We are seeking a results-driven engineer to design, develop, and maintain end-to-end web solutions that support AI and automation initiatives. This role requires expertise in modern front-end and back-end technologies, API integration, and cloud-based infrastructure.
Responsibilities:
- Develop and maintain scalable front-end applications to support AI and automation projects.
- Collaborate with data scientists, AI developers, and other engineers to integrate AI models and automation workflows into production systems.
- Design and implement user-friendly interfaces using modern front-end technologies and frameworks.
- Ensure the performance, quality, and responsiveness of front-end applications.
- Develop and maintain back-end services and APIs to facilitate seamless data exchange between different components of the AI and automation ecosystem.
- Troubleshoot and debug issues across the stack to ensure smooth operation of AI and automation solutions.
- Stay updated with the latest industry trends and technologies to continuously improve our systems.
Must-Have Qualifications:
- Bachelor's degree in computer science, Engineering, or a related field.
- Proven experience as a Front-End, Back-End, or Full-Stack Engineer
- Proficiency in front-end technologies such as HTML, CSS, JavaScript.
- Strong knowledge of back-end technologies such as Python.
- Experience with Django and Flask for web application development.
- Experience with RESTful API design and implementation
- Experience with database technologies like SQL, NoSQL, and ORM frameworks.
- Understanding of version control systems, preferably Git.
- Understanding of CI/CD pipelines and DevOps practices
- Knowledge of cybersecurity best practices.
- Ability to quickly learn and apply enterprise AI tools and technologies to support technical workflows and business objectives.
Nice-to-Have Qualifications:
- Frameworks like React or Angular, Node.js experience is a plus.
- Familiarity with containerization and orchestration tools like Docker and Kubernetes.
- Experience with AI and machine learning frameworks (e.g., TensorFlow, PyTorch).
- Knowledge of cloud platforms such as Azure, AWS, or Google Cloud
- Experience with data visualization tools and libraries.
