Application Engineer (Full Stack – AI Centric) – Indonesia

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Application Engineer (Full Stack - AI Centric) - Indonesia

  • Cloud Computing
  • Indonesia
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As a Full Stack Software Developer at PointStar, we seek a highly skilled and passionate Full Stack Developer with a proven track record of developing robust, scalable, and user-friendly products, specifically those leveraging Artificial Intelligence. As a key member of our growing engineering team, you will be pivotal in designing, developing, and deploying end-to-end AI-driven applications, from conceptualisation to production. This role requires a strong understanding of both front-end and back-end technologies, coupled with hands-on experience in integrating and building with AI tools and developing AI-based products.

Job Descriptions:

  1. Develop front-end and back-end: Write clean, efficient, and maintainable code for web applications, including UI/UX development and database management.
  2. Integrate and utilise various AI tools: libraries and APIs (e.g., OpenAI APIs, Google Cloud AI Platform).
  3. Develop and implement: AI models or integrate existing models into full-stack applications.
  4. Contribute to the entire lifecycle of AI-based products, from data ingestion and model training to deployment and monitoring.
  5. Deployment & Operations: Work with CI/CD pipelines, GitLab CI, GitHub Actions, for automated deployments. Understand and contribute to monitoring, logging, and performance optimisation of production systems, especially for AI workloads.
  6. Innovation & Research: Stay up-to-date with the latest trends and advancements in full-stack development, AI, and machine learning, and propose innovative solutions.
  7. API Design & Development: Design, build, and maintain robust RESTful APIs and/or GraphQL APIs for seamless communication between front-end and back-end systems, including those powering AI functionalities.
  8. Database Management: Work with databases like PostgreSQL, MongoDB, and MySQL to design schemas, optimise queries, and manage data effectively for both traditional application data and AI-related datasets.
  9. Collaborate with cross-functional teams: Work with designers, product managers, and other developers to deliver high-quality features and products.
  10. Ensure application scalability and performance: Write code optimised for speed, performance, and scalability.
  11. Testing and debugging: Write unit tests and conduct code reviews to ensure the highest code quality. Troubleshoot and debug issues.
  12. Project Management: Fulfil several project requests simultaneously while meeting tight deadlines and work well both independently and as part of a team
  13. Support: Provides technical support and troubleshoots application-related problems, performs software upgrades, keeps track of software licensing and makes the customisation and addition of new features to commercial software packages and internally developed applications according to end-user requests.
  14. Documentation: Writes technical documentation and uses best development practices regarding version control and testing.


Requirements:

  1. Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
  2. 2-4 years of experience in software development or a related field.
  3. Proven experience developing products that utilise AI tools and/or AI-based products. 
  4. Experience with real-time data processing or streaming technologies.
  5. Strong communication and interpersonal skills.
  6. Excellent problem-solving skills and the ability to work independently and as part of a team.
  7.  Experience integrating with or utilising cloud-based AI services (e.g., Google Cloud AI Platform, OpenAI APIs).
  8. Proficiency in front-end technologies such as HTML, CSS, JavaScript, and front-end frameworks (e.g., React.js).
  9. Strong back-end development skills using languages like Node.js (JavaScript)
  10. Experience with databases: SQL (PostgreSQL, MySQL) or NoSQL (MongoDB, Firebase).
  11. Familiarity with version control tools, especially Git.
  12. Experience with cloud platforms (e.g., Google Cloud) and DevOps tools (Docker, Kubernetes, CI/CD pipelines).
  13. Knowledge of web security principles (e.g., OAuth, JWT, data encryption).
  14. Strong problem-solving skills and ability to work independently or as part of a team.
  15. Experience with Agile methodologies (Scrum, Kanban) is a plus.

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