
Enterprise grade Observability for agentic applications
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Software engineer with infrastructure and platform experience building Machine learning platforms from ground up, distributed systems, high performance large scale computing and ML-OPS. Passionate on solving 0-1 problems, sharing and contributing back to the community through conferences and open source contributions
University of Southern California
MS, Computer Science
N/A – Present
B. M. S. College of Engineering
B.E., Computer Science
N/A – Present
Fiddler AI
Senior Staff engineer / TLM
September 1, 2025 – Present
Palo Alto, California, United States
Fiddler AI
Staff Engineer / TLM
August 1, 2024 – September 1, 2025
Palo Alto, California, United States
Fiddler AI
Staff Software Engineer
August 1, 2023 – August 1, 2024
Palo Alto, California, United States
Lyft
Senior Machine Learning Platform Engineer
August 1, 2021 – June 1, 2023
United States
Quantcast
Senior Software Engineer
October 1, 2015 – August 1, 2021
San Francisco Bay Area
Undertone
Senior Software Engineer
February 1, 2014 – October 1, 2015
San Francisco Bay Area
Goldman Sachs
Analyst Developer
May 1, 2010 – February 1, 2014
Greater New York City Area
Bloomberg
Financial Software Developer
February 1, 2009 – May 1, 2010
Greater New York City Area
Yahoo!
Software Intern
May 1, 2008 – August 1, 2008
San Francisco Bay Area
Infosys
Software Engineer
June 1, 2006 – July 1, 2007
Bengaluru Area, India
IBM
Software Intern
January 1, 2006 – January 1, 2006
Bengaluru Area, India
Cultural Fit Analysis
The candidate has a diverse background across various industries (finance, ad-tech, ride-sharing, AI observability) and company sizes (Goldman Sachs, Bloomberg, Lyft, Fiddler AI). This breadth of experience suggests adaptability and a willingness to tackle different problem domains, which generally aligns well with dynamic, innovative cultures. The consistent progression into leadership roles indicates ambition and a drive for impact. However, the lack of explicit project details or community involvement makes it difficult to fully assess cultural alignment beyond professional experience.
Soft Skills & Operational Fit
The candidate's resume indicates strong cross-team collaboration and mentoring experience, suggesting good operational fit and leadership potential. The progression through senior and staff-level roles, including TLM, points to strong soft skills in technical leadership and project ownership. However, without specific psychometric test results, a definitive assessment of stress handling or team collaboration beyond what's implied by role descriptions is not possible.