Senior AI Architect

Role Overview

• 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.
• 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.
• Leverage expert-level knowledge of Genesys AI capabilities to articulate and demonstrate product value to customers and prospects.
• Support pre-sales activities such as technical discovery, solution design, product demonstrations, sandbox/trial engagements, AI integration guidance, and value assessments.
• Design and deploy AI prototypes in sandbox and/or customer development environments to validate use cases, integrations, latency, and success criteria, and to highlight the differentiated value of Genesys AI.

Requirements

• 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, tool use and agentic approaches.
• Ability to make and defend architecture tradeoffs across latency, cost, explainability, governance, multilingual requirements, and business risk.
• Expertise integrating AI solutions with enterprise platforms, knowledge sources, RESTful APIs, event-driven architectures, identity systems, and broader cloud ecosystems.
• Able to design for real-world constraints including voice latency, fallback paths, throughput, reliability, and secure data access.
• 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.
• 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.
• Practical experience designing prompts, context strategies, and orchestration flows as part of a broader system architecture, rather than as a standalone discipline.
• Proven ability to create, deliver, and adapt compelling technical demonstrations and presentations that clearly articulate AI integration points and business impact.
• Demonstrated success partnering with sales teams to understand customer challenges and provide AI-focused technical solutioning.
• Ability to identify opportunities for process optimization and recommend AI-driven solutions that enhance customer outcomes and operational efficiency.
• Proven ability to influence CIO/CTO decision-makers.

Tech Stack

• Cloud

Benefits

• Medical, Dental, and Vision Insurance.
• Telehealth coverage
• Flexible work schedules and work from home opportunities
• Development and career growth opportunities
• Open Time Off in addition to 10 paid holidays
• 401(k) matching program
• Adoption Assistance
• Fertility treatments