Position Overview:
The AI Full Stack Developer will be responsible for building and maintaining AI-driven applications, working across the entire technology stack. You will be involved in everything from developing front-end user interfaces to designing and deploying back-end AI systems and services. This role requires strong programming skills, an understanding of AI/ML models, and the ability to build end-to-end solutions that are highly responsive, scalable, and efficient.

Key Responsibilities:

AI Application Development:

·         Design and implement AI-driven applications, integrating machine learning models and AI algorithms into full-stack web applications.

·         Develop user-facing features (front-end) using modern web technologies (e.g., React, Vue.js, Angular).

·         Implement back-end services (using Node.js, Python, Java, etc.) that integrate with machine learning models, APIs, and databases.

·         Build and deploy AI/ML models, and ensure their integration into production environments with optimal performance.

Machine Learning Model Integration:

·         Collaborate with data scientists and AI researchers to integrate pre-trained AI models into production-ready applications.

·         Ensure the seamless deployment and scaling of AI models in cloud environments (AWS, GCP, Azure).

·         Monitor and improve AI model performance, ensuring accurate and reliable outputs.

API & Database Management:

·         Develop and maintain RESTful APIs to facilitate communication between the AI models, front-end interfaces, and databases.

·         Manage and design relational and non-relational databases (e.g., SQL, MongoDB) to store, query, and manage data effectively.

·         Implement security measures to protect AI models and sensitive data.

End-to-End Development & Deployment:

·         Implement DevOps practices for continuous integration/continuous deployment (CI/CD) pipelines to automate testing and deployment of AI-powered applications.

·         Ensure applications are scalable, secure, and optimized for performance across all layers of the tech stack.

·         Conduct regular performance tuning and debugging to improve application reliability and efficiency.

Collaboration & Communication:

·         Work closely with other developers, data scientists, AI researchers, and product managers to define and understand application requirements.

·         Participate in agile development cycles, including sprint planning, daily stand-ups, and retrospectives.

·         Provide technical leadership, guidance, and mentorship to junior developers as needed.

Testing & Quality Assurance:

·         Develop unit, integration, and end-to-end tests for both front-end and back-end code, ensuring the overall quality of the application.

·         Write automated tests to validate AI models' outputs, ensuring accuracy and reducing the risk of errors in production environments.

Qualifications:

Education & Experience:

·         Bachelor’s in related field or equivalent.

·         10 Years IT experience

·         Proven experience working with AI/ML technologies and frameworks (e.g., TensorFlow, PyTorch, Keras, Scikit-learn).

·         Strong experience in both front-end (React, Angular, Vue.js) and back-end (Node.js, Python, Java, etc.) development.

·         Experience with cloud platforms (AWS, Google Cloud, Azure) for deploying AI applications.

Skills & Competencies:

·         Strong proficiency in JavaScript, HTML, CSS, and modern front-end frameworks (React, Vue.js, Angular).

·         Experience with server-side languages such as Python, Node.js, or Java for back-end development.

·         Solid understanding of AI and ML principles, algorithms, and model integration into production environments.

·         Familiarity with databases (SQL, NoSQL) and API development (RESTful APIs).

·         Knowledge of Docker, Kubernetes, and CI/CD pipelines for deploying scalable applications.

·         Strong understanding of software development best practices, including version control (Git), code review, and testing.

Soft Skills:

·         Excellent problem-solving skills, with the ability to troubleshoot and optimize AI systems.

·         Strong communication and collaboration skills, with the ability to work effectively in cross-functional teams.

·         Self-motivated, detail-oriented, and capable of managing multiple priorities in a fast-paced environment.

·         A passion for AI/ML technologies and staying up-to-date with the latest trends and innovations.