Full-stack GenAI Developer

Summary

Join OES as a Fullstack GenAI Developer to design, develop, and integrate AI-driven features into web applications. You will work across the full stack, from data pipelines and backend services to front-end interfaces, leveraging expertise in software engineering and machine learning. This role offers the opportunity to contribute to meaningful projects and grow your skills within a supportive team. The position is permanent, hybrid (Mondays and Thursdays in the office, other days remote), and located in Cape Town. Success is measured by the timely and budget-conscious delivery of AI solutions, efficiency gains, client satisfaction, revenue generation, effective collaboration, compliance, and innovative architecture. The company values collaboration, connection, and a shared goal.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience
• Solid experience with both frontend (e.g., React, Angular, Vue) and backend (e.g., Node.js, Python, Java) technologies
• Proficiency in at least one major machine learning framework
• Experience with cloud platforms (AWS, Azure, GCP) and DevOps tools (Docker, Kubernetes, CI/CD pipelines)
• Strong problem-solving skills and the ability to communicate complex technical concepts to diverse audiences
• Experience working in agile, cross-functional teams

Responsibilities

• Develop, deploy, and maintain full-stack applications with integrated AI/ML capabilities
• Collaborate with each department (Learning, Production, Sales, and Delivery) to define, build, and iterate on AI-powered features
• Build robust data pipelines for collecting, preprocessing, and transforming data for machine learning workflows
• Train, evaluate, and deploy machine learning models using frameworks
• Integrate AI models into production web applications, ensuring scalability, reliability, and performance
• Design and implement RESTful APIs and microservices architectures
• Ensure best practices in code quality, testing, and documentation
• Participate in code reviews and contribute to a culture of continuous improvement

Preferred Qualifications

• Familiarity with MLOps tools and practices
• A portfolio or examples of previous AI/ML projects

Benefits

• Employee Assistance Program (EAP)
• Medical allowance
• Commute allowance
• Flexible work for genuine career-life fit
• A healthy and supportive company culture
• Generous annual leave
• Paid maternity and paternity benefits
• Study leave
• Professional development and mentoring
• Construct Culture Club events
• Company funded lunch and drinks every 6 weeks