• Led technical strategic planning, including roadmap development and end-to-end sprint management.
  • Led the development and design of end-to-end, high quality software, complex technical prototypes and delivered the MVP for Cybrik AI, a cloud-based (Azure) enterprise platform with a React.js front end, a Python back end and data ingestion using Apache Airflow.
  • Designed and implemented the document search functionalities using Machine Learning and Natural Language Processing (NLP) techniques reducing the time for our customers to find the relevant information.
  • Scaled-up the company and hired additional technical resources to advance the platform after successful onboarding of clients onto Cybrik AI with the increase of the company valuation to US$ 5 million.
  • Represented Cybrik AI, with CEO and COO, during its selection as a portfolio company of Techstars (the second largest pre-seed fund); demonstrated leadership, ownership, technical expertise and entrepreneurial skills, and strengthened pitching and business case presentation abilities, in addition to overall investor relations and senior stakeholder management.
  • Led the recruitment and development of a team of 3 (a front-end developer, a back-end developer and a data scientist); defined requirements, deliverables, managed timelines and performance.
  • Created Kubernetes infrastructure in Azure and built pipelines in Github to support Continuous Integration and Continuous Delivery; Excellent knowledge and experience of various programming languages and techniques, including: FAST API for creating RESTful APIs with OpenAPI specifications and swagger documentation; Docker and Docker-compose; Javascript and Typescript (React); PostgreSQL, MongoDB; Elasticsearch; Azure and AWS; Kubernetes and Helm; Python libraries for machine learning such as scikit-learn and TensorFlow.