Pre-screened and vetted.
Mid-level Full-Stack Java Developer specializing in cloud-native microservices
Mid-level Full-Stack Developer specializing in React/Next.js and Spring Boot microservices
Mid-Level Software Engineer specializing in SaaS platforms and payments
Mid-level Java Software Engineer specializing in Spring Boot microservices on AWS
Senior Full-Stack Software Engineer specializing in Java/Spring microservices
Senior Full-Stack Java Developer specializing in cloud-native microservices for FinTech
Senior Full-Stack Software Engineer specializing in FinTech and Healthcare IT
Mid-Level Software Engineer specializing in Java microservices and event-driven systems
“Backend-focused engineer with experience spanning research and healthcare: owned a Python/SQL data pipeline that transformed vulnerability-fix code data from SQLite into model-ready JSON for LLM analysis. Also deployed Dockerized Spring Boot microservices to Kubernetes with Jenkins CI/CD and built Kafka-based real-time event streaming (appointment/report events) with idempotent consumers to avoid duplicate processing.”
Junior AI/Software Engineer specializing in NLP, RAG, and resume parsing
“Backend/AI engineer who built and refactored a production RAG system over IRS Form 990 filings for 60 nonprofits, using a dual-path architecture (deterministic financial ranking + TF-IDF semantic retrieval) to keep latency sub-2s and reduce hallucinations. Demonstrates strong API craftsmanship in FastAPI (contract-first, OpenAPI-driven) plus production-grade security for multi-tenant systems (JWT, RBAC, Supabase-style RLS) and careful migration practices (feature flags, traffic mirroring, incremental rollout).”
Mid-level Machine Learning Engineer specializing in real-time AI and data platforms
“ML/NLP engineer who has built production systems end-to-end: a real-time recommendation platform (100k+ profiles) using BERTopic-style clustering and a RAG-based news summarization/recommendation stack with ChromaDB. Strong focus on scaling and reliability (GPU batching, Redis caching, Kafka ingestion, Docker/Kubernetes, Prometheus/Grafana) and on maintaining model quality over time via drift monitoring and retraining triggers.”
Mid-level Full-Stack Python Developer specializing in AI/ML and backend APIs
“Python/Django backend engineer with open-source experience upgrading Archivematica to Django 4.2 LTS, including resolving a tricky breaking change in datetime parsing by implementing a preservation-safe legacy timestamp conversion layer. Also built a cost-efficient, reproducible Small Language Model (Microsoft Phi-3) fine-tuning pipeline that turns CSV product data into a domain-specific searchable Q&A chatbot, with emphasis on memory optimization and overfitting prevention.”
Mid-level AI/ML Engineer specializing in LLM-powered RAG systems and MLOps
Mid-Level Software Engineer specializing in cloud platforms, search/LLM systems, and payments
Mid-Level Backend Engineer specializing in scalable microservices and event-driven systems
Mid-level Backend/Full-Stack Software Engineer specializing in AWS, Node.js, and AI integrations
Junior Full-Stack Developer specializing in AI integrations and LLM research
Senior Full-Stack AWS Developer specializing in cloud-native microservices and serverless systems
Senior Full-Stack Developer specializing in cloud-native microservices (Angular/React, .NET, Java)
“Full-stack engineer with experience delivering an end-to-end NIH application using Angular and scalable .NET Core microservices backed by MySQL. Has hands-on depth in complex approval/workflow implementations (RBAC + workflow engine) and performance tuning for million-record, data-driven systems, plus 5 years with Java/Spring Boot microservices and React.”
Junior AI/ML Engineer specializing in LLM systems and personalization
“Backend engineer who built and scaled AmazonProAI, a multi-tenant SaaS platform for Amazon sellers, using a modular Django/DRF monolith with strict seller-level isolation and security controls. Led a controlled SQLite-to-PostgreSQL migration and hardened bulk Excel ingestion with idempotency and data integrity constraints to prevent duplicate metrics and noisy alerts while keeping the system ready for future service extraction.”
Mid-level QA Engineer specializing in cryptocurrency trading platforms
“QA tester focused on mobile, web, and API testing for complex real-time products (including crypto trading and multi-exchange integrations). Uses AI to accelerate test case creation and to summarize/analyze large logs and API responses, and brings a certification-blocker-first mindset to bug prioritization under tight submission deadlines.”