Key Responsibilities:

- Design, develop, and maintain enterprise integration services and platform components.

- Build scalable REST APIs and asynchronous services for AI/GenAI platform integrations.

- Implement authentication, authorization, and platform-level access controls.

- Integrate and manage relational and NoSQL databases as required.

- Containerize applications and services using Docker.

- Integrate applications with AWS, Azure, or other cloud services.

- Support integration of AI/GenAI services with enterprise applications and platforms.

- Ensure APIs and platform services meet requirements for security, scalability, reliability, and performance.

- Troubleshoot integration and production issues and contribute to continuous platform improvements.

- Work closely with AI engineers, architects, and development teams to deliver robust platform capabilities.

Required Skills:

- 35 years of experience in backend engineering, platform engineering, or enterprise integration.

- Strong hands-on experience with REST APIs and asynchronous programming.

- Good understanding of authentication and authorization mechanisms such as OAuth2/JWT.

- Experience with databases and data integration.

- Hands-on experience with Docker and containerized applications.

- Exposure to AWS, Azure, or GCP cloud services.

- Understanding of enterprise integration patterns and secure API development.

- Good programming and problem-solving skills.

- Experience working in Agile development environments.

Good to Have:

- Exposure to AI/GenAI platforms, LLM applications, or ML services.

- Experience with API gateways, messaging systems, or event-driven architectures.

- Familiarity with Kubernetes and CI/CD pipelines.

- Understanding of microservices architecture.

Key Skills:

- Enterprise Integration, REST/Async APIs, Authentication & Authorization, Databases, Docker, Cloud Services, Platform Controls, AI/GenAI Integration.