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Vetted Amazon Redshift Professionals
Pre-screened and vetted.
Executive engineering leader specializing in FinTech, payments, and cloud platforms
Mid-level DevOps & MLOps Engineer specializing in cloud-native CI/CD and Kubernetes
Mid-Level Full-Stack Software Engineer specializing in microservices and cloud
Mid-level Machine Learning & Generative AI Engineer specializing in enterprise RAG and MLOps
Mid-level Data Scientist specializing in ML, MLOps, and forecasting for FinTech and AI hardware
Senior Full-Stack Engineer specializing in cloud architecture and AI/ML integration
Mid-level Full-Stack Java Developer specializing in microservices and cloud platforms
Mid-level Full-Stack Software Engineer specializing in cloud-native data platforms
Mid-Level Full-Stack Software Engineer specializing in Java/Spring Boot microservices
Mid-level Data Engineer specializing in cloud-native ETL and data warehousing
Senior Full-Stack Software Engineer specializing in cloud microservices and GenAI
Senior AI/ML Engineer specializing in GenAI, MLOps, and healthcare analytics
Mid-level Data Engineer specializing in AWS lakehouse and Spark pipelines
Senior Data Engineer specializing in Cloud Data Platforms and Generative AI
Junior Data Analyst specializing in finance, supply chain, and GTM analytics
Principal Data Scientist specializing in LLMs, RAG, and enterprise AI products
Johnnie Sanders
Executive AI Architect specializing in enterprise cloud and FinTech solutions
“Candidate brings an operator-to-founder profile with leadership experience in IT and Business Systems and a strong grasp of how ideas become venture-backable products. They speak fluently about startup evaluation criteria such as TAM, technical defensibility, speed to scale, and AI differentiation, and appear especially motivated by building solutions end-to-end in startup or venture studio environments.”
NEHA KOLAN
Mid-Level Software Engineer specializing in microservices and cloud data pipelines
“Full-stack engineer with end-to-end ownership across React/TypeScript frontends, Spring Boot/Node microservices, and production ops on Docker/Kubernetes and AWS (ECS/CloudWatch). Built real-time healthcare eligibility and analytics systems at Cigna and an early-stage seller onboarding platform at Flipkart, driving measurable performance gains (35–40% latency/throughput improvements) through event-driven Kafka pipelines, Redis caching, and strong reliability/observability practices.”
Timothy Wong
Mid-level Data Engineer specializing in experimentation, analytics, and AI-driven product experiences
“Built production LLM automations using the Claude API, including a sales enablement workflow that summarizes playbooks and incorporates sales call metadata into strategic one-pagers. Experienced in orchestrating and scheduling data pipelines with SnapLogic, Airflow, and Databricks, and in scaling LLM API calls via parallel/batch processing. Also partnered with HR to deliver prompt-tuned, automated Slack messaging aligned to business tone and acceptance criteria.”