Vetted Full-Stack Development Professionals

“Backend/platform engineer who has built and run production Python/Flask + Kafka microservices processing RFID and camera/RFID fusion streams for near-real-time retail cart updates at ~4–5M events/day. Strong in reliability/performance debugging (p99 latency, Kafka lag, Cosmos DB RU hot partitions) with measurable impact including ~30% database cost reduction, and has also shipped an end-to-end vulnerability scanning workflow with DynamoDB-backed state, idempotency, and robust retry/verification guardrails.”

“Robotics/software engineer who deployed a Raspberry Pi computer-vision-controlled 3-axis platform at FuelCell Energy, improving screen-print alignment from >10mm to 0.01mm repeatability via encoder-based closed-loop PID control. Currently designing an AI-enabled hearing-aid accessory for the cocktail party problem using a multi-mic array, beamforming, and an edge-accelerated neural network with <10ms latency via shared-memory DSP integration.”

“UX/product designer in a medical laboratory B2B portal context who prototypes beyond Figma—built a GPT-based settings chatbot to address findability and low settings adoption, iterating through 11 tested versions with regression safeguards and structured prompts to mitigate instruction truncation/hallucinations. Also redesigned clinic order management by separating doctor vs assistant experiences and introducing step-based status views for a long, multi-stage lab order lifecycle; former full-stack engineer who improves design-to-dev handoffs via templates and readiness rituals.”

“Full-stack engineer who built an LLM-powered productivity web app (LifeOS) end-to-end with TypeScript/Next.js, Prisma, and Postgres, emphasizing fast iteration with stable API contracts and an isolated AI service boundary. Also built a security/compliance login-verification workflow at Medpace used within an internal admin portal for thousands of employees, and has AWS experience orchestrating batch GPU workloads with robust retry/idempotency patterns.”

“Unity gameplay/AI engineer with driving-simulator experience who re-architected state-based AI using multithreading (including a threaded 2D collision/location checker) to nearly double AI traffic while improving frame rate. Has shipped on a Photon-networked title (Frankie's Revenge / RoboRevengeSquad) and is comfortable debugging tricky multiplayer spawning/movement issues with practical client-server test setups.”

“Capgemini engineer who helped take a travel insurance platform from prototype demos to a stable production system by clarifying requirements, hardening API contracts, and adding validation/logging to handle real customer data and external integrations. Experienced in real-time troubleshooting of complex workflows (including LLM/agentic-style workflows) through strong observability practices, and in leading practical developer-focused demos that accelerate client integration and adoption.”

“Built an AI journaling app at HackCU 2025 featuring a speaking AI avatar with long-term memory via RAG (ChromaDB) and low-latency microservices coordinated through Kafka, including deployment under AMD/non-CUDA constraints using a quantized Llama 8B model. Also has Goldman Sachs experience deploying a Trade UI on Kubernetes with CI/CD rollback automation, plus a healthcare AI internship at CU Anschutz collaborating closely with physicians on diagnostic reasoning and dataset annotation.”

“Full-stack engineer who has owned end-to-end delivery of an internal, customer-facing data visualization product and helped build a data modification pipeline used across the organization for data integrity/governance. Demonstrates pragmatic MVP-driven delivery within sprints and makes performance-oriented architectural decisions (e.g., batching API calls to reduce frontend request volume) in TypeScript/React systems.”

“Software engineer focused on real-time, low-latency AI pipelines: built an end-to-end mobile-to-backend image classification system using React Native/Expo, Node.js, gRPC, MySQL, and Google Vision AI, optimizing throughput and latency. Also integrated an AI model into a real-time field workflow at DTE via Node.js + Azure Databricks, adding data cleaning/validation and safe fallback logic for reliability in operations.”

“Siemens AI engineer who shipped production multi-agent LLM systems across cybersecurity and sustainability, including a vulnerability automation agent that cut manual work 70%. Deep in orchestration (LangGraph supervisor-worker state machines), reliability engineering (async fault tolerance, retries, spike handling), and rigorous evaluation (offline benchmarks, LLM-as-a-Judge improving label agreement 28.9%) with measurable production guardrails.”

“Hands-on engineering leader who has scaled teams quickly (hired 20 engineers in 4 months) and led major architecture shifts including monolith-to-microservices and serverless, async AI-driven medical data ingestion/search. Also drove a versioned-inventory redesign with auditability and rollback that reduced operational errors by 22%, and demonstrates strong incident response with clear stakeholder communication.”

“Early-career engineer who owned an end-to-end objective assessment/coding contest platform at an edtech startup, using Postgres + S3 and Redis (queues + ZSET) to decouple and scale code submission processing with worker sandboxes. Also implemented idempotency controls and set up monitoring and CI/CD while the rest of the team focused on curriculum.”

“Won a machine learning contest and was placed onto a Kaiser data science team, where they built ML models for hospital bottleneck prediction and resource allocation. They later built and deployed a full-stack LLM-based “data analyst agent” (with custom orchestration plus LangChain/OpenAI Agents experience) that generates analysis code, answers questions, and produces dashboards from uploaded datasets, emphasizing rigorous evaluation sets, robustness, and healthcare security/compliance integration.”

“Built and operated a production TypeScript backend for a stateful conversational quoting chatbot at Tringapps, orchestrating multi-step workflows and session state while integrating with Salesforce and NetSuite. Implemented validation/retry logic, modular architecture, and strong logging/observability to handle real-world edge cases and external API failures.”

“Forward-deployed engineer/tech lead who built an end-to-end demand planning and forecasting application for a major US steel manufacturer, integrating Snowflake data into the C3 platform with batch/MapReduce workflows, monitoring, and a React/TypeScript UI. Also productionized an enterprise LLM integration with structured outputs and authorization guardrails, reporting +30% stakeholder engagement and broad adoption across customer deployments.”

“Startup-minded product builder with consulting experience in Oil & Gas who formed an LLC to design and deliver a modern project-controls software platform, replacing Excel-heavy workflows with scalable web-based calculations. Strong in pragmatic tech-stack decisions, talent matching, and shipping MVPs despite shifting stakeholders; sees marketing (pitching/networking) as a growth area and has evaluated partnership/investment offers for balanced support.”