Jobs at Genesys

Develop full-stack Workforce Management software for enterprise customers. Build scalable backend services and APIs with Kotlin, Spring Boot, AWS Lambda, and cloud technologies, while creating responsive frontend experiences with TypeScript, Vue.js, HTML, and CSS/LESS. Collaborate with engineering, product, design, and cross-functional teams; write tested, maintainable code; troubleshoot defects; and improve system reliability, security, performance, and scalability. The role also involves code reviews, automated testing, continuous improvement, and responsible use of AI-assisted development tools.

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.

Leads sales strategy and customer engagement for Genesys AI and Experience Orchestration solutions. Partners with account executives, senior clients, and cross-functional teams to develop pipeline, shape opportunities, run customer workshops, coordinate AI proofs of concept, and support positioning, proposals, pricing, and presentations. Acts as a subject matter expert, develops territory and account strategies, enables sales teams, and influences AI-powered customer experience adoption.

Leads the Business Development organization across Canada and strategic accounts, owning pipeline-generation strategy, forecasting, conversion performance, and regional growth. Responsibilities include coaching and developing BDRs, creating enablement and promotion programs, partnering with Sales and Marketing on go-to-market strategies, analyzing pipeline data, scaling repeatable processes, and promoting CRM, sales engagement, and AI-enabled prospecting tools.

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.

Own Professional Services growth across strategic Canadian accounts by creating pipeline, leading complex services sales, shaping cloud and AI transformation opportunities, negotiating commercial structures, and expanding customer relationships. Partner with sales, customer success, solution consulting, and delivery teams to align services with customer outcomes, including migration, implementation, optimization, automation, analytics, and AI-powered customer experience transformation.

Own the quality strategy for high-volume batch analytics systems and data pipelines. Design automated test frameworks, validate REST APIs and distributed microservices, assess architecture risks, and execute functional, performance, security, and accessibility testing. Maintain Jenkins and TestNG CI/CD suites, lead exploratory validation, influence cross-functional engineering practices, and mentor junior engineers. The role focuses on ensuring reliability, scalability, and customer trust in cloud-based, multi-tenant platforms.

Lead the design and delivery of Agentic AI solutions to enhance customer experience and operational efficiency, focusing on enterprise-wide AI transformation.