Alex Burciu

Tech Venture Partner

2021 - Current

- finding and evaluating tech startups for investments in: capital, sweat equity / joint ventures and M&As - running a venture lab (startup studio) for discovering opportunities, creating and spinning out startups

Angel Investor

2018

10+ tech startup seed investments across Romania and Europe: Bitstamp, Nifty Learning, ThinkOut, Pixteller, iFactor, Metabeta, Event Mix, Cart Loop, Telios, Origin Protocol, Enjin, Uniswap, Curve, Telos, Chintai

Short Term Consultant

2020 - 2021

Building the Romanian Startup Ecosystem Strategy for the following pillars: - Research & Development and Innovation - Infrastructure and Support Programs

Innovation Manager

2019 - 2020

Led the Applied AI Research program where startups/companies access Machine Learning Research Services to accelerate their R&D. Co-founded two internal start-ups to commercialize existing research as spin-offs. One of them was accepted to How To Web Startup Spotlight, the other received an innovation grant.

Technical Program Manager

2017 - 2019

I designed and ran the product development part of the acceleration program together with selection & evaluation of the best technical startups to enhance their progress on executing their vision up to demo-day. Contributed to creating the KPMG Startup Grow Pad and mentored deep-tech startups in the cohort on Product Development. I'm was empowering startups with a customer-centric product development approach, processes, tools, technologies, know-how and mentors to facilitate innovation and transparent growth for getting successful investments in order to scale globally.

Software Development Manager III

2013 - 2016

I built and ran a software development organization within Amazon Consumer Website with two teams that I founded: Client-Side Metrics and Robot Detection. Grew the staff from 3 engineers to 17 full time employees organized within 3 teams (each led by a Software Development Manager). Their composition was mainly of Software Development Engineers, but it included roles such as Business Intelligence Engineer, Data Scientist and Machine Learning Scientist. Most of the hiring was done by myself. As a Bar Raiser with more than 300 interviews, I contributed with hiring decisions for at least 30% of the technical staff within the entire development center. I also helped interviewing candidates for other office locations and for non-tech roles. My main focus was people management, product management and project management. I was in charge of customer connection, strategic direction, and securing business growth for my teams. Some highlights of both teams relate to S-team goals (highly visible company-wide initiatives owned by the senior leadership team under Jeff Bezos): * powered the Latency Reduction Program with reporting metrics and diagnosing data (hundreds of teams within Amazon were able to optimize their pages and bring down latency for key pages such as Product Detail Page from more than 6 seconds to less than 1 second, median) * instrumented the website for JavaScript errors and their exact source to minimize them * gathered information about non-secure popups for eliminating them, thus allowing migration of the website to HTTPS * accurately classified website visitors as human/robot for blocking unwanted robot traffic at peak times, avoiding buying website hardware worth millions of dollars * expanded robot detection for continuously blocking unwanted robots while keeping CAPTCHA solves within very aggressive thresholds, saving tens of millions of dollars per year in terms of website hardware

Software Development Manager II

2011 - 2013

Website Application Platform: Client-Side Metrics & Robot Detection The Client-Side Metrics team measures the web performance as perceived by millions of customers across billions of daily rendered pages across all Amazon's e-commerce websites. It enables internal teams to reduce page load times, detect/diagnose spikes and eliminate latency regressions to make the websites faster for a better customer experience. Other browser data is also distributedly processed for determining the full picture of customers' in-page interaction, allowing data-driven usability improvements. The Robot Detection team analyzes billions of weekly website hits using sophisticated algorithms and detection models to identify robot traffic. The separation of robots out of customer traffic allows internal teams to improve their services' availability, reduce TCO, gather accurate business metrics, and provide the best experience to both customers and robots.

Software Development Engineer II

2010 - 2010

Retail Customer Experience - Entity Customer-facing projects for Brands, Authors, Artists and TV Series on Amazon.com.

Software Development Engineer I

2008 - 2010

Retail Customer Experience - Tags Web application development on Community Tagging for the retail website: amzn.com/tags.

Network Engineer Intern

2007 - 2007

Managing and configuring NOC devices, network monitoring and technical support.

Freelance Web Developer

2005 - 2006