Senior Full-Stack Engineer

Shape the Future of AI & Data with Us

At Datatonic, we are Google Cloud's premier partner in AI, driving transformation for world‑class businesses. We push the boundaries of technology with expertise in machine learning, data engineering, and analytics on Google Cloud Platform. By partnering with us, clients future‑prove their operations, unlock actionable insights, and stay ahead of the curve in a rapidly evolving world.

As a Senior Full‑Stack Engineer, AI Applications
, you'll be instrumental in building innovative, end‑to‑end AI‑powered solutions. You'll take pride in crafting beautiful, production‑ready code across both front‑end and back‑end systems, ensuring seamless user experiences and robust functionality. You'll be an advocate for high‑quality engineering and best practices in all stages of software development, from rapid prototypes to scalable production deployments.

While this is a hands‑on technical role, we're particularly interested in candidates with a desire to lead projects and actively engage in client discussions. Your responsibilities will involve building trusted relationships with prospects, finding creative ways to integrate machine learning into user‑facing applications, scoping projects, and overseeing the delivery of these engagements.

To be successful, you will need strong full‑stack development fundamentals combined with an understanding of Generative AI concepts. You'll know the right tools and approaches for building responsive UIs, robust APIs, and well‑tested scalable applications. Furthermore, you'll need excellent communication and consulting skills, with the desire to meet real business needs and deliver innovative solutions using AI & Cloud.

• Translating Requirements: Interpret vague business requirements and design, develop, and deploy full‑stack applications that leverage AI to solve real‑world problems.
• AI Application Development: Build and maintain scalable, secure web applications, including user interfaces (UI) and application programming interfaces (API), that integrate and expose AI capabilities.
• Performance Optimisation: Optimise full‑stack solutions for performance, scalability, and responsiveness across both front‑end and back‑end systems.
• AI Application Lifecycle: Automate the deployment, monitoring, and maintenance of AI‑powered applications, focusing on reliability, testing, and continuous delivery.
• AI Application Solution Architecture: Create comprehensive architecture designs for AI applications, utilising Google Cloud tools and services for both application and AI components.
• Engineering Software for Production: Build and deploy production‑grade, secure, and maintainable software for AI and data‑driven solutions.

• Experience: 3+ years as a Full‑Stack Engineer, including some experience in AI application development.
• Programming
  
  Skills:
  
  Proficiency in Python (for backend services, APIs, and ML integration) and JavaScript/Type Script (for front‑end development). Capable of delivering production‑ready code in well‑tested CI/CD pipelines.
• Front‑End Expertise: Strong hands‑on experience with modern front‑end frameworks (e.g., React, Angular, Vue.js) and building responsive user interfaces.
• Back‑End Expertise: Experience designing and implementing RESTful APIs, microservices, and integrating with databases.
• Cloud Expertise: Familiarity with cloud platforms such as Google Cloud, AWS, or Azure, including deploying and managing applications.
• Software Engineering: Good knowledge of foundational software engineering practices, including design patterns, testing, and version control.
• Database Proficiency: Strong experience integrating applications with SQL and No
  
  SQL databases.
• Scalability: Experience scaling applications using cloud‑native services.
• Security & Authentication: Demonstrable understanding and practical experience with common web security vulnerabilities, secure coding practices, and various authentication and authorisation protocols.
• UI/UX Principles: Understanding of user interface (UI) and user experience (UX) design principles to create intuitive and engaging AI applications.
• Soft Skills: Strong communication and…