Vetted HTML Professionals

“Robotics/embodied-AI practitioner who built a TurtleBot3 LiDAR-fingerprint localization pipeline end-to-end (autonomous data collection + multi-head NN) achieving ~30 cm error in a 10x10 m space. Also has industry experience at Infineon building large-scale production data/AI pipelines and rapidly fixing a deployed recommendation system by correcting upstream data normalization, improving accuracy by 20%+.”

“JavaScript engineer and open-source contributor focused on runtime performance, reliability, and developer experience—refactored a widely used client-side API/state library to improve concurrent request handling, error consistency, and UI performance while adding tests and documentation. Also owned improvements to a core microservice at Velsa integrating multiple hospital systems, bringing structure to ambiguous priorities and delivering stability and performance gains from design through deployment.”

“Unity game developer who built a context-sensitive movement and camera system for a grid-based dungeon crawler and used DOTween for key gameplay animations. Worked at Chimera Entertainment on Songs of Silence, contributing via bug fixes, working within an existing Photon Fusion protocol, and implementing a UI-heavy in-game lexicon; also leverages AI tools (e.g., ChatGPT) to accelerate editor/tooling and gameplay scripting.”

“Forward-deployed/solutions-oriented engineer with experience shipping enterprise LLM voice-agent workflows from prototype to production, including variable extraction and API integrations. Demonstrated strong real-time troubleshooting via logs/RCA (e.g., fixing multilingual language-switching by tuning temperature and improving context), and has led technical workshops while partnering with sales/solutions teams to drive customer adoption.”

“Backend Java engineer with strong platform/DevOps experience: modernized an insurance claims legacy monolith into DDD-aligned microservices, deployed containerized services on Kubernetes with Jenkins CI/CD and static analysis gates, and implemented GitOps using ArgoCD. Also led major AWS migration planning with dependency mapping and network monitoring to uncover hidden dependencies, and built Kafka-based real-time event streaming with schema-registry-driven evolution.”

“Software developer with hands-on experience owning customer-facing work end-to-end (requirements, implementation, testing, and feedback-driven iteration) using Python and React.js. Also described remodeling an internal legacy page/tool to improve performance and accuracy, and has exposure to microservices and RabbitMQ plus ETL-based system work.”

“Backend/platform engineer with hands-on ownership of Kubernetes GitOps delivery (GitHub Actions + Argo CD) on AWS EKS, including progressive rollouts and reliable rollback across interdependent microservices. Built a Python/FastAPI ML-driven document-processing service (PostgreSQL + S3) to complement existing Spring Boot systems, and implemented Kafka streaming pipelines with Schema Registry plus Prometheus/Grafana observability. Also supported a hybrid cloud-to-on-prem migration for compliance/latency with phased rollout and incremental PostgreSQL migration.”

“Full-stack engineer who owns customer-facing web products end-to-end (React/TypeScript + Node.js), shipping frequent releases with strong testing, staged deploys, and production monitoring. Improved a key user flow by batching backend calls and simplifying frontend rendering, driving ~30% faster load times and ~30% higher completion rates. Also built an ops monitoring dashboard using ELK + Prometheus/Grafana that cut incident response time by 40% and has hands-on microservices messaging experience (RabbitMQ/Kafka, idempotency, DLQs).”

“Software developer at Indiana University who built a phishing training platform using TypeScript/React, Node, GraphQL, and DynamoDB, including an admin tool to monitor student completion and send automated reminder emails. Also created TechRent, an IU-only electronics rental marketplace concept focused on improving security by restricting access to university students.”

“Graduate Assistant Intern at Friends University who built and deployed a GenAI-driven requirement understanding system that automates extraction and semantic grouping of technical requirements from large unstructured documents. Demonstrates strong LLM engineering rigor (golden datasets, regression testing, post-processing validation) and production-minded delivery using LangChain/LlamaIndex orchestration, FastAPI microservices, Docker, and cloud deployment.”

“Built and deployed a production RAG-based enterprise document intelligence platform for financial/compliance/operational documents on AWS (Spark/Glue ingestion, embeddings + vector DB, LangChain orchestration, REST APIs on Docker/Kubernetes). Deep hands-on experience orchestrating multi-step and multi-agent LLM workflows (LangChain, LangGraph, CrewAI) with strong focus on grounding, evaluation, observability, and cost/latency optimization, and has partnered closely with non-technical finance/compliance teams to drive adoption.”

“Backend/AI engineer with Johnson & Johnson experience building data-heavy payer/claims analytics services (Python/FastAPI, PostgreSQL, AWS) and optimizing them under peak ingestion load via indexing/query tuning and caching. Also shipped an end-to-end RAG feature for clinicians to extract insights from unstructured clinical notes, using constrained prompts and retrieval-confidence guardrails to prevent hallucinations.”

“QA automation-focused engineer who hardens production CI/CD by integrating and stabilizing end-to-end automated tests (tackling async UI flakiness, resilient assertions/selectors, and controlled test data). Demonstrates strong cross-layer troubleshooting by correlating logs and system metrics to resolve intermittent service reachability, then adding monitoring/alerts and documentation. Also partners directly with operators to improve real-world workflows by enhancing validation logic and error messaging.”

“Built and maintained an air-quality prediction backend in Python/Flask that serves offline-trained ML models to a React dashboard via JSON REST APIs. Demonstrates strong performance focus across the stack—low-latency inference under load, SQLAlchemy/Postgres query optimization, multi-tenant data isolation, and caching/background task strategies for high-throughput systems.”

“Software engineer with hands-on AWS experience optimizing an email campaign delivery system—re-architected a monolithic worker into multi-threaded/multi-worker ECS components to boost throughput ~600% (5 to 35 emails/sec). Comfortable debugging production issues (e.g., SQS/EventBridge policy misconfiguration) and emphasizes maintainable delivery via design docs, TDD, versioned APIs, and strong test coverage.”

“Backend engineer with hands-on experience building real-time, low-latency systems: owned the Python backend for a real-time crowd-monitoring product (top 5% at HackHarvard 2025) using OpenCV, GPU YOLO inference (PyTorch), WebRTC, and OAuth. Also has production Kubernetes/GitOps experience (Helm/Kustomize, GitHub Actions, Argo CD), Kafka-based event pipelines, and executed a minimal-downtime on-prem PostgreSQL migration to AWS EC2.”

“Backend-focused engineer with experience owning a production e-commerce platform end-to-end (TypeScript/Node/Express, React, MongoDB, Redis) including RBAC and contract-based API development. Also worked at Infosys on a large healthcare management system built with Spring Boot microservices, using Kafka for messaging/retries, circuit breakers for resilience, and OpenTelemetry/Swagger for observability and API documentation.”

“Full-stack engineer who built "Workstream AI," an AI-powered engineering visibility product that converts GitHub activity into real-time insights using an event-driven microservices stack (RabbitMQ/Postgres/Express) and GPT-4 with a React frontend. Previously a Founding SWE at a health & wellness startup, building data-driven user management tooling, and also delivered a real-time shuttle tracking/ride request system using Java Spring Boot/Hibernate + React; comfortable owning production deployment details (AWS EC2, DNS, SSL).”

“Robotics software engineer who led system design for an Autonomous Trash Collecting ASV presented at the IEEE ICRA 2025 “Robots in the Wild” workshop, integrating YOLOv8-based perception with ROS autonomy logic to detour for trash while preserving a scientific survey mission. Also built ROS2 UAV capabilities combining ArUco detection, RTAB-Map SLAM, and PX4 integration, with strong simulation (Gazebo/VTD/MSC Adams) and CI/CD QA automation experience.”

“Robotics software engineer at Earthwise building a full ROS2 Humble warehouse AMR stack for bin picking—owning perception (Livox/Orbbec/RPLidar fusion + calibration), Nav2 navigation with custom planners/behavior trees, and application-layer nodes (barcode scanning, safety monitoring, web HMI). Demonstrated strong real-world debugging and performance tuning (sub-cm AprilTag docking; ~80% reduction in localization failures) plus solid simulation/CI practices (Gazebo + Docker + GitHub Actions).”

“Software engineer who shipped an end-to-end internal workforce dashboard at Northwestern Mutual, spanning Spring Boot APIs, PostgreSQL schema/query optimization, and a React + TypeScript UI with role-based access and filtering. Has hands-on production experience deploying via GitHub Actions CI/CD to AWS (Docker, EC2, RDS) and resolving performance incidents by tuning database queries and indexes.”

“Backend engineer who built and scaled a transaction-processing microservice (150K+ records/day) in a microservices ecosystem, debugging peak-load latency/timeouts via CloudWatch/Grafana, Kafka lag analysis, and DB query tuning (indexes, Redis caching, batching). Also shipped an LLM-powered document assistant end-to-end with prompt/response validation plus retries/fallbacks for production reliability.”

“Governance engineer intern at GSK who built policy-as-code automation using Open Policy Agent/Rego integrated into GitHub CI/CD and Terraform workflows. Also built and shipped a voice-enabled expense tracking app using speech-to-text + LLM structured extraction with strong validation, retries, and semantic guardrails, and designed the supporting PostgreSQL data model with performance-focused indexing.”