Sr. Cloud Platform Engineer

We are seeking a Sr. Cloud Platform Engineer to lead the design, development, and delivery our AI Services platform and framework, enabling enterprise-grade AI services and self-service capabilities across the organization. This role is critical to establishing the foundational platform layer that powers AI applications and services at scale. At Genesys, we are transforming the customer experience landscape with empathy, AI innovation, and global impact. Joining Genesys means becoming part of a global team that is redefining how companies engage with their customers while ensuring that AI is built responsibly, securely, and for long-term enterprise success.

Key Responsibilities

• Design and Develop Cloud Solutions: Architect and implement robust, scalable, and secure cloud-based applications and services on AWS.
• Containerization Deployment: Create, manage, and optimize containerized workloads using Terraform, Docker and Kubernetes to support CI/CD pipelines and production scalability.
• API Event-Driven Development: Build and maintain asynchronous and synchronous APIs, event streams, and messaging integrations to enable distributed system communication.
• AI/ML Integration: Develop and integrate AI and ML capabilities using vector databases, Jupyter Notebooks, and SageMaker. Collaborate with data scientists to operationalize models.
• Data Management: Design and manage data storage solutions using relational databases (SQL), NoSQL systems, and object stores (such as AWS S3).
• Software Quality Version Control: Apply software development best practices, including test-driven development (TDD), automated testing, and version control using GitHub.
• Monitoring Observability: Implement and maintain event-driven observability solutions, including metrics, logging, and alerting systems for performance and reliability.
• Collaboration Documentation: Work cross-functionally with engineering, data science, and DevOps teams. Maintain clear technical documentation and design specifications.

Required Qualifications

• bachelors or masters degree in Computer Science, Software Engineering, or related field
• Proven 5+ Years of experience designing and building scalable, distributed platforms (microservices, event-driven systems, APIs).
• Expertise in cloud platforms (AWS) and container orchestration (Kubernetes, Docker)
• Hands-on experience with AI platforms such as ChatGPT, AWS Q, or similar
• Strong programming and automation skills using Python
• Experience with MLOps and AI service delivery (model serving, pipelines, monitoring)
• Familiarity with enterprise security, compliance, and governance frameworks