Be the one building AI-powered experiences where they matter most.
At Genesys, we help organizations create better customer experiences through AI-powered experience orchestration. Our platform connects people, systems, data and AI to help organizations deliver more personalized service, improve operational efficiency and build stronger customer relationships.
Help build, support and operate technology used by more than 8,000 organizations in over 100 countries – moving AI from possibility to production in real-world enterprise environments every day.
The Genesys Partner AI Architect is a is a senior presales AI specialist who operates across four core motions:
Driving strategic Genesys Cloud CX and Genesys AI opportunities with Genesys Strategic Technology Partners, Global Systems Integrators (GSI), and Genesys sales teams showcasing the Genesys differentiated Genesys AI experience.
Scaling the Genesys partner ecosystem through creation of reusable assets, reference architectures, Pre-Sales technical enablement for Genesys partner’s Pre-Sales teams, and coaching. This role is pivotal in building assets that leverage the strengths of both Genesys and Genesys partners, allowing them to demonstrate the value of their solutions in combination with Genesys Cloud CX and Genesys AI capabilities.
Ensuring that partners understand the Genesys AI business and technical value proposition and are able to independently generate pipeline, articulating value, and delivering AI led outcomes. This is anchored in structured Pre-Sales enablement, repeatable frameworks, and targeted engagement models.
Shaping product and go-to-market direction through real-world partner and customer feedback
This role requires a blend of deep AI technical acumen, exceptional sales & communication skills, 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 workflows, tools, and orchestration layers. Define how AI interacts across the full journey (self-service, agent copilot, journey management, and back-office automation), including fallback strategies, human handoff, and failure handling.
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Optimize retrieval-augmented generation (RAG) and knowledge architectures to extend Genesys solutions where required. 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 that leverage real-time data and conversation state - Design how AI systems incorporate dynamic context such as customer data, interaction history, and external signals. Optimize context management and prompt structure to maximize relevance while managing token limits and response quality. Ensure AI interactions remain coherent, personalized, and aligned across channels and touchpoints.
Design for scalability, latency, and cost efficiency in enterprise environments - Evaluate and optimize AI 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 deliver performant and economically viable solutions. Ensure designs meet enterprise expectations for reliability and responsiveness.
Support Partner Development Lab Co-created Configurations: Work with Genesys Strategic Technology partners and GSI partners to build, refine, and optimize their Genesys Cloud development lab environments with a focus on AI. These labs will serve as the foundation for joint innovation, ensuring that both Genesys and partner teams can continuously iterate on solutions and use cases. This includes leading and facilitating remote and in person workshops educating and empowering Partners on the Genesys unique value proposition, roadmaps to help generate pipeline, help them to be more self-sufficient and drive Genesys Cloud and AI adoption.
Technical Escalation: Serve as a technical escalation point for difficult or complex integration issues that arise during partner Pre-Sales cycles. Provide advanced troubleshooting and solution development to resolve roadblocks effectively.
Mentor Genesys Partner’s Solution Consultant teams and act as a technical escalation point for complex technical issues.
Technical Field Readiness Assistance: Work with GSI and Genesys Strategic Technology partners, Genesys Product Management, Genesys Product Marketing, and Genesys Enablement teams to assist with technical field readiness. This may involve building assets, shared demo environments, videos, and assisting with RFx’s.
Support Strategic Pre-Sales Engagements: Co-sell with partners and Genesys Account Teams (when requested) in high impact opportunities by leading technical discovery, solution design, demonstrations, workshops, and value articulation.
Establish best practice frameworks: Create and maintain structured knowledge-sharing model across partners and internal teams including demos, success stories, and reusable assets.
Leverage expert-level knowledge of Genesys AI capabilities — including predictive AI and Agentic Virtual Agents —to articulate and demonstrate product value to customers and prospects.
Design and deploy AI prototypes in sandbox and/or partner and customer development environments to validate use cases, integrations, latency, and success criteria, and to highlight the differentiated value of Genesys AI.
Support partners, Genesys account teams, and professional services to transition successful prototypes into production pilots supporting technical handoff, hardening, KPI alignment, and business outcome validation through hands-on configuration and building of the production pilots.
Build integrations to third-party systems via RESTful APIs and emerging interoperability patterns such as MCP and A2A showcasing the art of the possible with Genesys Cloud AI solutions.
Develop reusable technical assets and enable Solution Consultants, partners, and account teams through workshops, deep-dive demonstrations, coaching, and scalable technical content.
Provide technical feedback and strategic insights to Product Management and Engineering on AI product design, implementation considerations, and customer-driven enhancements.
Support partners in influencing CIO/CTO-level stakeholders and position Genesys as integral to an organization’s broader IT and transformation strategy.
Requirements:
AI Architecture & Technical Judgment: Hands-on experience designing modern AI solutions for customer experience orchestration and contact center use cases using the right mix of classic ML, NLU/NLP, retrieval-based systems, LLMs, orchestration patterns, prompt engineering best practices, tool use and agentic approaches. Ability to make and defend architecture tradeoffs across latency, cost, explainability, governance, multilingual requirements, and business risk.
Enterprise Integration & Real-Time Design: Expertise integrating AI solutions with enterprise platforms, knowledge sources, RESTful APIs, event-driven architectures, identity systems, and b
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