Jan 2025 – Present · 1 yr 3 mos · Singapore, Singapore · Remote

• Strategizing AI initiatives across industries to help clients maximize technological value and transform from AI-native to AI-first businesses.

Jun 2023 – Sep 2025 · 2 yrs 3 mos · Lisbon, Portugal · Remote

• Led a 11-core member, 50+ talent pool, AI engineering team, engaged in 200+ presales opportunities, and delivered $100K+ project wins while driving cross-functional initiatives in AI solutions for financial services clients.
• Business Development & Strategy
• Collaborated with senior leadership on proposal development and customer presentations while partnering with the Chief Marketing Officer to define AI Engineering Strategy for market positioning.
• Engineering Leadership & Technical Excellence
• Built and maintained technical infrastructure supporting AI solution delivery, including standardized tech stacks, productivity tools, and reusable architectural patterns focused on state-of-the-art AI solutions in the financial services domain. Conducted regular technical enablement sessions and code reviews to elevate team capabilities while developing internal AI automations for enhanced productivity.
• Hands-On Delivery
• Maintained direct client engagement through active participation in customer projects as Sr. AI Architect (0.5-0.625 FTE), ensuring continued technical expertise and gathering critical market insights while supporting company financial health.
• Team Development & Operations
• Managed end-to-end talent lifecycle for AI Architects and Engineers, including recruitment, interviewing, onboarding, performance reviews, and promotions. Optimized team utilization and project staffing while maintaining effective cost management of engineering toolkits and billable hours within target ranges.
• Key Impact Areas:
• 👉 Technical team enablement and capability building
• 👉 AI solution architecture and engineering best practices
• 👉 Financial services domain expertise and client delivery
• 👉 Talent management and operational efficiency

Nov 2022 – Present · 3 yrs 5 mos · Lisbon, Portugal

Jan 2022 – Present · 4 yrs 3 mos · Lisbon, Portugal · Remote

• Helping with AI enablement.

Jan 2022 – Mar 2023 · 1 yr 2 mos · Lisbon, Portugal · Hybrid

• Building the product from scratch, enabling AI's native capabilities for a sales assistant co-pilot.

Jan 2020 – Present · 6 yrs 3 mos · Portugal · Remote

• enabling humans with AI as an extension

Nov 2019 – Dec 2022 · 3 yrs 1 mo · San Francisco Bay Area · Remote

• At Apres, we are at the forefront of pioneering domain-specific Knowledge Graph development, tailored to empower enterprises across a myriad of use cases. Our sophisticated Knowledge Graph technology is designed to address critical business challenges, including fraud detection, faster decision making and recommendation engines.
• By leveraging our advanced Knowledge Graphs, businesses can significantly enhance their grasp on their data. Our technology enables the identification of intricate patterns and anomalies within vast datasets, uncovering various types of activities that traditional methods might miss.

Oct 2019 – Jan 2020 · 3 mos · Copenhagen Area, Capital Region, Denmark

Apr 2019 – Jun 2024 · 5 yrs 2 mos · Remote

Apr 2019 – Apr 2019 · 0 mo · Paris Area, France

• BioSMART 2019 International Conference on BioEngineering for smart technologies

Oct 2018 – Jan 2019 · 3 mos

• This Learning Path offers practical knowledge and techniques you need to create and contribute to machine learning, deep learning, and modern data analysis. You will be introduced to various machine learning and deep learning algorithms from scratch, and show you how to apply them to practical industry challenges using realistic and interesting examples. You will learn to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open-source Python libraries.
• Throughout the Learning Path, you’ll learn how to develop deep learning applications for machine learning systems. Discover how to attain deep learning programming on GPU in a distributed way.
• By the end of this Learning Path, you know the fundamentals of AI and have worked through a number of case studies that will help you apply your skills to real-world projects.

Apr 2018 – Oct 2018 · 6 mos

• This book is aimed at intermediate machine learning engineers, software engineers, technology architects and programmers who are interested in knowing more about deep learning, especially applied deep learning, TensorFlow, Google Cloud and Keras. Python Deep Learning Projects is focused at the core of the data science pipeline – model building, training, evaluation, and validation.
• We approach deep learning projects from a very practical point of view. In thinking about how to share what we know, our experiences, the strategies that we've learned, and the tactics we employed in our daily day to day life.
• Tools and frameworks like, Keras, TensorFlow, and Google Cloud are used to showcase the strengths of various approaches covering NLP, CV and ASR.
• Link to Packt Publishing: http://bit.ly/DeepLearningProjects
• Link to Amazon: https://www.amazon.com/Python-Deep-Learning-Projects-Architectures/dp/1788997093

Jan 2018 – Feb 2020 · 2 yrs 1 mo · Copenhagen Area, Denmark

• Jatana is a deep learning based Saas solution that integrates directly with your help desk software of choice to automate processes related to customer service.
• My major areas of focus:
• Leading the AI team and taking care of the AI product end-to-end.
• Understood the business problem and developed a deep learning framework for classification and data extraction use-cases.
• Created a fully automated ML framework using Docker and microservice setup to deploy in production using Tensorflow Serving.
• Developed a few proofs of concepts for various language modeling projects i.e. unsupervised data labeling tool, article summarization tools in 102 languages, etc.
• Creating and maintaining documents/code files i.e. data dictionary, source code, project plan to keep the project on track.

Oct 2017 – Dec 2019 · 2 yrs 2 mos · Copenhagen Area, Denmark

Sep 2016 – Oct 2017 · 1 yr 1 mo · Bangalore

• Building Cognitive solutions around chatbots, Q/A engines for mCaaS.
• Focusing on implementing NLU engines using Deep Learning algorithms (CNN and RNN).

Oct 2014 – Sep 2016 · 1 yr 11 mos · Bengaluru, India

• Being part of Accenture’s R&D group, I explore and implement machine learning algorithms for various use cases - NLP, Feature extraction, Classification, Predictive model, etc. My current areas of R&D focus include NLP parsing, speech to text conversion and Q/A service.
• Previously I have also explored biometric (fingerprint, iris, face, vein, voice) and biographic (textual and contextual) data and algorithms to deliver value through effective human identity recognition. I developed web/mobile applications for targeted R&D, prototyping, development of proofs of concept and solution delivery.

Apr 2012 – Jun 2014 · 2 yrs 2 mos · Meerut Area, India

• Worked on a Biometric system dealing with the FOOTPRINT details.
• Used Footprint traits for identification/verification and establishing correlation between height,weight and age of the user .