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Vetted Amazon DynamoDB Professionals
Pre-screened and vetted.
Senior Software Engineer specializing in frontend platforms for FinTech and e-commerce
Mid AI/Machine Learning Engineer specializing in LLMs, NLP, and Computer Vision
Mid-level AI Software Engineer specializing in Generative AI and FinTech
Junior Frontend Software Engineer specializing in FinTech and crypto products
Senior Software Engineer specializing in AWS serverless backend and data engineering
Mid-level Data Scientist specializing in GenAI, LLMs, and MLOps
Senior Software Engineer specializing in cloud microservices and data pipelines
Intern Backend/Full-Stack Software Engineer specializing in cloud-native web systems
Junior Data Scientist & Data Engineer specializing in ML and scalable data pipelines
Staff Product Manager specializing in FinTech and enterprise SaaS platforms
Mid-level Software Engineer specializing in distributed systems and full-stack development
Mid-level Full-Stack Software Engineer specializing in cloud-native and data platforms
Mid-level Full-Stack Software Engineer specializing in AI-powered applications
Executive Engineering Leader (CTO/VP) specializing in platform scaling and video streaming
Ethan Pribble
Senior Software Engineer specializing in cloud cost intelligence and FinOps platforms
“Backend/data engineer with strong authorization and compliance-domain experience: led a phased migration from a simplistic role model to modern RBAC on a Python serverless stack (Auth0 + AWS Lambda/API Gateway), coordinating changes across 5 repos with extensive manual and automated validation. Previously built and operated custom ETL pipelines (Airflow + Groovy/Java on Spark/YARN/Hadoop) to normalize messy customer email/chat/voice data for NLP-driven financial compliance indicators, including complex email journaling metadata enrichment and large-scale remediation reprocessing after production bugs.”
Paul Liu
Senior Software Engineer specializing in cloud-native backend and web/mobile apps
“Backend engineer with Tesla experience building Python-based, serverless microservices for a supply chain portal, including a MongoDB-backed tracking/logging system and a reconciler Lambda to manage retries and failures. Has hands-on Kubernetes (EKS) and GitOps (Argo CD) experience, plus real-time Kafka pipelines for fleet/IoT telemetry and proxy-based migrations from monolith systems to AWS databases.”
Jagadeesh Kakamolu
Mid-level Software Engineer specializing in backend, cloud, and AI systems
“Engineer with hands-on experience across backend, full-stack, cloud, and AI/ML systems, with particular depth in Python, FastAPI, AWS Bedrock, SageMaker, and RAG-based architectures. Stands out for treating AI and agents as accelerators within disciplined production engineering, emphasizing guardrails, observability, latency/cost monitoring, and scalable system design.”