Greg Robinson is a seasoned and results-driven technology leader with over 15 years of experience specializing in cloud architecture, DevOps methodologies, and full-stack software development. He has a strong track record of building and scaling resilient, high-performance systems for SaaS platforms and enterprise applications. Greg is passionate about leveraging emerging technologies to solve complex business challenges and is adept at leading cross-functional teams to deliver innovative solutions. He is known for his strategic thinking, problem-solving skills, and ability to bridge the gap between technical and business stakeholders.
Greg Robinson's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Led a major cloud migration project to AWS for a legacy enterprise system, resulting in a 30% reduction in operational costs and a 50% improvement in system scalability and reliability. Implemented robust CI/CD pipelines, reducing deployment times from days to hours.
Architected and spearheaded the development of an innovative AI-driven analytics platform that provided actionable insights from large datasets, leading to a 20% increase in customer retention for key clients by enabling personalized service offerings.
Successfully scaled a software engineering team from 5 to 25 members within two years, establishing agile development practices, mentorship programs, and a culture of continuous improvement that significantly boosted team productivity and morale.
Awarded 'Innovator of the Year' by a previous employer for designing a patented algorithm that significantly enhanced data processing speeds for their core product.
Clemson University - Year 2006
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AutoFi is a financial technology company dedicated to streamlining the automotive sales process for dealers, OEMs, and lenders. Its platform enables a complete digital car buying and financing experience, allowing customers to secure financing, value trade-ins, and select protection products online or in-store, ultimately aiming to reduce transaction times and improve customer satisfaction.
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