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Vetted Celery Professionals
Pre-screened and vetted.
Mid-level AI Engineer specializing in LLM agents, RAG, and evaluation
Senior Full-Stack Engineer specializing in Python/Flask, React, and autonomous AI systems
Muhammad Midhat
Senior Full-Stack/Backend Engineer specializing in APIs, distributed systems, and AI integrations
“AI/backend engineer who has built and scaled production LLM-powered SaaS features (document assistant + compliance review agent) on a Node.js/TypeScript + Postgres/Redis stack deployed to GCP Kubernetes. Demonstrates strong production reliability chops—async queueing, autoscaling, observability, and database tuning—with quantified wins (p95 latency -60%, query 4s to <200ms) and robust AI guardrails (strict RAG, schema validation, citations, HITL).”
MUHAMMAD KHUSHAL KHAN
Mid-level Quantitative Developer specializing in low-latency trading systems
“Backend/ML engineer with deep fintech and marketplace experience: built a real-time financial analytics + algorithmic trading platform (Python/Postgres/Kafka/Redis) and drove major DB performance wins (10x faster analytics; sub-10ms response consistency). Also shipped an end-to-end ML recruitment matching platform (scraping/ETL/modeling/Django deployment) with reported 92% matching accuracy, and emphasizes production reliability via monitoring, blue-green deploys, and robust workflow error handling.”
Mid-level Python Developer specializing in cloud-native APIs and microservices
Mid-level Python Backend Engineer specializing in microservices and AWS
Junior Backend Engineer specializing in Python/Django and subscription-based systems
Mid-level Full-Stack Developer specializing in Python, React, and cloud-native microservices
Minh Huynh
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.”