Our partner is building an AI-powered marketing platform that serves as the operational, data-driven layer between raw marketing data and live advertising campaigns. The platform automates complex marketing workflows and enables data-driven campaign execution at scale. As a Full-Stack Engineer, you´ll help shape the customer-facing experience by building intuitive user interfaces and scalable backend services that power a modern AI-driven platform.
Responsibilities
- Build, maintain, and enhance responsive, data-rich user interfaces using React and TypeScript.
- Design, develop, and integrate scalable RESTful and/or GraphQL APIs.
- Connect frontend applications with cloud-based backend services, AI models, and data pipelines.
- Collaborate closely with Data Engineering, DevOps, and Product teams to deliver seamless end-to-end user experiences.
- Translate complex analytical data into intuitive, actionable user experiences.
- Write clean, maintainable, and well-tested code with a strong focus on performance and quality.
- Contribute to architectural decisions and continuously improve both the product and developer experience.
Required Skills & Qualifications
- 2–5 years of professional software engineering experience.
- Strong hands-on experience with React and TypeScript.
- Solid understanding of modern frontend architecture, state management, and asynchronous programming.
- Experience designing and integrating RESTful and/or GraphQL APIs.
- Experience connecting frontend applications to cloud-based backend services and data platforms (AWS experience is a plus).
- Ability to read and understand existing Swift code. Writing production Swift is not required.
- Strong UI/UX mindset with experience building clean, responsive, and intuitive interfaces.
- Excellent communication and collaboration skills in cross-functional engineering teams.
Benefits
- Experience with server-side TypeScript (Node.js, NestJS, or similar).
- Familiarity with serverless architectures and modern cloud environments.
- Experience with AWS services.
- Exposure to data platforms such as Databricks.
- Previous experience working on AI-powered or data-intensive products.