Max Chrétien

Greenly provides the first end-to-end carbon accounting and management platform, enabling companies to measure, reduce, and manage their greenhouse gas (GHG) emissions while defining their path toward Net Zero. Led a squad of four engineers, owning the technical roadmap and delivering scalable, reliable solutions. Platform & Technical Improvements • Contributed to the migration from no-code solutions to a scalable Next.js architecture, reducing critical page load times by 5x. • Built a single source of truth for large-scale datasets by automating workflows, validation, API synchronization, and AI-assisted data enrichment. • Implemented monitoring and quality assurance processes that reduced the time spent fixing bugs during sprints from approximately x3. Team & Leadership • Improved team organization by introducing new Agile ceremonies, redesigning sprint planning, and fostering a strong culture of ownership. • Revamped technical documentation and strengthened cross-functional collaboration between engineering squads. • Partnered closely with Product, Design, and Customer Success teams to prioritize high-impact initiatives and align technical constraints with user needs.

The platform enables teams to train through realistic AI voice roleplays, helping employees practice real-world scenarios across sales, medical, and customer service environments. • Delivered impactful platform features from concept to production, improving product capabilities and user experience. • Designed and integrated AI-powered features through external APIs and providers, including OpenAI integrations. • Improved system reliability by introducing monitoring, error tracking, and processes to reduce critical issues and operational overhead. • Led a technical audit to identify key areas of technical debt and define a pragmatic improvement roadmap aligned with product delivery goals.

Clear Fashion guides consumers towards the most respectful clothing for people and the environment. Achievements: 
 • Mobile application created from scratch by being solo in tech for 1 year. • MVP available in 4 months • After 3 years: AppStore & PlayStore > 4.5 ⭐ • Widget creation with high availability: - median display access time of 150ms • Implementation of CD/CI on all services • Modern dev practice: TDD, pair-programming • RubyOnRails code coverage of more than 80% • unit and e2e tests for more than 80% of the web application With the team: • Organizes tech and security training for new team members • Manages recruitment and evolution of new tech members • Follows the precepts of the agile manifesto Technical Stack: • Mobile application in React Native • Web application in Next.js with SEO in mind • Server-side in Ruby on Rails • Heroku and Vercel for hosting • Firebase for user data

Shift Technology: Automate and Optimize Insurance Decision Making with Artificial Intelligence. I was part of a squad of about ten people who were in charge of developing and optimizing a SaaS of claims reporting for insurance companies. Technical stack: C# and React.js

Talentoday is a SaaS platform combining psychometric to machine learning in order to help HR decisions. Daily work: • Creation of new ready-to-ship features, entirely programmed from Back-end (RubyOnRails) to Front-end (AngularJS). • Refactor legacy code into testable and readable units. • Integrate Pixel-Perfect mock-ups • Improve overall performance of the application (e.g. fixing many “N+1 Query problem”) Data-science tasks: • Creation of unit tests for the Data-science Python part, from 0% to 60%. • Integration of mocks, monitoring tools and permanent logs. • Creation of monitoring applications live for the production and reduce the cost x3 on Heroku without performance loss. Team tasks: • Participates regularly in the production release on AWS. • Involved into the preparation of the weekly sprints. • Take active part in recruiting new collaborators by conducting interviews

Cardiologs is a SaaS platform for electrocardiogram analysis powered by artificial intelligence. • Integration of new Python modules with 100% unit test coverage and PEP8 compliance. • Creation of new internal Ruby on Rails API routes, fully documented and mocked. • Assistance in the design of deep learning algorithms in TensorFlow using IPython notebooks. • Migration of the software from Python 2.7 to multi-compatibility between Python 2.7 and Python 3.4. • Creation of new Docker images for the development environment. • Reverse engineering of files in unknown formats in order to build the appropriate parsers.