Cloud Data and Application Engineer

TContact: careers.krishu@outlook.com; nalintowai@krishuai.com; sanjaysharma@krishuai.com

Job Title: Cloud Data and Application Engineer (3-4 years’ experience)

Role Description:

This role focuses on developing and maintaining the backend systems, APIs, and cloud infrastructure that power our AI-driven solution, strongly emphasizing seamless integration with AI models and related services. This role requires a deep understanding of cloud-native principles and practices, enabling the development and deployment of scalable, resilient, and cost-effective applications in cloud environments. You will work across the full stack, from data ingestion and processing to application development and deployment, ensuring seamless integration and optimal performance.

Responsibilities:
• Cloud Infrastructure for AI: Design, implement, and manage the cloud infrastructure required to support AI workloads, including model hosting, data storage, and related services. This includes setting up compute instances, storage, networking, databases, and other cloud resources. This may involve working with containerization technologies (Docker, Kubernetes) and cloud-specific AI/ML platforms.
• Cloud-Native Architecture: Design and implement applications following cloud-native architectural patterns, such as microservices, containerization (Docker, Kubernetes), and serverless computing.
• Data Pipeline Development & Management: Design, develop, and maintain efficient ETL/ELT pipelines for data ingestion, transformation, and loading. Implement and manage data streaming solutions. Optimize data pipelines for performance, scalability, and cost-effectiveness. Monitor and troubleshoot data pipeline issues.
• Backend Integration with AI models: Design, develop, and maintain robust and scalable integrations between AI models (NLP, speech, etc.) and the application's backend systems. This includes handling data flow, request/response formats, and performance optimization for AI inference.
• API Development for AI Services: Create and maintain APIs that expose AI functionalities to other parts of the application or external services. This includes designing API specifications, implementing authentication and authorization, and ensuring API reliability and security.
• CI/CD Pipeline Automation: Implement and maintain CI/CD pipelines to automate the building, testing, and deployment of applications to the cloud.
• Deployment and Management of AI Models: Automate the deployment and management of AI models in production, including versioning, scaling, and monitoring. Work with MLOps tools and practices.
• Security Best Practices: Implement security best practices throughout the application and infrastructure, including authentication, authorization, and data encryption.

Qualifications:

· Bachelor’s degree in computer science, Software Engineering, or a related field.

· 3-4 Years experience spread across both software engineering and data engineering.

· Strong proficiency in SQL and at least one programming language (Python, Java, Scala).

· Experience with cloud platforms (AWS, Azure, or GCP) and related data services.

· Experience with API development and web frameworks.

· Understanding of database design and optimization.

· Strong problem-solving and analytical skills.

· Excellent communication and collaboration skills.
• · Experience with containerization and orchestration technologies (Docker, Kubernetes) is a plus.