Pre-screened and vetted in the Greater Seattle.
Mid-level Full-Stack Software Engineer specializing in AI-powered applications
Mid-level Software Engineer specializing in AI/ML and full-stack systems
“Engineer with Apple experience building LLM-powered internal workflow orchestration systems using Python, LangGraph, FastAPI, Redis, vector search, and Kubernetes. Stands out for a highly pragmatic, production-focused approach to agentic systems: deterministic state management, strong guardrails, observability, and human review for high-risk actions.”
Entry-level Full-Stack Engineer specializing in AI-powered backend systems
Mid-level Software Engineer specializing in AWS, full-stack development, and AI data systems
“Backend engineer who built a Python-based data profiling/statistics platform processing up to 50M rows and ~300 metrics, using a DAG execution model, multithreading, and smart caching to cut processing time by up to 70%. Also improved PostgreSQL query performance from 12s to 2s via indexing/query rewrites, integrated an LLM (LangChain + OpenAI) for explainable “chat with the pipeline” functionality, and designed an AWS EC2+SQS architecture for scalable, isolated per-user processing.”
Mid-Level Full-Stack Java Developer specializing in microservices, cloud, and AI integrations
Mid-level Full-Stack Software Engineer specializing in React/Next.js and AI-powered document tools
Senior Full-Stack Engineer specializing in scalable web applications
Junior Full-Stack Software Engineer specializing in backend, cloud, and AI systems
Mid-level Full-Stack Software Engineer specializing in FinTech and real-time systems
“Full-stack product engineer with a strong real-time systems focus: built and rolled out a WebSocket-based notifications system (with robust reconnect/resync and event ordering protections) that cut update latency to under 200ms. Also owned a workflow automation platform backend in FastAPI (JWT/RBAC, versioned APIs, standardized errors), designed the PostgreSQL schema for workflows/tasks/executions, and operated deployments on AWS ECS Fargate with blue-green CI/CD and performance stabilization via caching and autoscaling.”