Credit card authorizations, fraud prevention, and disputes within the "BILL Spend & Expense" (Formerly Divvy) product written in Elixir.

Revea is a skincare company using diagnostics, personal analysis, and machine learning to deliver skincare designed for each individual’s biology. As a key member of a distributed team, my role encompassed various responsibilities, including software development, team management, developer recruitment and assessment, architectural planning, infrastructure setup, and codebase delivery.

Technical Achievements:

· Developed a pipeline for seamless integration of skin measurements from devices into the Google Cloud Platform (GCP).

· Implemented a reliable communication channel between the Web application and GCP using PubSub and Broadway data processing.

· Designed and developed client-facing interfaces using Elixir/Phoenix, GraphQL and Channels.

· Established a CI/CD using GitHub Actions for automated code deployment.

· Improved ML team infrastructure by setting up Terraform (IaC, infrastructure as code): Big Query, Cloud Functions, Cloud Runs, Cloud Tasks, Build Triggers, PubSub, Storage Buckets.

· Integrated system with 3rd-party services: Shopify for e-commerce, Postman for transactional emails, Stripe for payment processing, Klaviyo for marketing automation, Segment for customer data infrastructure, and others.

· Built a distributed system with multiple actors.

· Orchestrated a multi-environment setup, creating isolated staging and production environments.

Management Achievements:

· Motivated and led a diverse team: front-end and back-end developers, QA, and UI/UX talents.

· Optimized team productivity by using Agile practices: Scrum and Kanban.

· Improved long-term planning and predictability of release dates by utilizing Gantt charts and Agile Management boards.

· Defined and implemented effective team routines: sprint planning, grooming sessions, responsibility segregation, short and long-term planning.

· Ensured effective communication and collaboration among team members by describing and scoping tasks, and decomposition user stories into actionable items.

Chattermill unifies customer feedback, customer support, and product feedback into a single platform and uses deep learning artificial intelligence (AI) to analyze customer data at scale and provide actionable insights. The world’s leading brands like Amazon, Uber, Virgin Mobile, Zendesk, Tesco, JustEat, and H&M use Chattermill to transform their customer experiences and drive growth for their businesses.

· Developed the backend components of the “Workflow engine” using Elixir/Phoenix, PostgreSQL, and Elasticsearch, which encompassed multiphase data flows thru Triggers, Filters, and Actions.

· Designed an OTP (Open Telecom Platform) architecture layout and established efficient interactions with the rest of the system through APIs, WebSockets, and Redis PubSub.

· Actively contributed to the ongoing improvement and enhancement of the Chattermill platform, fostering a collaborative and innovative environment focused on delivering high-quality software solutions.

As a side project, I independently designed and developed Eventsme, a ticketing platform that simplifies ticket distribution for event organizers.

· Designed core infrastructure and codebase: Elixir/Phoenix, Angular, GraphQL.

· Setup CI/CD with Circle CI.

· Designed UI/UX in Figma using component and design system: Web and Native apps.

· Staffed and led a team of 3 developers, QA, and a lawyer.

· Designed thermal printer pool using Raspberry PI + Phoenix Channels for instant label printing at the entrance.

· Incorporated QR code scanners, allowing for quick and accurate ticket validation and check-ins.

Invocable is the collaborative platform for building chat and voice assistants (Voice User Interface). Quote from the website: “We rebuilt the voice design process from the ground up to help you create the future of interfaces. Craft your prototypes, instantly test on Alexa and share with your team.”

· Built a back-end for a powerful online editor that generated Alexa executable code, revolutionizing the voice design process.

· Led the backend development efforts, utilizing technologies such as Elixir, Phoenix, Ruby on Rails, PostgreSQL and Aurora Amazon RDS.

· Established the architectural setup, ensuring scalability, performance, and reliability of the platform allowing it to host approximately 8% of all Alexa skills.