Senior Director, AI Product Strategy

📍 Job Overview

Job Title: Senior Director, AI Product Strategy

Company: Ryan

Location: Dallas, Texas, United States

Job Type: Full-Time

Category: Revenue Operations / GTM Strategy / Product Management (AI Focus)

Date Posted: December 1, 2025

Experience Level: 10+ Years

Remote Status: Hybrid

🚀 Role Summary

• This pivotal role focuses on defining and executing the product strategy for transformative AI-enabled solutions, specifically within the tax and compliance technology domain.

• Responsibilities include leading cross-functional teams to innovate with machine learning, automation, and generative AI, directly impacting operational efficiency and client value.

• The position requires a strategic thinker and operator adept at translating advanced AI technologies into tangible business outcomes and client-facing experiences.

• Success hinges on driving impact through data-informed insights, customer empathy, product craft, and a continuous learning mindset, balancing long-term vision with agile execution.

📝 Enhancement Note: While the title is "Senior Director, AI Product Strategy," the core responsibilities and required skills strongly align with advanced Revenue Operations, Go-To-Market (GTM) Strategy, and Product Management roles, particularly those focused on leveraging AI to drive operational efficiency and client value in enterprise SaaS. The emphasis on "operational efficiency," "scalable value for clients," and "transformative AI-enabled solutions" points to a strong operations component, even within a product strategy framework.

📈 Primary Responsibilities

• Spearhead the product strategy and detailed roadmap for AI-first features, encompassing ML-powered document processing, generative AI use cases (e.g., "AskRyan" knowledge base expansion), and sophisticated decision automation tools.

• Collaborate intimately with Data Science, Engineering, and User Experience (UX) teams to ensure the successful development and deployment of scalable, explainable, and robust AI capabilities into production environments.

• Drive the entire product lifecycle for AI features: from initial data readiness assessment and prototyping through rigorous testing, successful market launch, and continuous post-release iteration based on performance metrics and user feedback.

• Define clear, measurable Key Performance Indicators (KPIs) for all AI solutions, meticulously ensuring that model outcomes and product performance directly align with overarching business objectives and revenue goals.

• Lead the development and implementation of human-in-the-loop systems, robust AI safety protocols, and efficient governance workflows to ensure responsible and ethical AI deployment.

• Partner closely with diverse stakeholders across the organization to champion and implement responsible AI principles, including data ethics, privacy considerations, and model interpretability.

• Manage and mentor cross-functional delivery teams, adeptly build and prioritize product backlogs for AI features and essential platform enablers to drive consistent progress.

• Clearly articulate complex technical concepts, potential risks, and demonstrable value propositions to a wide range of audiences, from executive leadership to non-technical teams.

• Represent Ryan in strategic AI partnerships, lead vendor selection processes for AI technologies, and contribute to thought leadership efforts within the AI and tax technology space.

📝 Enhancement Note: The responsibilities highlight a blend of strategic product vision and hands-on operational execution. The emphasis on "ML-powered document processing," "decision automation tools," and "human-in-the-loop systems" directly translates to optimizing core business processes, a key function within revenue operations and GTM.

🎓 Skills & Qualifications

Education:

Experience:

• Minimum of 10 years of direct, progressive experience in product management roles within the technology sector.

• Demonstrated track record of successfully launching and scaling AI/ML-enabled products, particularly within enterprise SaaS, compliance technology, or complex data-intensive domains.

• Proven ability to translate complex technical concepts and AI model outputs into intuitive, user-friendly customer experiences and actionable business insights.

• Skilled in balancing aggressive speed-to-market requirements with stringent regulatory compliance, robust data security protocols, and ethical AI best practices.

• Strong cross-functional leadership capabilities, with a proven talent for effective product storytelling and influencing diverse stakeholder groups.

Required Skills:

• Product Management: Deep expertise in product lifecycle management, roadmap development, and feature prioritization for complex software products.

• AI/ML Product Development: Significant experience in defining, launching, and iterating on AI/ML-enabled features, understanding their unique development cycles and challenges.

• AI Technologies: Familiarity with Natural Language Processing (NLP), classification models, embeddings, vector search, prompt engineering, and Generative AI (GenAI) tools and applications.

• Data Science & Engineering Collaboration: Ability to effectively partner with Data Science and Engineering teams, understanding their methodologies and requirements for AI model development and deployment.

• Cross-Functional Leadership: Proven ability to lead and influence diverse teams (Engineering, Data Science, UX, Marketing, Sales) without direct authority.

• Product Storytelling: Exceptional ability to articulate product vision, strategy, and value propositions compellingly to various audiences.

• Customer Empathy: A deep understanding of customer needs and the ability to translate them into product requirements and user-centric designs.

• Operational Efficiency: A keen focus on identifying opportunities for process automation and efficiency gains through technology.

Preferred Skills:

• Advanced AI/ML Concepts: Deeper understanding of specific ML algorithms, statistical modeling, and AI infrastructure.

• Enterprise SaaS & Compliance Tech: Direct experience within the tax, compliance, or financial technology sectors.

• UX/UI Design Principles: Familiarity with user-centered design methodologies and their application in AI product development.

• Business Acumen: Strong understanding of business strategy, financial modeling, and ROI analysis, particularly as it relates to technology investments.

• Agile Methodologies: Advanced knowledge of Scrum, Kanban, or other agile frameworks.

• Prompt Engineering Expertise: Demonstrable skill in crafting effective prompts for GenAI models to achieve desired outputs.

• AI Safety & Governance: Experience in developing and implementing AI ethics frameworks, safety protocols, and compliance measures.

📝 Enhancement Note: The detailed breakdown of required and preferred skills, particularly those related to AI technologies and cross-functional collaboration, is crucial for candidates to tailor their applications and highlight relevant experience. The emphasis on "operational efficiency" and "customer empathy" underscores the role's connection to business outcomes.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• AI Product Case Studies: Showcase 2-3 detailed case studies of AI/ML-enabled products you have managed from conception to launch. Each case study should clearly articulate the problem statement, the AI solution implemented, your specific role and contributions, the methodologies used (e.g., agile, data-driven iteration), and measurable outcomes.

• Process Optimization Examples: Provide examples of how you have leveraged AI or automation to significantly improve operational efficiency, reduce costs, or enhance client experience within a previous role. Quantify the impact wherever possible (e.g., percentage reduction in processing time, increase in accuracy).

• System Implementation Standards: Demonstrate experience in defining requirements for and overseeing the implementation of complex software systems, particularly those involving AI/ML components, data pipelines, and API integrations. Highlight your understanding of scalability, security, and maintainability.

• ROI Demonstration: Include examples or explanations of how you have measured and communicated the Return on Investment (ROI) for AI product initiatives, linking technical advancements to business value and client success.

Process Documentation:

• Workflow Design & Optimization: Evidence of designing, documenting, and optimizing complex workflows, especially those enhanced by AI, machine learning, or automation. This includes mapping current states, identifying bottlenecks, and proposing future-state solutions.

• Implementation & Automation: Documentation or examples of processes for implementing new AI features, integrating them into existing systems, and automating repetitive tasks to drive efficiency.

• Measurement & Performance Analysis: Processes for defining, tracking, and analyzing key performance indicators (KPIs) for AI products and operational processes. This includes setting up dashboards, conducting A/B tests, and reporting on performance to stakeholders.

📝 Enhancement Note: For a role like this, a portfolio demonstrating practical application of AI in product strategy and operational improvement is critical. Candidates should focus on quantifiable results and clear articulation of their strategic thinking and execution capabilities.

💵 Compensation & Benefits

Salary Range:

• Estimated Range: $180,000 - $250,000 annually.

• Methodology: This estimate is based on industry benchmarks for Senior Director-level Product Management roles with a strong AI/ML focus in major metropolitan areas like Dallas, Texas. Factors considered include the 10+ years of experience requirement, the strategic nature of the role, its leadership responsibilities, and the specialized AI/ML expertise demanded. Compensation will also be influenced by the candidate's specific experience, qualifications, and performance during the interview process.

Benefits:

• Hybrid Work Options: Flexibility to balance remote work with in-office collaboration.

• Award-Winning Culture: A recognized positive and supportive work environment.

• Generous Personal Time Off (PTO) Benefits: Ample paid time off for rest and rejuvenation.

• 14-Weeks of 100% Paid Leave for New Parents: Comprehensive parental leave policy, inclusive of adoption.

• Monthly Gym Membership/Equipment Reimbursement: Support for employee health and wellness.

• Benefits Eligibility Effective Day One: Immediate access to health, dental, and vision insurance.

• 401K with Employer Match: Retirement savings plan with company contributions.

• Tuition Reimbursement: Financial assistance for continued education and professional development.

• Fertility Assistance Program: Support for employees pursuing fertility treatments.

• Four-Week Company-Paid Sabbatical: Opportunity for extended leave after five years of service.

Working Hours:

• Standard full-time hours are expected, typically around 40 hours per week. However, given the senior leadership and product strategy nature of the role, flexibility and a willingness to work beyond standard hours to meet project deadlines and business needs will be essential.

📝 Enhancement Note: The provided salary range is an estimate. Candidates should research local Dallas compensation for similar roles and come prepared to discuss their salary expectations. The extensive benefits package at Ryan is a significant draw and should be a key consideration for applicants.

🎯 Team & Company Context

🏢 Company Culture

Industry: Tax Services & Technology. Ryan operates within the global tax services industry, providing a unique blend of expertise and technology solutions to help clients manage their tax obligations efficiently. They are actively transforming into a "world's trusted platform for tax," indicating a strong focus on integrating advanced technology with deep domain knowledge.

Company Size: Ryan is a large organization, indicated by its global presence and the mention of various employee levels and departments. This size offers opportunities for significant impact and broad exposure to different business functions.

Founded: Ryan was founded with a mission to liberate clients from tax burdens, evolving into a comprehensive tax solutions provider. While the exact founding year isn't provided, its sustained presence and multiple "Best Places to Work" awards suggest a stable, growth-oriented, and employee-focused culture.

Team Structure:

• AI Product Team: This role will likely lead a dedicated team focused on AI product development, comprising product managers, AI/ML engineers, data scientists, and UX designers.

• Reporting Structure: The Senior Director will report to a higher-level executive, likely a VP or SVP of Product, Technology, or Strategy, and will be responsible for managing and mentoring direct reports.

• Cross-Functional Collaboration: Close collaboration is expected with various departments, including Engineering, Data Science, Sales, Marketing, Legal, and Client Services, to ensure seamless integration and successful adoption of AI solutions.

Methodology:

• Data-Driven Insights: A strong emphasis on using data analytics to inform product strategy, measure performance, and drive decision-making.

• Agile & Iterative Development: The company embraces agile methodologies, focusing on rapid iteration, continuous improvement, and adaptability to market changes.

• Customer-Centricity: A core philosophy of understanding and addressing client needs through innovative product solutions, with a focus on empathy and delivering exceptional user experiences.

• Innovation & Efficiency: A commitment to exploring and implementing cutting-edge technologies like AI to enhance operational efficiency and create scalable value.

Company Website: https://ryans.world/

📝 Enhancement Note: Ryan's focus on blending tax expertise with technology, particularly AI, positions this role at the forefront of innovation in their industry. Understanding their mission to be a "trusted platform" is key to aligning with the company's strategic direction.

📈 Career & Growth Analysis

Operations Career Level: This is a senior leadership position, equivalent to a Director or VP level within a product or operations function. It involves significant strategic responsibility, team leadership, and direct impact on the company's technological direction and client offerings. The role requires a blend of strategic thinking, technical understanding (specifically in AI/ML), and execution prowess.

Reporting Structure: The Senior Director will likely report to a Vice President or Senior Vice President of Product Management, Technology, or a related strategic function. They will have direct reports, including product managers, AI specialists, and potentially data scientists.

Operations Impact: This role is critical for driving operational efficiency and client value through AI. Success will directly influence revenue growth by creating new AI-powered product offerings, improving client retention through better user experiences, and reducing internal operational costs through automation. The impact is strategic and directly tied to the company's mission to become a leading tax technology platform.

Growth Opportunities:

• Executive Leadership Advancement: Successful performance in this role can pave the way for advancement into VP or even C-suite positions within product, technology, or operations at Ryan.

• Specialization in AI/ML Product: Deepen expertise in cutting-edge AI and machine learning applications within a specialized industry (tax technology), becoming a recognized leader in the field.

• Strategic Influence: Gain significant influence over the company's technological roadmap and strategic direction, shaping the future of AI integration in tax services.

• Team Building & Mentorship: Develop strong leadership and team-building skills by managing and mentoring a high-performing team of AI product professionals.

• Industry Thought Leadership: Opportunities to represent Ryan at industry conferences, contribute to publications, and build a personal brand as an expert in AI product strategy.

📝 Enhancement Note: This role offers a clear path for career progression into executive leadership, especially for individuals passionate about AI and its application in enterprise solutions. The opportunity to shape a company's technological future is a significant growth aspect.

🌐 Work Environment

Office Type: Ryan operates a hybrid work model. This means employees can expect a blend of remote work and in-office presence, allowing for flexibility while maintaining team cohesion and collaboration.

Office Location(s): The primary location for this role is Dallas, Texas. While remote work is an option, the hybrid model suggests that regular office attendance in Dallas will be expected for team meetings, strategic sessions, and collaborative work.

Workspace Context:

• Collaborative Environment: The hybrid model fosters collaboration through scheduled in-office days for team meetings, brainstorming sessions, and cross-functional work.

• Operations Tools & Technology: Employees will have access to modern technology infrastructure and a suite of tools necessary for product management, AI development, and data analysis. This includes collaboration software, project management tools, and potentially access to cloud-based AI/ML platforms.

• Team Interaction: Opportunities for regular interaction with a diverse team of AI product specialists, data scientists, engineers, and business stakeholders, both virtually and in person.

Work Schedule:

• The standard work schedule is full-time (approximately 40 hours per week). However, given the senior leadership and strategic nature of the role, flexibility will be required to meet project deadlines, participate in critical meetings, and respond to urgent business needs. This may involve occasional work outside of standard business hours.

📝 Enhancement Note: The hybrid nature of the work environment is a key benefit. Candidates should clarify expectations regarding in-office presence and how the hybrid model is implemented for their specific team.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A brief call with a recruiter to assess basic qualifications, cultural fit, and salary expectations.

• Hiring Manager Interview: A deep dive into your experience with AI product management, strategy development, and leadership. Expect questions about your approach to defining roadmaps, managing cross-functional teams, and driving AI innovation.

• Technical/Product Deep Dive: This stage may involve a technical assessment or a product strategy case study. You might be asked to analyze an AI product challenge, propose a strategy, or discuss specific AI technologies and their applications. Be prepared to discuss your portfolio in detail.

• Cross-Functional Stakeholder Interviews: Meetings with potential peers and collaborators from Engineering, Data Science, UX, and business units. These interviews will assess your ability to collaborate, communicate effectively, and build consensus.

• Executive Interview: A final interview with a senior leader (e.g., VP/SVP) to evaluate strategic thinking, leadership potential, and overall fit with Ryan's vision and culture.

Portfolio Review Tips:

• Quantify Impact: For each case study, ensure you provide clear, quantifiable metrics demonstrating the success of your AI products (e.g., increased efficiency by X%, reduced errors by Y%, generated $Z in new revenue).

• Showcase AI/ML Specificity: Clearly articulate the AI/ML techniques used, the challenges in implementation, and how you navigated them. Highlight your understanding of model performance, explainability, and ethical considerations.

• Process Improvement Focus: When presenting process optimization examples, detail the "before" and "after" states, the specific process changes you implemented (especially those involving AI/automation), and the resulting operational improvements.

• Storytelling: Frame your portfolio items as compelling stories. Start with the problem, explain your strategic approach, detail your execution, and conclude with the measurable impact.

Challenge Preparation:

• AI Product Strategy Case Study: Practice developing a product strategy for an AI feature within the tax/compliance space. Consider target users, key features, competitive landscape, technical feasibility, and go-to-market plan.

• Process Optimization Scenario: Be ready to analyze a hypothetical operational bottleneck and propose an AI-driven solution, outlining implementation steps, potential risks, and expected outcomes.

• Stakeholder Communication: Prepare to explain complex AI concepts and strategies to both technical and non-technical audiences, demonstrating your ability to build alignment and gain buy-in.

📝 Enhancement Note: Candidates should prepare to demonstrate not just theoretical knowledge but practical, hands-on experience with AI product development and its impact on operational efficiency. A well-curated portfolio is essential for this role.

🛠 Tools & Technology Stack

Primary Tools:

• Product Management Platforms: Tools like Jira, Confluence, Asana, or Aha! for backlog management, roadmap planning, and documentation.

• AI/ML Development Platforms: Experience with cloud-based AI platforms such as AWS SageMaker, Google AI Platform, Azure Machine Learning, or Databricks.

• Data Analysis & Visualization: Proficiency in tools like Tableau, Power BI, Looker, or Python libraries (Pandas, NumPy, Matplotlib) for data exploration and reporting.

• Collaboration Suites: Microsoft 365 (Teams, SharePoint, OneDrive) or Google Workspace for daily communication and collaboration.

Analytics & Reporting:

• Business Intelligence Tools: Experience with BI platforms for creating dashboards and reports to track AI product performance and operational metrics.

• A/B Testing Tools: Familiarity with tools for conducting experiments to optimize AI models and user experiences.

• CRM & Sales Enablement Tools: Understanding of how AI products integrate with or impact systems like Salesforce or similar CRM platforms, and how they support sales and client success efforts.

CRM & Automation:

• CRM Systems: While not directly managing CRM, understanding its role in the client journey and how AI tools can integrate with or enhance CRM data and processes is important.

• Workflow Automation Tools: Familiarity with tools or concepts related to automating business processes, potentially including RPA (Robotic Process Automation) or custom scripting.

• API Integration: Understanding of how AI services and products are integrated into larger software ecosystems via APIs.

📝 Enhancement Note: While specific tools may vary, a strong understanding of the AI/ML development lifecycle, data analysis techniques, and collaborative platforms is crucial. Candidates should highlight experience with similar tools and demonstrate adaptability to new technologies.

👥 Team Culture & Values

Operations Values:

• Innovation & Continuous Improvement: A drive to constantly seek out new AI technologies and methodologies to improve products and processes, fostering a culture of experimentation and learning.

• Data-Driven Decision Making: A commitment to using data and analytics as the foundation for strategic decisions, product development, and performance measurement.

• Customer Centricity & Empathy: A deep focus on understanding customer needs and challenges, translating them into user-centric solutions that deliver tangible value.

• Collaboration & Transparency: An emphasis on working effectively across teams, sharing knowledge openly, and fostering a supportive environment where diverse perspectives are valued.

• Accountability & Ownership: A strong sense of personal and team responsibility for delivering high-quality products and achieving business objectives.

Collaboration Style:

• Cross-Functional Integration: The role demands seamless collaboration with Engineering, Data Science, UX, Sales, and Marketing teams. This involves proactive communication, shared goal-setting, and a willingness to adapt to the needs of different departments.

• Process Review & Feedback: An open culture for reviewing processes, providing constructive feedback, and collectively identifying areas for enhancement, particularly in the application of AI.

• Knowledge Sharing: Encouragement of sharing insights, best practices, and learnings from AI initiatives across the organization to foster collective growth and innovation.

📝 Enhancement Note: Ryan's stated values of innovation, customer focus, and collaboration are central to this role. Candidates should be prepared to articulate how their personal values and working style align with these principles, especially in the context of AI development and operational improvement.

⚡ Challenges & Growth Opportunities

Challenges:

• Translating AI Potential to Business Value: A primary challenge will be bridging the gap between cutting-edge AI capabilities and demonstrable, quantifiable business outcomes and client value in the complex tax domain.

• Navigating AI Ethics & Governance: Developing and implementing AI solutions responsibly, ensuring fairness, transparency, privacy, and compliance with evolving regulations will be critical.

• Cross-Functional Alignment: Gaining consensus and driving adoption of AI-powered products across diverse stakeholder groups with varying technical understanding and priorities.

• Rapid Technological Evolution: Keeping pace with the fast-moving field of AI and machine learning to ensure Ryan's products remain competitive and leverage the latest advancements.

• Data Readiness & Quality: Ensuring access to sufficient, high-quality data required for training and deploying effective AI models within the tax and compliance context.

Learning & Development Opportunities:

• AI Specialization: Deepen expertise in emerging AI fields like generative AI, large language models (LLMs), and advanced ML techniques through dedicated learning paths and project work.

• Industry Conferences & Certifications: Opportunities to attend leading AI, product management, and tax technology conferences, and pursue relevant certifications.

• Mentorship & Leadership Development: Access to senior leadership mentorship and formal leadership training programs to hone strategic and management skills.

• Cross-Functional Exposure: Gain broad exposure to various business functions within Ryan, understanding how AI impacts different areas of the company and client services.

📝 Enhancement Note: Candidates should demonstrate an awareness of these challenges and proactively discuss strategies for overcoming them, highlighting their problem-solving skills and adaptability. The growth opportunities are significant for those looking to lead in the AI product space.

💡 Interview Preparation

Strategy Questions:

• "How would you define the product strategy and roadmap for AI features at Ryan, considering our mission to be the world's trusted platform for tax?" (Prepare to discuss your framework for strategy development, prioritization, and alignment with company goals.)

• "Describe a time you had to lead a cross-functional team to launch a complex AI product. What were the biggest challenges, and how did you overcome them?" (Focus on your leadership style, communication strategies, and ability to manage diverse technical and business stakeholders.)

Company & Culture Questions:

• "Based on your research, how do you see AI transforming the tax and compliance industry, and what is Ryan's potential role in that transformation?" (Demonstrate you've researched Ryan's mission and industry position.)

• "How would you foster a culture of innovation and continuous learning within your AI product team, and how would you collaborate with other departments like Sales and Client Services?" (Showcase your understanding of team dynamics and cross-functional collaboration.)

Portfolio Presentation Strategy:

• Structure Your Narrative: For each case study, follow a clear story arc: Problem -> Solution (your AI product) -> Your Role & Strategy -> Execution -> Measurable Impact (quantified results).

• Highlight AI/ML Specificity: Clearly explain the AI/ML techniques used, the data involved, and any unique technical challenges overcome.

• Focus on Operational Efficiency: When discussing process improvements, explicitly link them to efficiency gains, cost savings, or enhanced client experience, using concrete examples and data.

• Engage Your Audience: Be prepared to discuss your portfolio items interactively, answering detailed questions about your decisions, methodologies, and the outcomes.

📝 Enhancement Note: Interview preparation should focus on demonstrating strategic thinking, deep AI/ML product knowledge, strong leadership, and a clear understanding of how to drive business value through technology. The portfolio is your primary tool for substantiating your experience.

📌 Application Steps

To apply for this operations-aligned AI Product Strategy position:

• Submit your application through the provided Workday link on the Ryan careers page.

• Tailor Your Resume: Customize your resume to highlight specific experience in AI/ML product management, strategic roadmap development, cross-functional team leadership, and driving operational efficiency through technology. Use keywords from the job description, such as "AI Product Strategy," "Machine Learning," "Generative AI," "NLP," and "Operational Efficiency."

• Prepare Your Portfolio: Curate 2-3 impactful case studies showcasing your experience with AI/ML-enabled products, process optimization initiatives, and quantifiable business results. Ensure your portfolio clearly demonstrates your strategic thinking and execution capabilities.

• Research Ryan: Thoroughly understand Ryan's mission, values, and recent industry positioning, particularly their emphasis on becoming a "trusted platform for tax" through technology and expertise.

• Practice Your Narrative: Be ready to articulate your career journey, your approach to AI product strategy, and your key achievements using compelling storytelling techniques, especially during portfolio presentations.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.