.png){kind=logo}
Vetted pytest Professionals
Pre-screened and vetted.
Mid-Level Software Engineer specializing in FinTech data pipelines and backend APIs
Mid-level AI/ML Engineer specializing in LLM agents, RAG pipelines, and AI automation
Mid-Level Software Engineer specializing in full-stack web apps and cloud-native APIs
Senior Full-Stack Engineer specializing in cloud-native SaaS and AI-integrated platforms
Junior Software Engineer specializing in Python microservices and full-stack web development
Mid-Level Full-Stack Developer specializing in ERP integrations
Mid-level Full-Stack Developer specializing in Java/Spring Boot, React, and AI/ML APIs
Mid-Level Full-Stack Software Developer specializing in cloud-native web applications
Mid-level Software Engineer specializing in backend systems, data pipelines, and AI/RAG
Mid-level Full-Stack Engineer specializing in backend systems and AI integration
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices
Intern Software Engineer specializing in cloud infrastructure, DevOps, and AI-enabled systems
Junior Full-Stack Software Engineer specializing in Python/React and AI-powered web apps
Mid-Level Full-Stack Software Engineer specializing in cloud microservices and Voice AI
Senior Full-Stack AWS Developer specializing in cloud-native microservices and serverless systems
Kealan Doherty
Junior Software Engineer specializing in full-stack web and AI applications
“Early-career backend developer building an Arc Raiders game-data API end-to-end in Go on AWS with PostgreSQL, making their first real deployment and learning system design hands-on. Also built an AI resume and cover letter generator using Gemini and has experience debugging open-source code and managing PRs in a capstone team project.”
Muhammad Midhat
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).”