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Experienced VP Software Engineering
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine Learning. Internet software. Search. EAI/Enterprise software. Mobile software. Social networking software. Viome. Oracle. Google. Yahoo. TIBCO. Motorola. Stanford. Specialties: Data Science. Distributed systems.Really large (web or otherwise) back-end systems. Search, data. Enterprise Integration and Real-time data. Mobile Software Infrastructure and Applications.
Stanford University
Doctor of Philosophy - PhD, Computer Science
N/A – Present
Stanford University
MSCS, Computer Science
N/A – Present
Indian Institute of Technology, Kanpur
B Tech, Computer Science
N/A – Present
St. Xavier School - Jaipur
High School, Math & Science
N/A – Present
Stealth Startup
Founder
October 1, 2023 – Present
Palo Alto, CA · On-site
Lighted Road Insurance
Co-Founder, CTO and VP Engineering
September 1, 2022 – October 1, 2023
Stealth Startup
Co-founder, CTO and VP Engineering
June 1, 2020 – September 1, 2022
San Francisco Bay Area
MachEye
VP Engineering
February 1, 2020 – May 1, 2020
San Jose, California, United States
Viome
VP Engineering
November 1, 2018 – February 1, 2020
Santa Clara, CA
Oracle
VP Engineering, Machine Learning
February 1, 2017 – June 1, 2018
Redwood City, CA
Engineering Director
February 1, 2008 – February 1, 2017
Yahoo!
Director, Software Engineering
June 1, 2005 – February 1, 2008
Motorola, Inc.
Senior Manager
February 1, 2003 – May 1, 2005
TIBCO Software Inc.
Manager
February 1, 1998 – December 1, 2002
Renaissance Software
Principal Engr
January 1, 1997 – February 1, 1998
SUNY Binghamton
Assistant Professor, Computer Science
January 1, 1993 – January 1, 1996
Cultural Fit Analysis
The candidate's diverse experience across large corporations (Google, Oracle, Yahoo!) and multiple startups, including founder roles, suggests a high degree of adaptability and a strong drive for innovation. Their background in search, machine learning, and data infrastructure aligns well with the demands of a Big Data Engineer role, particularly at a senior level where architectural and strategic contributions are expected. The breadth of their experience, from academic research to managing large engineering teams and founding companies, indicates a versatile individual who can thrive in various organizational cultures. However, the lack of specific project details makes it difficult to assess their hands-on contribution style in recent years.
Soft Skills & Operational Fit
The candidate's extensive leadership and entrepreneurial background suggests strong strategic thinking, problem-solving, and team management skills. Their history of working in various startup environments and large corporations indicates adaptability and resilience. The descriptions, though brief, imply a focus on impactful projects and technical leadership. However, without specific psychometric or communication test results, a detailed assessment of operational fit and soft skills beyond leadership is limited.