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Director of AI at SEEK / Stanford GSB
AI and technology executive with 25+ years of experience building, scaling, and governing digital platforms in high-growth, global environments. My career spans hands-on entrepreneurship and senior executive leadership, with a consistent focus on turning advanced technology into durable, responsible, and commercially meaningful outcomes. At SEEK, one of the world’s largest online employment platforms (ASX top-60, ~6,000 employees, ~AU$10B market cap), I lead Global AI, Data Science, Generative AI, Responsible AI, and Ontology teams across Australia, Brazil, China, Southeast Asia, and Latin America. My work sits at the intersection of GenAI delivery, AI policy / governance, and operational scale, partnering closely with engineering, product, legal, risk, and executive leadership to deploy AI systems that are both high-impact and trustworthy. I have led the transition from traditional machine learning to large-scale GenAI and LLM-based systems, establishing Responsible AI frameworks, internal policy and governance models that enable innovation while managing real-world risk. This includes building teams, platforms, and operating models that move fast without breaking trust. Previously, as entrepreneur and CTO at boo-box, I built and scaled the company’s core technology in a hyper-growth environment. Boo-box was recognized by Fast Company as one of the World’s Most Innovative Companies. Across roles, I bring a general management mindset, strong technical depth, and comfort operating across strategy, execution, governance, and culture, especially where AI, regulation, and business growth collide. #Bitcoin / #DeFi enthusiast. SEO: Artificial Intelligence (AI), Generative AI, GenAI, Large Language Model, LLM, AutoGen, Data Science / Data Scientist, CTO, Entrepreneurship, Venture Capital, M&A, Big Data, Machine learning
Stanford University Graduate School of Business
Stanford Executive Program (SEP), General Business Administration
June 1, 2022 – July 1, 2022
Universidade Anhembi Morumbi
Bacharel, Computer Science
January 1, 2002 – January 1, 2005
SEEK
Director of AI - APAC
July 1, 2023 – Present
SEEK
Global Director of Artificial Intelligence / Machine Learning
July 1, 2015 – June 1, 2023
Catho
Head of Innovation & Artificial Intelligence
December 1, 2012 – June 1, 2015
São Paulo Area, Brazil
IAB
Chairman of Brazilian IAB's Committee of AdNetworks and AdExchange / AdTech & Data
September 1, 2011 – January 1, 2013
São Paulo Area, Brazil
boo-box
Entrepreneur & CTO/COO
May 1, 2009 – May 1, 2013
São Paulo
XnX
CTO
September 1, 2008 – May 1, 2009
Sao Paulo, Brazil
Inova Inc
Engineering Manager
January 1, 2005 – September 1, 2008
Sao Paulo, Brazil
Voxel Informática
Engineering Manager
January 1, 1999 – December 1, 2004
Sao Paulo, Brazil
Stanford Executive Program
Stanford Graduate School of Business
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse background spanning leadership in large corporations (SEEK, Catho) and entrepreneurial ventures (boo-box, XnX). This blend suggests adaptability and a comfort with both structured environments and fast-paced, innovative settings. Their involvement with IAB and global teams indicates a collaborative and outward-looking approach. However, the target role is 'Backend Engineer', which is a hands-on individual contributor role. The candidate's experience is predominantly in senior leadership and strategic roles, with limited recent direct engineering contributions evident in the resume. This creates a potential mismatch for a pure backend engineering role, suggesting a stronger fit for an engineering leadership or architect position.
Soft Skills & Operational Fit
The candidate's extensive leadership roles (Director, Head of Innovation, CTO/COO) suggest strong strategic thinking, team leadership, and operational management skills. Experience with M&A and raising investment rounds indicates business acumen and resilience. The descriptions highlight a proactive approach to innovation and a capacity to drive growth, which are valuable for operational fit.