Pre-screened and vetted.
Mid-Level Full-Stack Software Engineer specializing in Java/Spring microservices and cloud
Junior Full-Stack Software Engineer specializing in web apps, cloud, and ML inference
Mid-level Python Backend Engineer specializing in microservices and AWS
Entry-Level Full-Stack Software Engineer specializing in web applications and APIs
“Backend engineer who built and evolved ConGreG8 end-to-end: a stateless Node/Express REST API on MongoDB for fast, location-based church discovery. Demonstrates strong performance and operability discipline (instrumentation, p95 latency, slow-query analysis) with a reported ~30% response-time improvement, plus security depth via JWT/OAuth and Supabase-style row-level security. Experienced in safe refactors with contract preservation, dual-read validation, and incremental rollouts.”
Entry Backend Software Engineer specializing in Python/FastAPI and cloud-native APIs
“Backend engineer who built and evolved a low-latency document search platform (C++/gRPC on Kubernetes with a vector database), emphasizing resilience under concurrent load through strict deadlines, retries, idempotency, and observability. Also experienced building secure, frontend-friendly FastAPI services (Pydantic + JWT) and executing safe incremental refactors using feature flags and parallel validation.”
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.”
Junior Full-Stack Software Engineer specializing in AI and web applications
“LLM/AI backend engineer with hands-on experience taking customer LLM prototypes into production using FastAPI, containerization, CI/CD, and OpenTelemetry-based observability. Demonstrated measurable impact by cutting LLM costs ~40% and reducing workflow errors ~50% through schema-enforced outputs, better tool definitions, retries, and prompt/model optimization; also supports pre-sales via technical discovery and rapid integration demos.”
Intern Full-Stack Software Engineer specializing in AI-powered RAG systems
“Built FlowPilot, an AI-powered product that generates complete importable n8n workflows from natural-language prompts using a RAG pipeline (Qdrant + LangChain) and a multi-stage agent with a scoring/repair 'Judge' loop for intent alignment. Experienced in backend architecture across Laravel/Node microservices and production AI/RAG systems, plus performance debugging from async job offloading to database index tuning after ORM migrations.”