Pre-screened and vetted in Illinois.
Mid-Level Backend Software Engineer specializing in distributed financial systems
“Full-stack engineer with fintech payments experience who shipped an end-to-end guest invoice payment flow emphasizing reliability under retries/failures (idempotency via DynamoDB, async processing with Lambda/EventBridge/SQS + DLQ). Also built a FastAPI backend with Cognito/JWT + scoped guest tokens and a polished React/TypeScript checkout UX, and has performance-focused Postgres/Redis design experience for flash-sale e-commerce workloads.”
Junior Software Engineer specializing in full-stack web development and test automation
“Full-stack engineer who built and owned a production workflow/kanban-style drag-and-drop system in Next.js (App Router) with Postgres/Prisma, including reusable component abstractions, Cypress E2E coverage, and post-launch performance/bug ownership. Notable for measurable impact (25% faster UI dev, ~30% query perf improvement) and for leading an incremental Express→NestJS migration that reduced technical debt (~40%) through better structure, docs, and team enablement.”
“Backend-focused engineer with deep healthcare interoperability experience, building Go-based distributed systems for live clinical data exchange across hospital systems. Stands out for combining startup-style ownership with HIPAA/compliance rigor, including creating a reusable Go microservice template and improving reliability across Kafka, PostgreSQL, and Kubernetes-based production platforms.”
Senior Full-Stack Developer specializing in Node.js/TypeScript, cloud, and data engineering
“Frontend/fullstack lead who inherited a messy psychological app with production issues, drove a rapid stabilization (2–3 weeks) and major performance/architecture overhaul (Redux Toolkit, memoization, caching, lazy loading, CDN offload to S3/CloudFront). Also owns delivery and infrastructure practices (multi-env, Docker, GitHub Actions CI/CD, AWS ECS + load balancing) and led a 1-week POC for an AI-powered trucking management system (app.neblo.ai).”
Mid-level Full-Stack Software Engineer specializing in AI-augmented web and mobile systems
“Builder-oriented engineer who has shipped production systems across fintech-style payments, mental health recommendations, industrial oil-and-gas analytics, and AI-assisted client discovery. Stands out for combining deep backend reliability practices with founder-facing product scoping, and reports using Claude-based internal tooling to increase delivery capacity by 40% and handle eight concurrent projects.”
Junior Machine Learning Engineer specializing in real-time inference and production ML systems
Junior Software Engineer specializing in C++ systems, HPC backends, and ML infrastructure
Mid-level Software Engineer specializing in Python automation and Agentic AI (RAG)
Senior Software Engineer specializing in cloud-native microservices and distributed systems
Mid-level Machine Learning Engineer specializing in multimodal vision-language models
Senior Python/Django Full-Stack Engineer specializing in cloud-native web applications
Mid-level Software Engineer specializing in AI and Cloud Infrastructure
Junior Software Engineer specializing in data-heavy frontend dashboards (Vue/Nuxt, React)
Mid-level AI/ML Engineer specializing in computer vision and generative AI
Mid-Level Software Engineer specializing in SaaS platforms and payments
Mid-level Full-Stack Engineer specializing in FinTech and real-time systems
Junior Software Engineer specializing in serverless automation and full-stack web development
Mid-level Data Engineer specializing in cloud ETL and big data pipelines
“Data engineer focused on building reliable, production-grade pipelines and data services end-to-end, including a 50+ GB/day pipeline ingesting from APIs/files into Snowflake with PySpark/SQL transformations. Emphasizes strong data quality controls, monitoring/retries, and performance optimization, and has also shipped a Python data API with caching and backward-compatible versioning.”
Mid-level Full-Stack Engineer specializing in AI-powered web platforms
“Solo builder of ZenDSA, a live AI-powered DSA learning product with 37 real users, built end to end using Java/Spring Boot, React, and TypeScript. Particularly interesting for teams building AI products: they designed a production LLM fallback architecture, enforced structured JSON outputs, monitored parse-failure regressions, and fixed an SSRF vulnerability after launch.”