Teams at Genesys

Build and operate scalable analytics data platforms using Java, Python, Spark, Airflow, Iceberg, and AWS. Responsibilities include developing batch pipelines, automated testing frameworks, CI/CD validation, data quality controls, representative test datasets, and release gates. The role also advances AI-driven engineering workflows, supports production reliability through on-call participation and incident analysis, and collaborates with distributed engineering teams to improve platform quality, scalability, and observability.

Lead the architecture and end-to-end delivery of enterprise IVR, routing, conversational AI, generative AI, and agentic virtual agent solutions. Responsibilities include developing bots, designing integrations, optimizing speech experiences, leading Agile delivery, establishing testing and deployment practices, advising customers, delivering training, and providing technical leadership. The role requires extensive experience with Dialogflow, Lex, enterprise APIs, architecture, software development, and customer-facing technical consulting.

Lead coordination and operational rhythm for an engineering platform portfolio. Ensure cross-team alignment, manage dependencies and risks, maintain Jira/Confluence tracking, produce executive communications and dashboards, improve documentation and automation, and streamline intake and reporting to accelerate delivery and reduce friction.