Job Summary :

We are seeking a highly skilled AI Engineer with 5-8 years of experience, possessing a strong foundation in backend development and cloud technologies, particularly within the Microsoft Azure ecosystem.

The ideal candidate has practical experience across diverse AI/ML domains, including NLP, Computer Vision, Video Processing, Text Extraction, Dubbing, and Translation.

This role is critical for designing, developing, and deploying scalable, production-ready, intelligent applications using modern cloud-native practices.

Key Responsibilities :

- Backend & Microservices Development: Design and develop advanced backend components, data systems, scalable data pipelines, and microservices that power AI-driven applications.

- Cloud-Native Infrastructure: Engineer and implement production-ready, cloud-native infrastructures (or on-premise), covering everything from optimized databases to serverless architectures.

- AI/ML Integration & Deployment: Integrate and deploy diverse AI models and services into the production environment. This includes specialized solutions for NLP, computer vision, and video processing.

- Azure AI Utilization: Expertly utilize Azure AI Services, Cognitive Services, and other cloud-native AI tools to accelerate the development and deployment of intelligent applications.

- Software Engineering Best Practices: Follow and enforce best practices in software engineering, including setting up robust CI/CD pipelines, comprehensive testing, and detailed documentation.

- Cross-Functional Collaboration: Collaborate effectively with data scientists, product managers, and other engineering teams to deliver highly scalable and maintainable AI solutions.

Qualifications :

- Experience: 5-8 years of professional experience in software engineering, with a focus on AI/ML applications.

- Backend Proficiency: Strong foundation and hands-on experience in backend development (e.g., Python, C#/.NET) and data systems architecture.

- Cloud Expertise: Strong experience with Microsoft Azure cloud technologies, including services for compute, storage, and networking.

- AI Domain Knowledge: Practical experience in one or more AI/ML domains: NLP, Computer Vision, Video Processing, Text Extraction, Dubbing, or Translation.

- Azure AI Services: Hands-on experience utilizing Azure AI Services and Cognitive Services.

- Process & Tools: Experience with modern software engineering practices: CI/CD, automated testing, and microservices architecture.

Preferred Skills:

- Experience with distributed computing frameworks (Spark), containerization (Docker/Kubernetes), and MLOps tools.