Genesys
AI Strategy Engagement Lead, CX Advisory
United States, USA
Sponsorship not specified$136k-$239kDetected 71 days ago
Machine LearningData VisualizationNLPAgentic AIBusiness DevelopmentExcelCustomer SuccessLeadershipCommunicationCollaborationPublic SpeakingAdaptabilityMicrosoft Office
About the role
- We employ more than 6,000 people across the globe who embrace empathy and cultivate collaboration to succeed.
- They should have a passion for leveraging AI to solve real-world problems, a deep understanding of operational efficiency, and a track record of delivering business value through data-driven decision-making.
- Actual salaries will vary depending on a candidate's experience, qualifications, skills, and location.
Responsibilities
- Lead AI Transformation initiatives, ensuring customer success throughout the consulting lifecycle, from pre-sales activities to delivery and post-implementation support.
- Facilitate design thinking workshops and work sessions to define AI opportunities, solutions, and transformation roadmaps.
- Analyze data and customer processes to provide strategic AI recommendations that drive measurable impact.
- Collaborate with Genesys product, engineering, and delivery teams to ensure the seamless integration of AI solutions into the Genesys platform.
- Build and refine repeatable AI advisory and transformation frameworks, with an emphasis on scalable and industry-specific solutions.
- Partner with cross-functional teams (e.g., Product, Sales, Marketing) to position Genesys's AI capabilities as a competitive differentiator in the market.
- Contribute to the creation of sales collateral, thought leadership materials, and AI success stories to drive business growth.
- Support RFP responses, SOW development, and other pre-sales activities to drive the adoption of AI solutions.
- Solution Design & Development
- Collaborate with internal and external stakeholders to champion ethical AI practices, ensuring solutions are secure, compliant, and aligned with customer needs.
Requirements
- 10+ years of relevant experience, preferably in management consulting, AI strategy and transformation, or SaaS value consulting role in an analytical environment
- Proven track record in delivering large-scale AI-driven initiatives within enterprise environments.
- Familiarity with AI integration into SaaS platforms, especially in contact center or CX transformation settings.
- Experience with designing and deploying AI-based solutions to improve customer and operational outcomes.
- Strong ability to define and execute AI roadmaps that align with business objectives.
- Strong ability to use data storytelling techniques to translate technical insights into actionable business recommendations.
- Proficiency in creating impactful presentations using tools such as Excel, PowerPoint, and data visualization platforms.
- Background
- relevant masters is a bonus
- AI Expertise
- Deep understanding of AI technologies, including machine learning, natural language processing, automation, and analytics.
- Strategic Thinking and Leadership
- Proven ability to influence C-suite executives, align cross-functional stakeholders, and drive executive-level decisions that accelerate AI adoption and value realization.
- Adept at identifying, structuring, and solving complex business problems using AI-driven insights.
- Data-Driven Decision-Making
Nice to have
- A bachelor's degree (business or STEM focus preferred)
Skills
- To learn more, visit www.genesys.com.
Compensation
- This role has a market-competitive salary with an anticipated base compensation range listed below.
- $135,600.00 - $238,600.00
Benefits
- Medical, Dental, and Vision Insurance.
- Telehealth coverage
- Flexible work schedules and work from home opportunities
- Open Time Off in addition to 10 paid holidays
- Click here to view a summary overview of our Benefits.
Company info
- Develop tailored AI strategies and solutions by understanding customers' business challenges, goals, and operational contexts.
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This listing is sourced directly from Genesys's careers page and normalized into a canonical job model.