Principal, AI Strategy & Automation Architect

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 Principal, AI Strategy & Automation Architect is a senior technical‑strategic role responsible for designing and building the automation, data, and prototype capabilities that enable the NACS AI Strategy Team to scale its impact.

This role bridges AI strategy, technical architecture, data engineering, automation, and practical prototyping. The Architect will help transform outcome‑led AI methodologies into reusable tools, accelerators, technical patterns, lightweight applications, data workflows, and decision‑support assets that improve how internal teams shape, measure, and execute AI strategies.

This is not a Product, Sales, or traditional software delivery role. The Architect does not own product roadmap, quota, or production implementation delivery. Instead, this individual supports strategic enablement by building practical internal accelerators, proof‑of‑concept tools, data automation workflows, and technical advisory assets that help teams evaluate AI opportunities, assess readiness, understand feasibility, measure outcomes, and improve consistency across engagements.

The ideal candidate is a hands‑on technical builder with strong business context – someone who can work with ambiguity, understand customer experience and AI strategy, and rapidly turn concepts into usable tools, prototypes, automations, and analytical assets.

Key Responsibilities:

• Partner with AI strategy, analytics, advisory, and delivery teams to translate outcome‑led AI methods into scalable technical assets.
• Design and build practical tools that support AI opportunity mapping, KPI alignment, readiness assessment, value realization, health checks, journey analysis, and outcome measurement.
• Support complex customer and internal scenarios by assessing technical feasibility, data availability, integration considerations, and automation opportunities.
• Translate ambiguous strategic needs into working prototypes, data workflows, proof‑of‑concept applications, and reusable technical patterns.
• Help internal teams move from manual, one‑off analysis toward repeatable, scalable, and automated methods.

• Build internal accelerators, lightweight applications, scripts, dashboards, data workflows, and automation assets that improve team efficiency and consistency.
• Develop prototypes that demonstrate how AI strategy, measurement, and operational data can be connected to actionable recommendations.
• Create reusable automation patterns for customer health checks, KPI tree generation, value realization scorecards, readiness assessments, use case prioritization, and engagement preparation.
• Design tools that help teams synthesize customer context, operational performance, AI adoption data, digital journey friction, and business goals into practical strategic recommendations.
• Use AI‑assisted development, LLMs, APIs, automation frameworks, and data tools to improve speed, quality, and repeatability of strategic engagements.

• Work with Genesys Cloud data, APIs, analytics exports, conversation data, queue/routing metrics, bot and flow data, digital engagement data, and related operational datasets.
• Design repeatable data models and workflows that support outcome measurement, baseline analysis, adoption tracking, performance diagnostics, and optimization recommendations.
• Partner with strategy and analytics leads to turn KPI frameworks and value models into scalable technical tools.
• Assess data quality, reporting maturity, integration constraints, and technical readiness as part of AI strategy and value…