Vetted FastAPI Professionals

“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.”

“Built and deployed an AI customer representative for iCore used at the IEE convention (2025), serving 100+ users in a day; implemented RAG with a vector database and scaled reliability via Docker and Google Cloud. Also has hands-on experience with multiple agent orchestration stacks (LangChain/LangGraph, Google AI Agent Development Kit, OpenAI SDK, Composio) and has delivered stakeholder-driven apps using prototyping and MVP scoping.”

“Built a solo full-stack equipment manager app for the game Dragon's Dogma, scraping a wiki with Beautiful Soup, transforming data to JSON, modeling armor/weapon schemas, and integrating everything into a PostgreSQL-backed API with caching. Dockerized and deployed the application to the web.”

“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.”

“Built and shipped a production AI-driven privacy automation system that autonomously navigates data broker sites to submit opt-out/data deletion requests end-to-end, including robust CAPTCHA detection/solving (e.g., reCAPTCHA/hCaptcha/Cloudflare) via 2Captcha. Experienced in orchestrating stateful LLM agent workflows with LangGraph and hardening them for production with strict state management, retries/fallbacks, validation layers, and database-backed observability/audit logs, collaborating closely with legal/compliance stakeholders.”

“Backend-focused developer who built LinguaTile (language learning app) on a FastAPI + MongoDB monolith deployed to Google Cloud Run, emphasizing async performance and security (RBAC/JWT, rate limiting, request tracing). Also created Mark-RS, a static HTML generator with a 100% CommonMark-compliant Markdown parser, demonstrating strong edge-case rigor and systems robustness.”

“Built a production automated resume matching system using Python, FAISS vector search, and Selenium-based job scraping, including mitigation for IP blocking and heterogeneous site structures. Also develops LLM/RAG applications with LangChain, using Pydantic-guardrailed structured outputs and LLM-as-a-judge evaluation (including a project focused on tone/semantics for a 3D avatar’s emotional responses).”

“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.”

“AI/LLM engineer who has owned end-to-end production delivery of multi-agent RAG systems on Azure (React + FastAPI + data pipelines + Terraform), including rigorous evaluation/monitoring and reliability guardrails. Shipped an AI-driven observability root-cause analysis assistant that reduced MTTR ~30%, cut alert noise ~20%, and reached ~70% adoption in the first month; also built a clinical document Q&A system with citations and compliance-oriented controls.”

“Currently working at CBS Lab in Austria, where they implemented/replicated the "Open World Grasping" research pipeline end-to-end. Built a ROS-based RGB-D perception-to-action system using SAM 2.1 segmentation and MoveIt motion planning to generate grasp poses and execute pick-and-place/sorting with a robotic arm.”

“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.”