Collaborate with cross-functional teams to understand business needs and translate them into backend functionalities for GenAI and Agentic AI projects.
Design, develop, and maintain scalable backend solutions, including event-driven architectures and integration with external systems/APIs.
Manage data storage solutions using relational (PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB) databases to support AI applications in production.
Utilize containerization (Kubernetes) and implement DevOps practices, including CI/CD pipelines (Azure DevOps, GitHub Actions), for effective deployment and scalability.
Build and integrate APIs using Python frameworks (Flask, FastAPI) and collaborate with data scientists, engineers, and DevOps teams for seamless AI model deployment.
Preferred candidate profile
At least a Bachelor's & Master's degree
At least 4 years of experience