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Vetted Scrum Professionals
Pre-screened and vetted.
Senior Full-Stack Software Engineer specializing in cloud-native distributed systems and AI
Staff-level Software Engineer specializing in LLM inference infrastructure and scalable model serving
Senior Full-Stack Engineer specializing in AI/ML platforms and cloud-native systems
Max Zhu
Staff Software Engineer specializing in Cloud Healthcare Data Platforms
“Backend/data engineer with deep healthcare data experience (FHIR, de-identification) across both GCP and AWS. Has built and operated production microservices and ETL pipelines (FastAPI, Dataflow, Glue) with strong reliability practices, and led modernization of a legacy SAS compliance reporting system to cloud services with validated parity and stakeholder-facing Looker comparisons.”
Senior Backend Engineer specializing in AWS cloud-native systems and data workflows
Senior Software Engineer specializing in cloud platforms and healthcare AI
Senior Software Engineer specializing in distributed systems and high-scale backend platforms
Senior Full-Stack Engineer specializing in AI platforms, real-time collaboration, and observability
Senior Full-Stack Engineer specializing in AI platforms and distributed systems
Principal Data Scientist & AI/ML Engineer specializing in LLMs, recommender systems, and MLOps
Senior Python Developer specializing in FinTech and RegTech payment systems
Staff Full-Stack Software Engineer specializing in cloud platforms and real-time health data
Mid-level AI/ML Engineer specializing in LLM training, RAG, and scalable inference
Executive AI/ML Engineer specializing in LLMs, NLP, and production ML systems
Senior AI/ML Engineer specializing in LLM applications, RAG systems, and MLOps
Senior Software Engineer specializing in full-stack systems and ML-driven platforms
Senior VR Engineer specializing in Unity game systems and multiplayer experiences
Nathan Telles
Staff Software Engineer specializing in distributed systems, cloud platforms, and AI services
“Meta engineer who owned end-to-end production systems for AI-enabled smart glasses, spanning React/TypeScript apps through Node/Java microservices on AWS EKS with Kafka/Postgres. Built and productionized a real-time RAG pipeline (LangChain + OpenAI + Elasticsearch) with rigorous guardrails (shadow/canary, fallbacks, monitoring), delivering major improvements in latency (~35–40%), error reduction (~30%), and engagement (reported +40% DAU).”
Upender Mula
Mid-level Software Engineer specializing in backend systems, real-time data pipelines, and FinTech
“Backend/platform engineer who has owned real-time reporting and streaming analytics systems end-to-end, combining FastAPI/Postgres APIs with Kafka consumers, Celery background jobs, and Redis caching. Strong DevOps/GitOps experience deploying Python/Node microservices to AWS EKS with Helm, ArgoCD/FluxCD, and CI pipelines, and has supported phased on-prem to AWS migrations using Terraform and traffic cutovers.”
Neeraj Sharma
Executive Engineering Leader specializing in AI/ML platforms and cloud-scale distributed systems
“Senior engineering/technology leader with experience driving board-backed, multi-year platform transformations in retail commerce (American Eagle) and scaling ML/product delivery platforms at Amazon Alexa. Known for data-driven build-vs-buy decisions, org scaling (6→80), and measurable outcomes including 98.5%→99.9% uptime, 234 experiments generating ~$200M revenue lift, and increasing delivery velocity from 1.5 to 30 features/week while transitioning to DNN/large-model architectures.”
Pradeep Nadella
Mid-level AI/ML Engineer specializing in LLM optimization and real-time fraud/risk modeling
“ML engineer with 5 years at Stripe building and productionizing real-time fraud detection at massive scale (3M+ transactions/day; $5B+ annual payment volume). Delivered measurable impact (22% accuracy lift, 18% loss reduction, +3–5% authorization rates) and has strong MLOps/orchestration experience (Docker, Kubernetes, Airflow, MLflow, CI/CD, monitoring/rollback) plus a structured approach to LLM agent/RAG evaluation.”
Mid-level AI/ML Engineer specializing in LLM training, RAG, and scalable inference
Staff-level Software Engineer specializing in distributed systems and cloud platforms