Vetted Express Professionals

Joe Zayd

Screened

Senior Full-Stack Engineer specializing in AI and cloud-native platforms

Woodbridge, VA8y exp

“Full-stack engineer who has operated in a very lean startup setting, helping a non-technical founder turn an AI-focused education product idea into a shipped MVP in roughly six weeks. Also brings B2B SaaS experience from a real estate rental platform with payment flows and Experian-based background and credit check integrations.”

“Front-end engineer focused on sophisticated, high-stakes enterprise UIs in privacy computing and healthcare-related products. They combine deep browser-performance knowledge with TypeScript/React architecture, and can point to concrete impact like zero critical UI bugs, 40% faster configuration flows, and nearly 90% fewer configuration-related failures.”

“Full-stack software engineer who shipped production systems in academic and e-commerce contexts, including a UC Irvine course recommendation platform with async Kafka-based OCR processing (Tesseract) and LangChain-driven recommendations. Strong in building polished React/TypeScript dashboards (Figma-to-implementation) and owning Python backends (FastAPI/Flask) with solid API design, caching, and AWS EKS deployments; delivered measurable impact (tripled engagement, ~50% faster processing).”

“Full-stack engineer who built an early-stage social platform for scriptwriters (Scriptscape) from scratch, owning everything from React Native/React UX to Node/Postgres APIs and AWS deployment. Demonstrates strong production-minded engineering with CI/CD, observability, and scalability patterns (cursor pagination, indexing, background jobs), plus experience hardening flaky third-party integrations with idempotency and backfills.”

“Backend engineer with fintech/AI startup experience who built an Azure serverless, event-driven pipeline for large-scale crypto sentiment analysis and semantic search (OCR/NLP to vector search) and integrated LLM + blockchain data for predictive insights. Demonstrated measurable impact (25% lower retrieval latency, 10% fewer data errors, 15% higher engagement) and has led safe microservices migrations with strong security and reliability practices.”

“AI Engineer at Humanitarian AI who has built and productionized both a LangGraph-based multi-agent workflow system and a RAG pipeline (OpenAI embeddings + vector DB) with rigorous evaluation/guardrails. Reports strong measurable impact (60% faster workflow delivery, 40% fewer incidents, 70% reduced research time) and has prior enterprise modernization experience at Infosys migrating ETL to microservices with zero production incidents.”

“Backend engineer who has designed and evolved high-traffic event/activity management systems using Node/Express and PostgreSQL, prioritizing scalability and reliability with a layered architecture. Has led zero-downtime refactors/migrations using parallel runs, dual writes, and rigorous validation/monitoring, and brings a security-focused API approach (JWT, RBAC/ABAC, rate limiting, DB-enforced tenant/RLS filters).”

“Unity game developer with hands-on experience improving platformer feel through playtest-driven movement tuning (e.g., coyote time) and building multiplayer features using Unity Netcode for GameObjects (authentication, lobbies, transport troubleshooting with UDP). Uses AI assistants pragmatically for repetitive code/architecture exploration while integrating changes manually to prevent regressions.”

“Frontend engineer who led end-to-end delivery of a customer-facing ticket booking platform at Simplii Financial, emphasizing scalable React architecture, performance (code-splitting/lazy loading), and accessibility. Also built a data-heavy real-time metrics dashboard at Q-TED using React + TypeScript with React Query for server-state, strong API contract validation practices, and tight QA/product/design collaboration for fast, stable releases.”

“Engineer with experience in regulated healthcare and financial systems, including a United Health healthcare service migration to AWS. Built documentation-as-code for CI/CD (Jenkins/Docker/Kubernetes/Terraform + GitHub Actions) that accelerated release cycles from 3 weeks to 4 days and tied security configuration (Spring Security/OAuth2/JWT) directly to HIPAA/GDPR compliance. Strong in observability-led incident response (ELK/Prometheus/Grafana) and performance tuning (PostgreSQL, async processing), citing MTTR reduction from 3 hours to 50 minutes and support for 250K+ concurrent users.”

“Master’s program project lead who built and deployed a real-time sound recognition system (Flask + React Native + ML) that was adopted by 200+ university students. Demonstrates strong production engineering and cross-layer debugging—solving latency, unreliable uploads, and observability gaps using microservice separation, chunked/idempotent transfers, and packet-capture-driven network diagnosis—plus AWS/on-prem and IoT edge-to-cloud integration experience.”

“Early-career CS/data professional with hands-on experience integrating analytics dashboards into a production MERN system, including a Redux state redesign and schema validation that delivered zero-downtime release and measurable performance gains (~30% faster APIs, 25% faster reporting). Previously a data analyst at Reliance Jio, where they extended Python-based reporting pipelines (CSV/MySQL) with automated validation and anomaly detection to improve KPI dashboard reliability and cut investigation time by ~30%.”

“Backend-focused engineer who owned an AI mentoring workflow platform built in Django with LangGraph multi-agent orchestration, optimizing it to stay under 200ms latency while scaling past 1,200 active users using profiling, caching, load testing, and OpenTelemetry-style tracing. Also has hands-on experience containerizing and deploying Python/ML services to AWS ECS via GitHub Actions/GitOps, and building reliable real-time pipelines with webhooks and Redis queues (idempotency, backpressure, DLQ).”

“Full-stack engineer focused on data-heavy platforms, building Spring Boot microservices and Angular/React dashboards end-to-end. Has hands-on experience improving large-scale API and UI performance (including cutting 8–10s response times) and ensuring cross-service consistency using Kafka, idempotent consumers, and strong validation/transaction patterns on AWS with CI/CD and observability (Prometheus/ELK).”

“LLM/RAG-focused engineer who repeatedly takes agentic workflows from impressive demos to dependable production using rigorous evals, SLOs, and deep observability. Has led high-impact incident mitigation (22-minute MTTR during a major sale) and developer enablement workshops, and partnered with sales to close a $410k ARR enterprise deal with a tailored RAG pilot (FastAPI/pgvector/Okta/InfoSec-ready).”

“QA automation-focused candidate with hands-on ownership of unit and integration test suites, including CI/CD integration in GitLab. Caught a database-query regression that would have shipped incomplete API data by relying on automated integration tests, and has practical Cypress experience stabilizing flaky tests using cy.intercept()/cy.wait() and stable selectors.”

John Kalyango

Screened

Senior Full-Stack Software Engineer specializing in geospatial and mobile data collection

Germany9y exp

“Frontend engineer who led end-to-end development of a React-based carbon credits data collection and analysis tool, focusing on scalable architecture and performance (code splitting, SWR caching, memoization, Lighthouse monitoring). Experienced building complex route-driven TypeScript wizards with Redux/Rematch state persistence, and refactoring legacy monolithic UI into reusable, tested, documented components while shipping deadline-driven features using feature flags and tight QA collaboration.”

Muhammad Waqas Ashraf

Screened

Senior Full-Stack Engineer specializing in AI, cloud infrastructure, and DevOps

Lahore, Pakistan7y exp

“Frontend engineer focused on building and scaling data-heavy, real-time dashboards with React/Next.js/TypeScript. Emphasizes performance and reliability at scale through modular architecture, centralized state (Zustand/Redux), strict API contracts, automated testing, and production monitoring (Grafana/CloudWatch), and has experience shipping quickly with feature-flagged rollouts and rapid iteration from user feedback.”

Sam Fish

Screened

Senior Full-Stack Engineer specializing in web platforms, cloud infrastructure, and data systems

Culver City, CA5y exp

“Full-stack/product-leaning engineer who owned an end-to-end AI Tutor feature (Claude-powered) shipped simultaneously to iOS/Android/web via Expo, with Cloudflare Workers backend and PostHog analytics. Built the company’s GitHub-based CI/CD to coordinate app store releases with backend blue/green deployments. Also has significant data engineering experience (including ~8TB/day workloads) using dbt/Fivetran plus sharding and hashing-based diffing for correctness.”

Aditi Deshpande

Screened

Mid-level Software/AI Engineer specializing in GenAI, AWS, and microservices

Remote, United States4y exp

“Built a production AI pipeline at EyCrowd to automatically grade shaky outdoor user-submitted brand videos using CV + CLIP/BLIP and a LangChain RAG layer per brand, with GPT-4 generating structured JSON explanations and grades. Optimized for latency and cost (batch PyTorch inference, caching), cutting review time from ~8 minutes to <2 minutes while reaching ~90% alignment with human graders and supporting thousands of videos/day.”

Abhishek Ingle

Screened

Junior Full-Stack & AI Software Engineer specializing in React/Next.js and LLM systems

Bloomington, IN2y exp

“Backend engineer with hands-on experience building low-latency, high-concurrency real-time chat on AWS (Node.js/Socket.IO/MongoDB) and improving reliability under unstable networks, contributing to ~40% user adoption growth. Also built FastAPI-based AI assistant context retrieval (RAG) APIs with embeddings/vector search, and has strong production experience in rate-limit handling, async refactors with safe rollout, and Supabase Auth/RLS optimization.”

Mahiyadav Sidda

Screened

Junior Machine Learning Engineer specializing in LLMs, RAG, and on-device AI

Bangalore, India2y exp

“Built an "Offline Study Assistant" that runs LLM inference locally on a 5-year-old Android device using Llama.cpp and the Android NDK, achieving a 27x speedup and cutting time-to-first-token from 11 minutes to 30 seconds. Also has applied backend/API experience with FastAPI, Supabase (Auth + RLS), and production hardening of a RAG system at Hashmint using Celery and Redis to eliminate PDF-processing-related query failures.”