Vetted Amazon Redshift Professionals

“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.”

“Hands-on engineering leader currently at Vianai (GenAI enterprise applications) building AI-assisted data exploration/insights products with Python and React. Previously Corporate VP of Digital Health at Samsung Electronics, where they helped close key partner deals by demonstrating API-driven openness and led a major Samsung Health modernization from monolith to microservices for horizontal scalability and faster, safer iteration.”

Jesse Olson

Screened

Executive AI technology leader specializing in agentic AI and enterprise transformation

22y exp

“Candidate is exploring a startup in the autonomous agentic AI space and is approaching it with a disciplined founder mindset. They are evaluating market opportunity, competition, customer pain, ROI, technical feasibility, and MVP options while already speaking with potential customers across verticals to validate needs and buying processes.”

“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.”

“Software development manager who led development of the open-source AI agents framework Strands (for Amazon Bedrock), which launched mid-year and is used as a primary agent-development framework at Amazon and externally. Owned the Strands SDK end-to-end, drove adoption through stakeholder management and agile execution, and led a JavaScript-to-TypeScript migration to improve type safety and maintainability.”

“Built and deployed a production LLM conversational AI system at OpenAI supporting chat, summarization, and semantic search at 1M+ requests/day, driving major latency (40%) and accuracy (25%) improvements through Pinecone optimization and tighter RAG with re-ranking. Also has Amazon experience improving recommendation systems by translating ML metrics into business terms to boost CTR and conversions, with strong MLOps/orchestration depth (Airflow, MLflow, SageMaker, Kubeflow).”