Cloud Platform Engineer @ Genesys

We are seeking a Cloud Platform Engineer to design, develop, and deliver 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.

About the Team

The Data & AI Platform team is a central group comprised of Data Engineering, Data Platform/Technologies, Data Analytics, Data Science, Data Product, AI, and Data Governance practices. This team serves the enterprise, including sales, finance, marketing, customer success, product, and more. It acts as a core conduit and partner to operational systems that run the business, such as Salesforce and Workday.

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 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

Bachelor s or Master s degree in Computer Science, Software Engineering, or related field.

Proven 3+ Years of experience designing and building scalable, distributed platforms (microservices, event-driven systems, APIs).

Expertise in cloud platforms (AWS) and container orchestration (Terraform, Kubernetes, Docker).

Hands-on experience with AI platforms such as ChatGPT, AWS Q, or similar.

Strong programming and automation skills using Python.

Preferred Qualifications

Experience with MLOps and AI service delivery (model serving, pipelines, monitoring).

Familiarity with enterprise security, compliance, and governance frameworks.