We are looking for a passionate and technically skilled AI System Engineer with 1–3 years of experience to join our growing technology team. The ideal candidate will work on designing, developing, and maintaining AI-driven systems and scalable software solutions for real-world business applications. This role provides the opportunity to work with modern artificial intelligence technologies, cloud infrastructure, backend systems, and machine learning workflows in a collaborative and innovation-driven environment.
The candidate will contribute to the development of intelligent applications, automation systems, cloud-based AI services, and scalable architectures that support business growth and operational efficiency. You will work closely with developers, engineers, analysts, and product teams to deliver high-performance AI-enabled solutions while ensuring system reliability, scalability, and maintainability.
This position is ideal for professionals who are passionate about artificial intelligence, cloud computing, backend development, and emerging technologies. The role requires strong problem-solving abilities, analytical thinking, and a willingness to continuously learn and adapt to new tools, frameworks, and technologies.
Key Responsibilities
- Design, develop, and optimize AI and machine learning models for various business applications
- Build and maintain scalable backend systems and AI-driven applications
- Support the integration of AI solutions into existing software platforms and enterprise systems
- Develop and manage data pipelines, APIs, and automation workflows for AI processing
- Collaborate with cross-functional teams including developers, engineers, and product teams to deliver AI-enabled solutions
- Research and implement modern AI technologies, frameworks, and machine learning techniques
- Participate in software development lifecycle activities including planning, coding, testing, deployment, and maintenance
- Write clean, maintainable, and reusable code following software engineering best practices
- Improve application performance, scalability, and system reliability
- Work with cloud platforms such as AWS or Google Cloud Platform (GCP) for AI deployment and infrastructure management
- Troubleshoot technical issues, debug applications, and provide production support when required
- Assist in optimizing AI workflows, backend services, and cloud-based applications
- Contribute to system architecture discussions and technical decision-making processes
- Monitor and maintain AI applications and backend services for smooth operations
- Document technical workflows, development processes, and implementation details
- Stay updated with the latest trends and advancements in AI, machine learning, cloud computing, and software engineering
Required Skills
- Strong understanding of artificial intelligence, machine learning, and deep learning concepts
- Knowledge of machine learning algorithms, neural networks, and AI model development
- Proficiency in programming languages such as Python, Java, C++, or C#
- Experience with backend development and API integration concepts
- Familiarity with cloud platforms including AWS or Google Cloud Platform (GCP)
- Understanding of scalable system architecture, distributed systems, and cloud-native applications
- Knowledge of databases, data pipelines, and data processing workflows
- Strong analytical thinking and problem-solving abilities
- Good understanding of software development principles and coding standards
- Experience with debugging, troubleshooting, and performance optimization
- Ability to work independently as well as collaboratively in a team environment
- Good verbal and written communication skills
- Strong attention to detail and ability to manage multiple tasks effectively
- Passion for learning new technologies and adapting to modern development practices
Preferred Skills
- Experience with ASP.NET, .NET Framework, WCF, or WPF technologies
- Familiarity with machine learning frameworks and AI tools such as TensorFlow, PyTorch, or Scikit-learn
- Exposure to AI model deployment and MLOps workflows
- Knowledge of cloud-native application development and microservices architecture
- Understanding of DevOps concepts, CI/CD pipelines, and automation tools
- Familiarity with Docker, Kubernetes, or containerized environments
- Exposure to scalable distributed systems and enterprise application architecture
- Knowledge of code quality tools, testing frameworks, and debugging techniques
- Interest in AI research, intelligent automation, and data-driven technologies
- Understanding of version control systems such as Git
Education
B.Tech / BCA / MCA / B.Sc. in Computer Science, Information Technology, Artificial Intelligence, Data Science, Engineering, or Equivalent Qualification
