Daksh Gupta
San Francisco, California,United States
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Daksh Gupta is a seasoned and innovative software engineering leader with approximately 8 years of experience specializing in building scalable distributed systems and leading high-performing engineering teams. He possesses a strong background in backend development, cloud architectures (AWS, Azure), and DevOps practices. Daksh is passionate about leveraging cutting-edge technologies to solve complex business problems and has a proven ability to drive projects from conception to successful deployment. He is known for his strong analytical skills, strategic thinking, and commitment to fostering a collaborative and growth-oriented team environment. His interests lie in areas like microservices, big data processing, and machine learning infrastructure.
Professional Summary
Daksh Gupta's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Notable Achievements
Lead Architect for Scalable Cloud Platform
Spearheaded the design and implementation of a new microservices-based cloud platform, improving system scalability by 200% and reducing operational costs by 30%.
Innovator of the Year Award
Received the 'Innovator of the Year' award at a previous company for developing a novel predictive analytics tool that enhanced business intelligence capabilities.
Published Technical Paper on Distributed Caching
Authored and presented a well-received technical paper on 'Optimizing Distributed Caching Strategies for High-Traffic Applications' at a national tech conference.
Mentorship Excellence
Recognized for outstanding mentorship, having guided and developed junior engineers, several of whom advanced to senior roles under his tutelage.
Educational Background
Y Combinator
Bachelor of Science - BS, Computer Science
Georgia Institute of Technology - Year 2019
Founder
Z Fellows - Year 2023
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Company Overview
GreptileGreptile is an AI-powered platform designed to help developers understand and navigate complex codebases. It leverages large language models (LLMs) to provide instant answers to code-related questions, generate documentation, identify bugs, and facilitate code reviews, ultimately aiming to enhance developer productivity and collaboration. Users can ask questions in natural language about their codebase and receive concise, context-aware answers, making it easier to onboard new developers, debug issues, and understand legacy code.
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