi-agent workflows as a force multiplier while keeping architecture, security, scalability, and production quality under human control. Shared a concrete example of accelerating a backend-heavy SaaS email ingestion platform with authentication, role-based APIs, database models, and deployment setup using agent-style development and review.”