Pre-screened and vetted.
Mid-level Full-Stack & Cloud Engineer specializing in backend, AWS infrastructure, and DevOps
“IBM Power/AIX engineer who has owned a large production estate (20+ Power9/Power10 frames and 400+ LPARs) with vHMC and dual-VIOS HA. Has hands-on incident recovery experience (NPIV/RMC issues, LPM restores) and PowerHA failovers, plus modern DevOps exposure using Terraform on AWS and CI/CD with GitHub Actions/Jenkins (including deploying AI/RAG and vision workloads).”
Junior Full-Stack Software Engineer specializing in AI-powered SaaS
“Worked on an AI-adjacent search/results product with a React front end and an API-driven backend, focusing on scalability and performance. Emphasizes decoupled JSON API architecture, React rendering optimizations (useMemo/useCallback), and large-dataset techniques like virtualization, plus strong user-issue triage via log analysis and edge-case fixes in query handling/ranking.”
Mid-level Full-Stack Software Engineer specializing in AI-powered web applications
Mid-level Full-Stack Engineer specializing in healthcare, mobile apps, and AI
Junior Full-Stack Engineer specializing in serverless AWS and e-commerce platforms
Mid-Level Full-Stack Software Engineer specializing in AI-powered web applications
Mid-level Full-Stack Engineer specializing in web platforms and AI-enabled products
Mid-level Full-Stack AI Engineer specializing in web and generative AI solutions
Mid-Level Full-Stack & Mobile Engineer specializing in React, React Native, and serverless apps
Junior Full-Stack Engineer specializing in Next.js and modern web platforms
Mid-level Full-Stack AI Engineer specializing in agentic AI and RAG systems
Mid-level Applied AI Engineer specializing in LLM systems for EdTech and FinTech
Junior Full-Stack Engineer specializing in SaaS platforms across FinTech and HealthTech
Mid-level Full-Stack Engineer specializing in SaaS, AI, and Healthcare IT
“Fullstack engineer with roughly 3 years of experience who has independently built customer-facing systems in healthcare, including invoice notification infrastructure, nurse speech-to-text documentation, and a voice agent/chatbot workflow. Particularly interesting for teams needing hands-on builders who can ship end-to-end products with reliability features, real-time communication flows, and direct user-informed design.”
Mid-level Full-Stack AI Engineer specializing in LLM systems and RAG
“Built and shipped a production "Campaign AI" multi-agent system (LangGraph) that personalizes B2B outbound emails at scale using Apollo.io prospect data, clustering-based segmentation, and 21 persona variants. Notably uncovered that high click rates were largely email security scanners and created a validated bot-detection/scoring pipeline (timestamps/IP/user-agent/click patterns), bringing reported engagement down from ~40% to a trusted 5–8% that aligned with real conversions.”
Senior Full-Stack Software Engineer specializing in AWS, TypeScript, and scalable microservices
“Frontend engineer who led the end-to-end UI for a virtual trivia/multiplayer game, including architecture (component-driven + design system), quality practices (TypeScript, linting/formatting, unit + E2E tests), and real-time synchronization for ~100 concurrent players using Pusher. Emphasizes pixel-perfect, mobile-first responsive delivery with Tailwind and design tokens, plus ongoing refactors for reusability and performance.”
Mid-Level Full-Stack Engineer specializing in React, TypeScript, and Node.js
Mid-level Full-Stack Engineer specializing in scalable web applications
“Frontend-leaning full-stack engineer with hands-on experience building React/TypeScript applications backed by Node.js and GraphQL services. They highlighted a quiz-game product with complex frontend synchronization and an e-commerce optimization effort that raised homepage performance to roughly 90% in Lighthouse, while also creating reusable components and shared services to improve team velocity.”
Senior Full-Stack/Backend Engineer specializing in APIs, distributed systems, and AI integrations
“AI/backend engineer who has built and scaled production LLM-powered SaaS features (document assistant + compliance review agent) on a Node.js/TypeScript + Postgres/Redis stack deployed to GCP Kubernetes. Demonstrates strong production reliability chops—async queueing, autoscaling, observability, and database tuning—with quantified wins (p95 latency -60%, query 4s to <200ms) and robust AI guardrails (strict RAG, schema validation, citations, HITL).”