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Vetted FastAPI Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in generative AI and MLOps
Mid-Level Full-Stack Software Engineer specializing in cloud-native FinTech and ERP systems
Mid-level AI/ML Engineer specializing in financial risk, fraud detection, and NLP
Senior Full-Stack Engineer specializing in web platforms, e-commerce, and FinTech
Mid-level Backend Software Engineer specializing in Python microservices and cloud-native APIs
Intern Full-Stack Software Engineer specializing in AI-powered web applications
Senior GenAI Engineer specializing in LLM agents and insurance automation
Mid-level Full-Stack AI Engineer specializing in agentic LLM platforms
Mid-level Full-Stack Software Engineer specializing in cloud-native microservices
Senior Software Engineer specializing in backend systems, AWS cloud services, and data pipelines
Mid-level Machine Learning Engineer specializing in MLOps and applied data science
Mid-level Full-Stack Software Engineer specializing in GenAI and SaaS platforms
Mid-level AI Engineer specializing in NLP, computer vision, and MLOps
Mid-level Software Engineer specializing in full-stack systems and LLM evaluation
Nimsy Duddu
Mid-level AI/ML Engineer specializing in LLMs, RAG, and cloud MLOps
“Backend engineer with insurance/claims domain experience who modernized legacy claims processing systems to support AI-assisted claim review. Emphasizes production-ready API design in Python/FastAPI (schemas, async, caching, graceful degradation), strong observability with Prometheus, and layered security including JWT auth plus database row-level security (Supabase/Postgres).”
Nency Patel
Intern Backend Software Engineer specializing in AI and distributed systems
“Built and owned an enterprise AI document-processing deployment at an automotive tech startup, taking it from discovery to stabilization. Strong in production LLM/RAG systems and backend reliability, with measurable impact including 8,000+ documents processed monthly and turnaround time reduced from nearly 24 hours to about 3 hours.”