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Vetted Amazon S3 Professionals
Pre-screened and vetted.
Senior Full-Stack Software Engineer specializing in cloud-native microservices and FinTech
Senior Data Scientist specializing in Generative AI, NLP, and MLOps
Mid-level Full-Stack Engineer specializing in React and Java microservices
Senior DevOps / Cloud / Site Reliability Engineer specializing in AWS and Kubernetes
VP Data Engineer specializing in AI-driven analytics platforms for investment management
Mid-level Full-Stack Engineer specializing in cloud-native microservices and data integrations
Junior Full-Stack Software Engineer specializing in SaaS and AI-powered web apps
Mid-Level Backend Software Engineer specializing in Java/Spring Boot microservices on AWS
Senior Data Engineer specializing in cloud data platforms and real-time pipelines
Mid-Level Software Engineer specializing in AI platforms and backend systems
Mid-level Software Engineer specializing in backend microservices and cloud-native systems
Mid-level Data Engineer specializing in cloud data platforms and streaming pipelines
Mid-level Data Engineer specializing in AI/ML data platforms and real-time streaming
Mid-level Data Engineer specializing in cloud lakehouse and streaming pipelines
Executive Product & Technology Leader specializing in AI and healthcare platforms
Khaliun Gerel
Senior Full-Stack Engineer specializing in cloud, web, and mobile platforms
“Full-stack product engineer who has owned end-to-end delivery of multi-client platforms: Finy (agriculture platform with 3 role-based web dashboards plus 2 field mobile apps) and Ugoku (Japanese studio platform with React/TypeScript dashboards, Node/Mongo backend, and mobile AR video playback). Strong in scalable architecture and performance—offline-first mobile for low connectivity, and AWS-based asynchronous video/AR processing with S3/CloudFront—plus building internal ops tools adopted quickly due to measurable workflow improvements.”
Abhishikth Meesala
Mid-level AI/ML Engineer specializing in NLP, Generative AI, and fraud detection
“At PwC, built and productionized an agentic RAG enterprise search assistant over 6M internal documents (8M embeddings), deployed across AWS and GCP. Drove major retrieval gains (72%→92% precision via BM25+dense hybrid with RRF and cross-encoder re-ranking), reduced hallucinations 30%, achieved <2s latency at 50–60K queries/month, and cut support tickets 30%—boosting adoption to 2,500 users by adding source-cited answers.”
JYOTHI N
Senior Data Scientist specializing in analytics, experimentation, and BI on AWS
“Data/ML practitioner focused on healthcare data quality and record linkage: analyzed 10M+ records, built anomaly detection and NLP-driven entity resolution, and automated AWS ETL/validation pipelines (Glue/Redshift/Lambda), cutting data errors by 40% and generating $500k in annual savings. Has hands-on experience with embeddings (Sentence Transformers/spaCy), FAISS vector search, and fine-tuning for domain-specific matching.”
Longyang Xu
Junior Full-Stack Software Engineer specializing in cloud microservices and ML-driven products
“Backend engineer with hands-on ownership of Python/Flask microservices and recommendation systems across edtech and telecom. Deployed and operated real-time personalization/recommendation platforms on AWS EKS with Jenkins-based CI/CD, GitOps-style declarative configs, and strong observability practices. Has migration experience moving legacy mixed environments to modern containerized Kubernetes and built Kafka pipelines feeding ML services while managing schema evolution.”
Matthew Mullins
Senior Software Engineer specializing in AI/ML backend and cloud infrastructure
“Backend/data platform engineer with production experience at Walmart and Molina Healthcare, building Python microservices on AWS (EKS + Lambda) for real-time inventory and recommendation systems. Strong in reliability/observability and incident leadership, plus modernizing legacy healthcare workflows and building resilient AWS Glue/PySpark pipelines with schema evolution and data quality controls.”