Vetted Engineering Professionals

George Platon

Screened

Principal Full-Stack Engineer specializing in AI, DevOps, and cloud platforms

Romania, Romania16y exp

“Built a production end-to-end AI video-to-reels clip extraction system using a multi-agent architecture with transcription, captioning, effects generation, and centralized orchestration. Demonstrates unusually strong systems thinking around reliability, observability, evaluation, and production tradeoffs for LLM-powered workflows, including Kubernetes/Kafka-based deployment and regression-driven prompt governance.”

“Engineer with hands-on experience owning customer deployments for ordering and billing systems at Amdocs, including performance tuning, CI/CD improvements, and post-launch stabilization that delivered about 50% faster execution time. Also built and debugged an LLM-powered task prioritization app using Gemini, Streamlit, Python, and MongoDB, with a strong focus on prompt reliability, validation, and handling inconsistent real-world inputs.”

“Controls/automation candidate whose experience is weighted more toward commissioning, troubleshooting, and system verification than full end-to-end design ownership. Has hands-on exposure to PLC logic review, interoperability testing, fire alarm/life safety commissioning, and ensuring safety-critical systems operate as intended in commissioning environments.”

“Engineer with a mature, agent-oriented approach to AI-driven software development, using structured planning, TDD, and verification loops rather than ad hoc prompting. Has hands-on experience acting as a tech lead for multiple AI agents in an LLM intelligent routing project, coordinating implementation, testing, debugging, and edge-case review with strong attention to system tradeoffs.”

“Software engineer focused on backend/full-stack, distributed systems, cloud infrastructure, and AI-related work. Stands out for using AI and multi-agent workflows as an engineering accelerator while maintaining rigorous testing, logging, and system-level validation, including work on telemetry and monitoring platforms where reliability and correctness are critical.”

“Data engineering/software development candidate who built a stock market pipeline and uses that project to demonstrate strong architectural thinking across Kafka, Spark, and Airflow. They stand out for a pragmatic approach to AI: using tools like Copilot, ChatGPT, LangChain, and AutoGen to accelerate development while maintaining human oversight, testing, and system-level decision making.”

“Candidate has hands-on experience using AI-assisted development in a pragmatic, controlled way, including shipping a more user-friendly student feedback form by redesigning text-heavy inputs into checkboxes and dropdowns. They stand out for disciplined review habits: line-by-line validation of AI-generated code, strong edge-case testing, and thoughtful use of structured prompts and staged workflows instead of over-relying on autonomous agent frameworks.”

“Full-stack developer who has built and shipped both traditional web products and AI-powered applications, including a Spotify playlist-combining app, a recruiter-facing RAG chatbot embedded in a portfolio, and a fine-tuned GPT-2 art review generator. Stands out for combining privacy-conscious engineering, practical LLM guardrails, and scrappy production problem-solving—from queue-based inference systems to newsroom digital transformation with multi-tenant WordPress.”

“AI/backend engineer who has built multiple applied AI systems end-to-end, including an underwriting document intelligence copilot, ambient clinical documentation workflows, and a financial analysis agent. Stands out for combining practical LLM architecture choices with reliability mechanisms like human-in-the-loop review, eval frameworks, and grounded retrieval in production settings.”

“Intern-level full-stack engineer who has built across accessibility tech, ad-tech, healthcare software migration, and consumer analytics projects. Stands out for combining hands-on React/frontend work with backend integration, accessibility-aware routing logic, OAuth debugging, and pragmatic product decisions in highly ambiguous environments.”

Mainak Pandit

Screened

Senior Frontend Engineer specializing in React, TypeScript, and product-focused SaaS

Hyderabad, India5y exp

“Frontend-leaning product engineer who operated as an end-to-end owner at Cone, a 5-person startup, building the proposal creation and signing platform that became the company’s primary revenue driver. Stands out for combining product judgment with architecture and backend execution, including a self-built Node.js PDF service that cut generation time by ~60% and meaningfully reduced developer overhead.”

Rozaliia Russkikh

Screened

Mid-Level Full-Stack Software Engineer specializing in AI systems

5y exp

“Full-stack engineer with hands-on experience leading early AI product initiatives, including a RAG dashboard prototype and a production-ready agentic workflow integrating Front, Airtable, and Slack. Stands out for combining Angular/TypeScript frontend leadership with FastAPI backend work, plus a strong focus on evals, observability, and hardening LLM systems before launch.”

Nikita Papenkov

Screened

Mid-level Full-Stack Engineer specializing in frontend, Web3, and data visualization

Russia7y exp

“Frontend engineer with hands-on ownership of a complex blockchain launchpad UI, including a solo refactor that unified Solana and Monad flows under one architecture. Their work emphasized feature-flag-driven multi-chain support, real-time data handling, and major bug reduction, with team feedback strong enough that they nearly received a promotion.”

“Full-stack AI engineer who built HireMate end to end using FastAPI, React, and TypeScript to automate resume-to-job matching and tailoring with LLMs. Demonstrates strong practical judgment around grounding, validation, hallucination prevention, and human-in-the-loop design, and has also shipped an early-stage multi-agent rental research workflow that processed 200-300 listings in parallel.”

Michael Adeniyi

Screened

Mid-level Full-Stack & AI Engineer specializing in LLM-integrated cloud applications

New York, NY3y exp

“Built an AI immigration compliance co-pilot for F1 OPT and STEM OPT students, combining rule-based risk assessment with LLM-powered guidance on a React/TypeScript and AWS serverless stack. Stands out for thoughtful handling of high-risk AI: grounding responses in structured compliance data, adding guardrails, and keeping legal interpretation human-in-the-loop. Also contributed to an education-focused AI product for teachers and helped expand it with quiz generation and document editing features.”

“Early-career software/ML candidate with hands-on experience spanning full-stack product work at Carrier and multiple AI-heavy academic projects. Particularly interesting for teams exploring applied ML: they built a reinforcement-learning-based movie recommender with LIME/SHAP explainability and benchmarked it against a DDPG baseline, while also having practical React/Next.js and Django/Postgres experience.”

Lenny Lin

Screened

Junior Full-Stack Engineer specializing in AI and distributed systems

Champaign, IL3y exp

“Built and owned a hackathon project (Gritto) with a Python/FastAPI backend that routes user text through a sequence of Gemini agents to produce structured JSON outputs. Has hands-on production deployment experience using Docker/Docker Compose, GitHub Actions CI/CD, AWS App Runner, MongoDB, and secrets management (Doppler + migration to AWS Secrets Manager), plus implemented a chat-like experience via multiple HTTP requests when SSE wasn’t viable.”

“Software engineer using AI pragmatically to accelerate development while keeping human review central to quality. Has hands-on experience applying AI and lightweight multi-agent workflows in a microservices environment spanning Java Spring Boot APIs, React modules, and Kafka event flows, with strong emphasis on architecture validation and production safeguards.”

Prabhav Karve

Screened

Junior Software Engineer specializing in data engineering and AI applications

Rochester, NY4y exp

“Data engineer/automation builder with experience at Rochester Regional Health and Accenture, focused on replacing fragile manual reporting with production-grade Azure, Python, and Snowflake pipelines. Stands out for combining strong systems thinking, rigorous validation, and practical AI/LLM usage to drive measurable outcomes, including a 34% throughput improvement and support for regulatory reporting that helped avoid €150M in penalties.”

“Intern/full-stack developer who built a sports player statistics dashboard with Next.js, React, Node.js, TypeScript, Zustand, and PostgreSQL. Demonstrated solid ownership across the stack, including API design, state consistency, production debugging, query/index optimization, and phased zero-downtime schema migrations.”

Godwin Idowu

Screened

Intern Software Engineer specializing in AI/ML and full-stack systems

Gambier, OH4y exp

“Full-stack engineer with hands-on ownership of both real-time marketplace features and production AI systems. Built AI-powered matching at an early-stage startup and shipped LLM-driven CRM and competitive intelligence workflows using OpenAI, LangChain, and RAG, with measurable gains in engagement, workflow reduction, and decision speed.”

“Front-end engineer focused on sophisticated browser UIs, with strong depth in performance optimization, modular architecture, and workflow-heavy product design. Built a reporting platform from scratch and delivered measurable UX wins, including reducing form latency from 300ms to under 12ms and turning a 2.5-hour image-prep workflow into a 5-minute batch process.”

“Backend/data engineer who helped evolve Bitnimbus LLC’s Kafka-as-a-service MVP from a monolith into an event-driven distributed system, using careful design, parallel rollouts, and idempotent event handling to maintain correctness. Also built production-grade API and database security (JWT scopes, rate limiting, explicit Postgres policies/RLS-style controls) and improved Prometheus monitoring by eliminating false outages via heartbeat metrics and windowed aggregation.”

“Robotics/embedded candidate who built an IoT smart shoe for visually impaired users, implementing real-time obstacle detection with ultrasonic sensors and haptic feedback on Arduino. Has practical ROS experience (RViz/Gazebo) and improved reliability in distributed systems by hardening an Arduino-to-ROS serial protocol with framing, strict parsing, and sensor-noise filtering; also containerized ROS environments with Docker for reproducible simulation and onboarding.”