Vetted Role-Based Access Control Professionals

“Backend/platform engineer who built an LLM-driven QA automation system (“mockmouse”) using a Flask orchestration microservice, Socket.IO real-time updates, Redis caching, and strict Pydantic schemas to turn prompts into reliable action graphs and automated browser tests. Has hands-on Kubernetes delivery experience (Docker/Helm/Jenkins) and has supported large migration programs, validating ETL cutovers with 1M+ synthetic records and rigorous output comparisons; also built event-driven monitoring/anomaly detection streaming into Grafana.”

“Full-stack engineer with hands-on ownership of production systems, including a Kafka-based notification/alerting platform (Node.js + React) deployed on AWS with Docker/GitHub Actions, achieving ~95% email delivery reliability. Demonstrates strong operational maturity (observability, CI/CD, zero-downtime migrations) and experience shipping in ambiguous environments (SJSU project) with evolving requirements.”

David Pang

Screened

Intern Full-Stack Software Engineer specializing in web apps and healthcare APIs

1y exp

“Full-stack developer who built an end-to-end e-commerce application with admin/blog/announcement features using Node/Express and AWS S3, emphasizing security via expiring presigned URLs. Also has strong distributed-systems fundamentals from implementing the Raft consensus algorithm (replication logs, majority acks, leader elections) and has created build automation tools (GNU Makefiles/scripts) to streamline team workflows.”

“Built and shipped a production LLM feature that explains DSA problems with real-life explanations, using Grok with automatic failover to OpenRouter (and multiple backup models) to avoid user-facing failures. Improved cost efficiency by implementing difficulty-based token budgets and iterated prompt quality via structured constraints and an in-app feedback mechanism, reporting satisfaction across 38 users.”

“Built and productionized an LLM-powered service desk ticket triage and reporting agent that classifies, prioritizes (including sentiment/urgency), and summarizes tickets into structured SQL outputs feeding Power BI dashboards. Emphasizes production reliability (99% uptime) with retries, schema validation, confidence thresholds, human review queues, and rule-based fallbacks, delivering 85–90% reduction in manual effort and 25–30% faster resolution times.”

Phu Le

Screened

Senior Frontend Engineer specializing in modern web apps and blockchain gaming

7y exp

“Frontend engineer who led the Yams marketing/advertising campaign management app end-to-end using React + Next.js, emphasizing scalable component architecture (Atomic Design) and strong automated/UI testing (React Testing Library, Storybook, Playwright). Has built TypeScript dashboards with typed API hooks to reduce prop drilling and improve reuse, and has improved performance via code splitting, lazy loading, and render optimization.”

Iskhak Ishmakhametov

Screened

Mid-level Full-Stack Software Engineer specializing in FinTech and real-time systems

Bellevue, WA7y exp

“Full-stack product engineer with a strong real-time systems focus: built and rolled out a WebSocket-based notifications system (with robust reconnect/resync and event ordering protections) that cut update latency to under 200ms. Also owned a workflow automation platform backend in FastAPI (JWT/RBAC, versioned APIs, standardized errors), designed the PostgreSQL schema for workflows/tasks/executions, and operated deployments on AWS ECS Fargate with blue-green CI/CD and performance stabilization via caching and autoscaling.”

HarshelSrivatsava Srivatsava

Screened

Intern Full-Stack Engineer specializing in AI-powered SaaS products

Birmingham, AL1y exp

“Solo builder of OGym, shipping production AI features for gyms that turn member behavior/health data (workouts, attendance, nutrition, payments, device metrics) into prioritized, actionable owner and member insights. Designed and implemented FastAPI backends, PostgreSQL-based RAG workflows, guardrails (RBAC/validation/rate limiting), and real-user evaluation loops, with a strong focus on latency/cost optimization and reliable data pipelines.”

“Backend/data engineer focused on climate/emissions data platforms, building production Python (FastAPI) microservices and AWS serverless/ETL pipelines (Glue/Athena/Lambda/EventBridge). Demonstrated strong reliability and observability practices plus measurable optimization wins, including cutting PostgreSQL query runtimes from minutes to seconds and reducing AWS costs from ~$6k/month to ~$400/month.”

“Full-stack system analyst/programmer at PeakPlay Sports (startup) who built an AI "coach" product end-to-end in ~2 months, using a LangGraph-orchestrated multi-agent architecture with a FastAPI backend. Shipped production RAG grounded in athlete history (OpenAI embeddings + vector store) with guardrails and a structured eval loop (golden set + LLM-judge + human review) to improve engagement and reduce hallucinations.”

“Robotics software engineer with ROS 2 Humble/Nav2 experience on a warehouse robot fleet, focused on improving throughput in dynamic human environments. Implemented C++ local-planner and velocity-control changes using LiDAR-based motion prediction and real-time costmap tuning under a 20ms control loop, and built a Gazebo digital twin with custom failure-injection plugins plus Docker/Kubernetes deployment tooling.”

“Software engineering intern who built and deployed a full-stack telemedicine platform (React/Node/MongoDB) used daily in a pediatric clinic, incorporating PyTorch-based predictive features. Demonstrated strong customer-facing iteration and production performance debugging—resolved a live slowdown by indexing/optimizing MongoDB queries and adding caching, improving response times by ~50%.”

“Robotics software engineer focused on reliability in real-time sensor pipelines and ROS/ROS2 integration, with hands-on experience hardening systems against noisy data, dropouts, and network variability. Uses ROS introspection tools plus simulation (Gazebo/Webots) to diagnose latency and stability issues before hardware deployment, and supports repeatable rollouts via Docker and CI/CD.”

Ekta Mulkalwar

Screened

Junior Machine Learning & Full-Stack Engineer specializing in applied AI systems

Los Angeles, CA2y exp

“Master’s thesis focused on building and deploying a gait-based biometric authentication system using mobile accelerometer time-series data as an alternative to passwords/2FA. Emphasized real-world robustness by addressing sensor noise and variability (phone placement, walking speed, footwear) and improving safety using biometric metrics like FAR/FRR and EER, while collaborating closely with a non-ML thesis advisor.”