Senior AI Architect

Genesys•Hermosa Beach, CA

21h•$134,900 - $237,300•Hybrid

About The Position

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. Role Overview: The Senior AI Architect, Presales will shape how global enterprises apply AI to customer experience, designing architectures that turn advanced capabilities into reliable, scalable business outcomes. At Genesys, you will guide the technical direction of strategic AI opportunities, helping customers connect Genesys Cloud AI with enterprise data, workflows, knowledge, and broader cloud ecosystems. Operating as a senior presales AI specialist, you will lead solution architecture across self-service, agent assistance, journey management, and back-office automation. Working across LLMs, retrieval-augmented generation (RAG), deterministic workflows, tools, orchestration, enterprise integrations, and agentic AI, you will guide critical decisions involving accuracy, latency, scalability, cost, governance, security, and business risk. You will partner directly with sales and account teams, customers, Professional Services, Product Management, and Engineering to move complex AI opportunities from technical discovery through validation and production pilots. You will influence CIO and CTO stakeholders, connect architecture decisions to enterprise transformation priorities, and help customers create more relevant interactions, improve operational efficiency, and confidently adopt Genesys Cloud AI. Your impact will extend beyond individual customer engagements as you help expand AI expertise across the field and bring customer insight into broader product and go-to-market direction. The role provides exposure to strategic enterprise initiatives, platform-level decisions, and emerging AI capabilities shaping the future of customer experience.

Requirements

Extensive hands-on experience architecting modern AI solutions using the appropriate combination of traditional machine learning, NLU and NLP, retrieval-based systems, LLMs, orchestration patterns, tool use, and agentic AI approaches
Demonstrated architectural judgment and ability to make and defend tradeoffs across model selection, latency, cost, explainability, governance, multilingual requirements, security, scalability, and business risk
Deep expertise integrating AI solutions with enterprise platforms, knowledge sources, RESTful APIs, event-driven architectures, identity systems, and broader cloud ecosystems
Strong background designing real-time enterprise solutions that account for voice and digital latency, throughput, secure data access, reliability, fallback paths, failure handling, and system scalability
Demonstrated expertise defining AI evaluation, governance, and observability strategies spanning offline and online testing, retrieval quality, tool-call accuracy, safety, drift, auditability, and cost control
Practical experience with prompt design, context management, RAG, and AI workflow optimization as components of broader production-ready AI architectures
Proven ability to create and deliver compelling technical demonstrations, prototypes, and presentations that connect complex architecture decisions to customer and business value
Demonstrated success partnering with sales teams on technical discovery and AI-focused solution design, with strong business judgment in identifying opportunities to improve customer outcomes, operational efficiency, and enterprise processes
Strong executive communication, storytelling, and presence, with demonstrated ability to influence CIO, CTO, and senior technical stakeholders

Nice To Haves

Strong understanding of Genesys Cloud and Genesys AI capabilities
Experience designing AI solutions for customer experience orchestration, contact centers, self-service, agent assistance, journey management, or back-office automation
Experience creating reusable technical assets and enablement that scale AI expertise across solution consulting, partner, sales engineering, or related field organizations
Experience partnering with Product Management and Engineering to translate customer and field insights into product or platform improvements

Responsibilities

Architect production-ready AI systems for customer experience use cases that combine LLMs, deterministic workflows, tools, orchestration layers, human handoffs, fallback strategies, and failure handling
Design scalable RAG and enterprise knowledge architectures, including strategies for content structuring, chunking, embedding, ranking, and trusted knowledge integration, to improve response accuracy, relevance, and freshness while balancing latency, performance, security, and governance requirements
Establish AI evaluation and observability frameworks that connect accuracy, retrieval quality, tool-call performance, containment, customer satisfaction, safety, drift, cost, and other technical measures to customer and business outcomes
Engineer contextual AI experiences that use real-time customer data, interaction history, conversation state, and external signals to deliver coherent and personalized experiences across channels and touchpoints
Optimize enterprise AI architectures for scalability, voice and digital latency, throughput, reliability, and cost through informed decisions about model selection, caching, context management, and architecture patterns
Drive strategic presales engagements through technical discovery, solution architecture, product demonstrations, sandbox and trial engagements, AI integration guidance, and value assessments that advance enterprise opportunities
Develop and validate AI prototypes through production pilot readiness, partnering with account teams and Professional Services to prove use cases and integrations, validate latency and success criteria, harden architectures, align KPIs, and confirm business outcomes
Demonstrate the value of Genesys Cloud AI by connecting platform capabilities, architecture patterns, integrations, and emerging interoperability approaches, including Model Context Protocol (MCP) and agent-to-agent (A2A), to customer requirements and measurable business outcomes
Scale field capability by developing reusable technical assets, workshops, coaching, and enablement for Solution Consultants, partners, and account teams
Influence AI product and go-to-market direction by translating customer requirements, implementation insights, and field feedback into actionable guidance for Product Management and Engineering