Vetted Cloud-Native Architecture Professionals

“Built a 0-to-1 iOS mobile gardening application that helps users plan, track, and harvest crops with pest control guidance, weather, and climate-zone-based planting date recommendations. Demonstrated strong customer discovery and MVP-first product execution, including a major data challenge: compiling US climate zone data for every ZIP code from widely dispersed public sources into an app-ready database.”

“Backend/data engineer who has maintained high-traffic FastAPI microservices and delivered a hybrid AWS serverless+containers platform using Terraform and GitHub Actions, with secrets managed via Secrets Manager/SSM. Also led modernization of a mission-critical 10,000+ line SAS financial reporting engine into Python microservices and built AWS Glue ETL pipelines feeding a centralized data lake.”

“Backend engineer at Discover who built and scaled Python/Flask services for a card dispute resolution platform, tackling long-running external network validations with Celery+Redis and delivering measurable gains (response time ~3s to <300ms; throughput +40%). Experienced in high-scale PostgreSQL/SQLAlchemy optimization (partitioning, read replicas, N+1 avoidance), event-driven systems with Kafka, and integrating ML fraud detection using AWS SageMaker/Lambda/ECS with clear separation of real-time vs batch processing.”

“Backend engineer with American Express experience maintaining an internal Python/Flask rewards simulation microservice used by product analysts and QA. Demonstrated strong performance and scalability work: moved batch simulations to Celery, added Redis caching to cut DynamoDB latency, and tuned Postgres/SQLAlchemy queries with EXPLAIN ANALYZE and composite indexes (bringing API responses under ~200ms by queueing jobs). Also has experience integrating ML via Flask-based model-serving APIs (scikit-learn/LightGBM packaged with joblib) and designing multi-tenant data isolation and tenant-specific configuration systems.”