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Senior Director of Engineering | AI Startup (Stealth) | PhD
I help CEOs and C-level leaders cut through the AI and GenAI hype and get real systems into production with measurable impact on revenue, productivity, and customer experience. I bring 15+ years hands-on and leadership working with machine learning, data products, and automation in large organizations. I’m usually brought in when a company has already "tested AI" but is stuck in endless PoCs, isolated IT projects, or initiatives that don't scale commercially. The patterns repeat: difficulty connecting AI to business strategy, lack of architecture and governance, and overloaded teams trying to do everything without clear priorities. My work combines strategy, product, and engineering: designing use cases that make economic sense, building the technical foundations (data, models, platforms, agents), and organizing teams to scale what works. I've led initiatives that delivered double-digit productivity gains, 4× conversion improvements in digital journeys, and new AI commerce capabilities at scale. I like to work close to both business decision-makers and technical teams: translating constraints, aligning incentives, and simplifying complexity without losing technical depth. If you lead an organization that wants to use AI seriously - to increase commercial performance, operational efficiency, or create new digital products - and you want pragmatic, no-hype paths forward, feel free to reach out here.
Universidade Estadual de Campinas
PhD, Electrical and Computer Engineering
January 1, 2011 – January 1, 2014
Universidade Federal de Pernambuco
Master of Science - MS, Computer Science
January 1, 2009 – January 1, 2011
Universidade Católica de Pernambuco
Bachelor, Computer Science
January 1, 2004 – January 1, 2008
Universidade Federal de Pernambuco
Bachelor's degree (partially completed), Communication, Marketing, and Media Studies
January 1, 2001 – January 1, 2003
Universidade Católica de Pernambuco
Bachelor's degree (partially completed), Law
January 1, 2001 – January 1, 2001
Stealth AI Startup
Senior Director of Engineering
February 1, 2026 – Present
Bain & Company
Expert Associate Partner, AI & Data Science
January 1, 2024 – February 1, 2026
Hybrid
Bain & Company
Director of Data Science, South America
March 1, 2022 – December 1, 2023
Hybrid
Zenklub
Head of Data
September 1, 2021 – February 1, 2022
Remoto
Awari
Mentor de Data Science
August 1, 2021 – February 1, 2022
São Paulo, Brazil
Coteminas
Head of Product, Persono
September 1, 2020 – September 1, 2021
Coteminas
Director, Data Science
November 1, 2019 – September 1, 2021
QuintoAndar
Data Science Manager
June 1, 2019 – November 1, 2019
São Paulo Area, Brazil
Ericsson
Research Project Manager
January 1, 2019 – May 1, 2019
Ericsson
Experienced IoT Technologies Researcher
May 1, 2018 – June 1, 2019
Samsung Electronics
Lead Artificial Intelligence Researcher
June 1, 2017 – May 1, 2018
Campinas, São Paulo, Brazil
ExO Works
ExO Consultant
February 1, 2016 – February 1, 2022
Ericsson Research
Machine Intelligence Researcher
June 1, 2015 – June 1, 2017
Indaiatuba, São Paulo, Brazil
School of Electrical and Computer Engineering - Universidade Estadual de Campinas
Postdoctoral Researcher
September 1, 2014 – June 1, 2015
Campinas Area, Brazil
University of Minnesota
Visiting Researcher
June 1, 2013 – August 1, 2013
Greater Minneapolis-St. Paul Area
IEEE
Scientific Reviewer and Technical Committee Member
January 1, 2012 – November 1, 2016
IEEE
IEEE Computational Intelligence Society Leadership Roles
February 1, 2011 – February 1, 2017
Singularity University
Global Solutions Program participant
June 1, 2010 – August 1, 2010
NASA Ames Research Park - Mountain View, California
Unibratec
Lecturer on Software Engineering
January 1, 2007 – August 1, 2007
Recife Area, Brazil
Especializa Treinamentos
Developer and Instructor on Programming Languages
January 1, 2006 – July 1, 2007
Recife Area, Brazil
Nativ
Web Developer Internship
January 1, 2005 – July 1, 2005
Recife Area, Brazil
SciTorrent
June 1, 2016 – Present
***CURRENTLY SEEKING VOLUNTARIES*** (Contact me via LinkedIn message if touched by the cause!) A free, open-source disruptive alternative for collaborative open science. - Vision: a World where the scientific production is free from centralizing models of reputation and impact. - Mission: to provide an open-source tool for the scientific community to simplify the execution of distributed computational experiments. - Goals: 1. To provide an open-source tool for the scientific community for search and access to research data collection. 2. To provide a better access for information among connected researchers (metadata about research projects and publications). - Features: an automated mechanism for measuring research projects reputation and impact. A smart index of papers, the craft of a distributed citations, concepts and collaboration graph. Integrated recommendation system. Integrated crowd-funding. - Technology: Peer-to-peer. Multi-platform (web and desktop).
Multi-Objective Autonomous Robotics for Management and Operations of Complex Logistics Systems
March 1, 2016 – Present
The project aims to explore the interplay between multi-objective machine intelligence approaches and autonomous robotics for managing complex logistics operations by modeling and simulating intelligent, automated vendor-managed inventory control strategies allowing for efficient real-time integration of warehouse operations with multi-retailer inventory replenishment tasks.
A methodology for multicriteria stochastic anticipatory optimization
October 1, 2012 – August 1, 2014
This research project aims to design new sequential decision-making systems, operating in uncertain environments under multiple conflicting optimization criteria. It is assumed that the dynamics of the system under control (in discrete time and over a finite horizon) is linear and that the exogenous uncertainty can be estimated by parametric probabilistic models. In this context, four challenges are covered, namely: (1) the learning of probabilistic models capable of measuring the influence of the decisions implemented on the future operating costs; (2) the determination of stochastic policies capable of modeling the decision maker; (3) the determination of the risks of violating the problem constraints; and (4) the incorporation of partial preferences in the decision making process. It is emphasized that research activity on the treatment of multiple conflicting criteria and the incorporation of chance-constraints is scarce, considering the literature of anticipatory meta-heuristics and approximate dynamic programming. As its main contribution, this project proposes a new methodology as well as tools to allow for the effective synthesis of anticipatory multicriteria decision-making systems. The methodology will be investigated over a broad class of problems, ranging from vendor managed inventory-routing problems; optimization of financial and product portfolios, and the control of public transport systems operating in real time.
Academy Accreditation - Generative AI Fundamentals
Databricks
June 24, 2026 – Present
Global Solutions Program
Singularity University
June 24, 2026 – Present
Building a Data Science Team
Coursera
June 24, 2026 – Present
Building Deep Learning Applications with Keras 2.0
June 24, 2026 – Present
Kafka Essential Training
June 24, 2026 – Present
Edge Analytics: IoT and Data Science
June 24, 2026 – Present
Certificate of Proficiency in English
Universitiy of Michigan
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's extensive experience across various industries (consulting, health tech, retail, telecom) and their involvement in both corporate and startup environments suggest adaptability. Their academic background and continuous engagement in research and mentorship roles (Awari, IEEE, Singularity University) indicate a strong drive for learning and contributing to the broader technical community. The projects listed, particularly 'SciTorrent', demonstrate an interest in open science and disruptive innovation, which aligns with a culture that values forward-thinking and impact. However, the target role of 'Data Analyst' seems significantly junior to their demonstrated experience and leadership capabilities, which could lead to a mismatch in expectations or underutilization of their senior expertise. This discrepancy lowers the cultural fit score, as the candidate appears overqualified for the stated target role.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership, mentorship, and strategic planning skills through their various Head of Data and Director roles. Their experience in establishing data product tribes, defining career paths, and upskilling teams indicates a focus on team development and operational excellence. Collaboration with C-suite and external partners (OEMs, academic institutions) highlights strong communication and stakeholder management. The emphasis on democratizing access to data and fostering communities suggests a collaborative and purpose-driven work attitude. However, without psychometric test results, a full assessment of stress handling and direct team collaboration style is limited.