sr. AI architect

TheGenesys AI ArchitectisaseniorpresalesAIspecialist whooperatesacrossthreecoremotions:

• Drivingstrategic AI opportunitieswithcustomers andsalesteams
• Scaling the field through reusable assets technical enablement and coaching
• Shaping product and go-to-market direction through real-world customer and field feedback

This role requires a blend of deep AI technical acumen exceptionalsales communication and executive storytellingskills and the ability to translate complex capabilities into clear actionable business value.

Key Responsibilities:

• Design end-to-end AI systems for customer experience use cases.Architect reliable production-ready AI solutions that go beyond prompt design combining LLMs deterministic workflowstoolsand orchestration layers. Define how AI interacts across the full journey (self-service agentcopilotjourney management andback-officeautomation) including fallback strategies human handoff and failure handling.

• Optimizeretrieval-augmented generation (RAG) and knowledge architectures to extend Genesys solutions whererequired.Design scalable knowledge and retrieval strategies that ground AI responses in enterprise data. Develop approaches for content structuring chunking embedding and ranking to ensure accuracy relevance and freshness. Partner with customers to align AI outputs with trusted knowledge sources while balancing performance latency and governance requirements.

• Establish AI evaluation frameworks and quality measurement strategies.Define how success is measured for AI-driven experiences including accuracy containment customer satisfaction and business impact. Create test sets evaluation methodologies and feedback loops to continuously improve performance. Translate technical quality metrics into business-relevant outcomes to support customer decision-making and adoption.

• Engineer contextual AI experiences thatleveragereal-time data and conversation state.Design how AI systems incorporate dynamiccontextsuch as customer data interaction history and external prompt structure to maximize relevance while managing token limits and response quality. Ensure AI interactionsremaincoherent personalized and aligned across channels and touchpoints.

• Design for scalability latency and cost efficiency in enterprise environments.Evaluate andoptimizeAI solutions for real-world constraints including response time (especially for voice) throughput and cost at scale. Make informed tradeoffs across model selection caching strategies and architecture patterns to deliverperformantand economicallyviablesolutions. Ensure designs meet enterprise expectations for reliability and responsiveness.

• Leverage expert-level knowledge of Genesys AI capabilitiesto articulate anddemonstrateproduct value to customers and prospects.

• Support pre-sales activitiessuch as technical discovery solution design product demonstrations sandbox/trial engagements AI integration guidance and value assessments.

• Design and deployAIprototypesin sandboxand/or customer development environments tovalidateuse cases integrations latency and success criteriaand to highlight the differentiated value of Genesys AI.

• Partner with account teams andProfessional Servicesto transition successful prototypes into production pilotssupporting technicalhandoffhardening KPI alignment and business outcome validation.

• Build integrations tothird-party systems via RESTful APIs and emerging interoperability patterns such as MCP and A2Ashowcasingthe art of the possiblewithGenesys Cloud AI solutions.

• Develop reusable technical assetsand enable Solution Consultants partners and account teams through workshops coaching and scalable technical content.

• Provide technical feedback and strategic insights toProduct Management and Engineeringon AI product design implementation considerations and customer-driven enhancements.

• Influence CIO/CTO-level stakeholders and position Genesysas integral to an organizations broader IT and transformation strategy.

Requirements:

• AI Architecture & Technical Judgment:Hands-on experiencedesigningmodern AI solutionsfor customer experienceorchestrationand contact center use casesusing the rightmix ofclassic ML NLU/NLPretrieval-based systemsLLMs orchestration patternstooluseand agenticapproaches. Ability to make and defend architecture tradeoffs across latency cost explainability governance multilingual requirements and business risk.

• Enterprise Integration & Real-Time Design:Expertiseintegrating AI solutions with enterprise platforms knowledge sourcesRESTfulAPIs event-driven architectures identity systems and broader cloud ecosystems. Able todesignforreal-world constraints including voice latency fallback paths throughput reliability and secure data access.

• Evaluation Governance & Observability:Ability to define AI evaluation strategies success metrics and monitoring approaches across offline and online testing retrieval quality tool-call accuracy safety drift auditability and cost control.

• Executive Communication & Field Enablement:Strong ability to translate complex AI architectures into clear business value for technical and executive stakeholders while also creating reusable assets workshops and enablement content that scale field capability across the SC organization.

• Prompt Design & AI Workflow Optimization: Practical experience designing prompts context strategies and orchestration flows as part of a broader system architecture rather than as a standalone discipline.

• Technical Demonstration Prowess:Provenability to create deliver and adapt compelling technical demonstrations and presentations that clearly articulate AI integration points and business impact.

• SalesAcumen:Demonstratedsuccess partnering with sales teams to understand customer challenges and provide AI-focused technical solutioning.

• BusinessValueOrientation:Ability toidentifyopportunities for process optimization and recommend AI-driven solutions that enhance customer outcomes and operational efficiency.

• ExecutivePresence:Provenability to influence CIO/CTO decision-makers.

• Strong understanding of the Genesys Cloud platform and Genesys AI preferred.

• Foundational understanding of programming concepts (Python preferred).

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