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Vetted Amazon DynamoDB Professionals
Pre-screened and vetted.
Intern Full-Stack Software Engineer specializing in web platforms and IoT
Mid-Level Full-Stack Software Engineer specializing in AWS and RAG pipelines
Senior AI/ML Engineer specializing in NLP, LLMs, speech, and computer vision
Senior AI/ML Engineer specializing in NLP, LLMs, speech, and computer vision
Mid-level Python Backend Engineer specializing in microservices and AWS
Mid-Level Front-End Software Engineer specializing in React, Next.js, and TypeScript
Mid-level Full-Stack Developer specializing in Python, React, and cloud-native microservices
Senior AI/ML Engineer specializing in NLP, LLMs, speech, and computer vision
Mid-Level Software Engineer specializing in Java/Spring Boot microservices and cloud platforms
Intern Full-Stack Software Engineer specializing in AI-powered applications
Maulik Maganbhai Ghatala
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.”
Sudarshan Naicker
Entry-Level Software Engineering Student specializing in Full-Stack Web Development and ML
“Frontend-focused builder with multiple end-to-end academic product builds (event manager, niche social media app, airline booking site, AI-based obituary generator). Experienced in React/Next.js with an emphasis on scalable component architecture, pragmatic state management/performance, and strong collaboration with design via Figma; has shipped complex user flows like real-time chat, booking/seat selection, auth, and media upload under tight timelines.”
Andrew Fu
“Backend/infrastructure engineer in the EBS org focused on global server lifecycle and fleet reliability. Led a major modernization from manual, ticket-driven recovery to centralized Python services and operator tooling with DynamoDB-backed state, strong auth/allowlisting, and CloudWatch monitoring, plus an AWS Glue/S3/SNS data pipeline to join server and hardware datasets for global operational querying and automated recovery.”