UX-AX Operations Manager

📍 Job Overview

Job Title: UX-AX Operations Manager

Company: SecurityScorecard

Location: Austin, TX (Hybrid)

Job Type: Full-Time

Category: UX/Design Operations & Program Management

Date Posted: 2026-09-10T22:59:18

Experience Level: 5-10 Years

Remote Status: Hybrid

🚀 Role Summary

• Spearhead the creation and management of a novel AI-first design operating model, integrating AI agents and human designers within a pod-based structure.

• Drive the adoption and refinement of advanced AI-enabled design practices, focusing on interactive prototyping directly from live codebases and design systems.

• Establish robust processes for design-to-engineering handoffs, ensuring accuracy and buildability of interaction details to bridge the gap between design and implementation.

• Define and operationalize Agent Experience (AX) frameworks, including guardrails, permissions, and escalation paths, to ensure safe and reliable AI agent operation.

• Champion the development of metrics and KPIs to measure and improve prototyping velocity, handoff quality, cycle time, and AI tooling adoption within the design organization.

📝 Enhancement Note: This role is explicitly positioned at the intersection of traditional UX Operations and the emerging field of Agent Experience (AX) Operations, reflecting a significant shift towards AI-driven product development within SecurityScorecard's Product & Design organization. The emphasis on "AI-first workflows" and "agent experience" suggests a forward-thinking approach to design operations.

📈 Primary Responsibilities

• Design and implement the operating model for a pod-based design organization, embedding designers within cross-functional product teams for continuous ownership and specialized product area focus.

• Drive the adoption of AI-first design practices, enabling designers to prototype directly from the live codebase and design system using tools like Claude, and deliver working interaction details rather than static mockups.

• Own and optimize the design-to-engineering handoff process, ensuring that critical interaction details are accurately captured, communicated, and are immediately buildable by engineering teams.

• Manage Agent Experience (AX) operations, including the coordination of AI agent evaluations, defining operational guardrails, managing agent primitives (permissions, tool access, escalation paths), and implementing failure handling mechanisms.

• Define the strategic handoff points and coordination mechanisms between human designers and AI agents, as well as between multiple AI agents, to foster intentional collaboration.

• Establish, track, and report on key performance indicators (KPIs) that demonstrate increased velocity and improved overall experience, such as prototyping speed, handoff quality, development cycle time, agent evaluation coverage, and AI tool adoption rates.

• Lead planning, prioritization, and cross-pod cadence meetings, facilitating shared or infrastructure-level design initiatives that span across multiple product lines.

• Support customer co-build and live-prototyping sessions, ensuring that learnings are scaled effectively across similar customer segments rather than remaining isolated.

• Collaborate with the UX Director and pod leads to onboard new designers into the AI-first workflow, enhancing their fluency with tooling, design judgment, and specialized agentic design skills.

• Act as connective tissue within a flat organizational structure, coordinating standards and best practices across teams without direct management oversight, fostering a collaborative and unified design approach.

📝 Enhancement Note: The responsibilities highlight a shift from traditional design operations to a more integrated, technologically advanced role. The emphasis on "pod-based ownership," "AI-first design," and "agent experience" indicates a need for an operations leader who can navigate complex, evolving workflows and drive standardization in a cutting-edge environment.

🎓 Skills & Qualifications

Education: While no specific degree is mandated, a Bachelor's degree in Design, Human-Computer Interaction, Computer Science, Business Operations, or a related field is often preferred for roles of this nature, demonstrating a foundational understanding of design principles and operational frameworks.

Experience: Minimum of 5 years of progressive experience in Design Operations, UX Operations, Program Management, or a closely related operational discipline, with a strong preference for B2B SaaS environments.

Required Skills:

• 5+ years in design/UX operations, program management, or a similar operating role, with a strong preference for experience within B2B SaaS companies.

• Direct, hands-on experience running AI-enabled design workflows, including designers working from live codebases and design systems to produce interactive prototypes and implementation-ready specifications for engineering.

• A well-defined perspective on AI-first design-to-engineering workflows, derived from practical application and understanding of tooling, process, and associated tradeoffs.

• Demonstrated exposure to agent evaluation, defining operational guardrails, or designing for agent-facing products, including experience building evaluations, defining agent permission models, or designing product interfaces for AI agents.

• Proven track record of successfully transitioning from centralized, ticket-based intake models to embedded, pod-based ownership structures, or the ability to articulate a clear and credible plan for such a transition.

• Proficiency in operating effectively within a flat organizational structure, driving adherence to standards across teams without direct managerial authority.

• Strong cross-functional operating skills, capable of leading planning and prioritization cadences involving design, product, engineering, and security teams without introducing bureaucratic bottlenecks.

• A pronounced bias towards rapid, iterative prototyping and disposable design work over highly invested, potentially over-engineered solutions. Preferred Skills:

• Prior background in cybersecurity, threat intelligence, or other security-adjacent B2B SaaS product domains.

• Experience in establishing or scaling an AI-first product development practice within a company undergoing a similar technological transition, such as rolling out org-wide agentic coding or design tools.

• Experience facilitating customer co-build sessions or live-prototyping workshops with enterprise-level clients.

• Experience in building or operating multi-agent systems, or in defining evaluation frameworks for AI agent behavior in production environments.

📝 Enhancement Note: The qualifications strongly emphasize practical, hands-on experience with AI-driven workflows, not just theoretical knowledge. The preference for B2B SaaS and cybersecurity backgrounds, combined with the specific mention of "Claude," suggests the company is looking for someone who understands the nuances of enterprise product development and advanced AI tooling. The requirement for a "point of view" on AI-first workflows indicates a need for a strategic thinker, not just an executor.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrate successful implementation of operational models that shifted from centralized intake to embedded, pod-based team structures, showcasing efficiency gains and improved collaboration.

• Provide case studies or examples of how you've standardized and improved the quality and efficiency of design-to-engineering handoffs, particularly in complex B2B SaaS environments.

• Showcase experience with the implementation and adoption of AI-powered design tools and workflows, detailing the processes, challenges, and outcomes achieved.

• Present evidence of designing, implementing, or managing operational frameworks for AI agents, including examples of guardrails, permissions, and evaluation metrics.

• Include examples of defining and tracking key operational metrics (e.g., prototyping velocity, cycle time, AI tool adoption) and demonstrating their impact on organizational performance. Process Documentation:

• Detailed documentation of workflow design and optimization phases for operational processes, with a focus on streamlining the product development lifecycle.

• Evidence of process implementation and automation methods used to enhance efficiency and scalability within design and product organizations.

• Examples of measurement and performance analysis techniques applied to operational processes, highlighting how data was used to drive improvements and inform strategy.

📝 Enhancement Note: For this role, the portfolio should not just showcase design outputs but operational excellence. Applicants should be prepared to present concrete examples of process design, implementation, and impact, particularly concerning AI integration and operational model shifts. The focus is on the how of operations, not just the what.

💵 Compensation & Benefits

Salary Range: The estimated total compensation range for this position is $185,000 - $230,000 annually. This range includes base salary and potential performance-based incentive compensation. The final compensation will be determined based on factors such as the candidate's skills, qualifications, experience, and the company's internal affordability assessments.

Benefits:

• Competitive salary and performance-based incentive compensation.

• Stock options providing an opportunity for equity ownership in a growing company.

• Comprehensive health benefits packages.

• Unlimited Paid Time Off (PTO), reflecting a trust in employee autonomy and work-life balance.

• Generous parental leave policies to support new parents.

• Tuition reimbursement programs to encourage continuous learning and professional development.

• Other benefits as detailed by the company, contributing to overall employee well-being and professional growth.

Working Hours: The standard working hours for this role are approximately 40 hours per week. However, given the hybrid nature and the operational demands of a dynamic tech environment, flexibility may be expected to meet project deadlines and cross-functional collaboration needs.

📝 Enhancement Note: The salary range provided is specific to the US market and likely reflects the high cost of living and competitive tech talent market in Austin, TX. The benefits package is robust, emphasizing well-being and professional growth, which are key attractors for experienced operations professionals. The inclusion of stock options and performance-based incentives aligns with typical compensation structures for managerial roles in growth-stage tech companies.

🎯 Team & Company Context

🏢 Company Culture

Industry: Cybersecurity, specifically focusing on cybersecurity ratings and risk management. SecurityScorecard operates within the rapidly evolving RegTech and FinTech sectors, providing essential data and analytics for risk assessment and compliance.

Company Size: SecurityScorecard is a well-established scale-up, indicated by its funding rounds and global operations. It is recognized as a significant player in the cybersecurity market. The company size implies a dynamic environment with resources for innovation but still retaining agility.

Founded: 2013. Founded by security and risk experts, SecurityScorecard has a strong foundation in its core domain. Its history reflects a journey from startup to market leader, with a focus on continuous innovation, particularly in AI.

Team Structure:

• The Product & Design organization is undergoing a transformation, moving towards an "AI-first" model with a pod-based structure. Designers are embedded directly into cross-functional product pods.

• There is no traditional management layer between designers and the UX Director; the role of the UX-AX Operations Manager is to coordinate standards and enable these teams, rather than manage headcount.

• Collaboration is expected to be highly cross-functional, involving design, product management, engineering, and security teams to ensure seamless integration of AI capabilities and user experiences. Methodology:

• Data-Driven Operations: Emphasis on defining and tracking metrics to prove organizational velocity and improvement in AI-first workflows and agent experience.

• AI-First Development: A core methodology shift where AI agents work alongside human designers, and designers prototype directly against live codebases using AI tools.

• Embedded Ownership: Designers are embedded within product pods, fostering deep ownership and continuity for specific product areas, moving away from centralized ticket queues.

• Iterative Prototyping: A bias towards rapid, disposable prototyping to accelerate learning and reduce time-to-market for new features and AI integrations.

Company Website: https://securityscorecard.com/

📝 Enhancement Note: SecurityScorecard's culture is characterized by innovation, particularly in adopting AI. The operational structure is moving towards a more agile, decentralized "pod-based" model, requiring strong operational leadership to maintain alignment and efficiency without traditional hierarchical management. This is a key differentiator for operations professionals to understand.

📈 Career & Growth Analysis

Operations Career Level: This role is classified as a Managerial/Lead Operations position, focusing on specialized UX/Design Operations with a significant AI and Agent Experience component. It requires substantial experience to define and implement new operational paradigms.

Reporting Structure: The UX-AX Operations Manager will report to the UX Director. While there is no direct management layer between designers and the Director, this role acts as a crucial facilitator and standard-setter, coordinating efforts across multiple embedded designers and product pods.

Operations Impact: The Operations Manager will have a direct impact on the speed, quality, and efficiency of product development within the Product & Design organization. By optimizing AI-first workflows, improving handoffs, and ensuring effective agent operations, this role will directly contribute to faster innovation cycles, enhanced user and agent experiences, and ultimately, the company's ability to deliver cutting-edge cybersecurity solutions.

Growth Opportunities:

• Specialization in Emerging Fields: Opportunity to become a recognized expert in the nascent field of AI-first design operations and Agent Experience (AX) operations, a highly sought-after skill set.

• Strategic Influence: Play a key role in shaping the future of product development at SecurityScorecard by defining and scaling new operational models and AI integration strategies.

• Leadership Development: Potential to grow into more senior operational leadership roles within Product & Design or broader GTM Operations, especially as the company continues its AI-first transformation.

• Cross-Functional Exposure: Gain deep insights and build strong relationships across Product, Engineering, and Security, broadening professional networks and understanding of complex B2B SaaS products.

📝 Enhancement Note: This role offers a unique opportunity to shape a new operational domain (AX Operations) within a leading cybersecurity company. The growth potential lies in becoming a pioneer in AI-driven product development operations, with clear pathways for strategic influence and advanced leadership within the organization.

🌐 Work Environment

Office Type: Hybrid work model, requiring some in-office presence in Austin, TX, for collaboration and team cohesion, while allowing for remote work flexibility. This suggests a balance between in-person interaction and individual focus time.

Office Location(s): Austin, TX. This location is a major tech hub, offering a vibrant ecosystem for talent and innovation. Specific office details would be provided upon inquiry or during the interview process.

Workspace Context:

• The work environment is described as "pod-based" and "flat," emphasizing collaboration and direct communication over hierarchical structures. Designers are embedded within cross-functional pods.

• The role requires operating with AI tools and potentially designing interfaces for AI agents, suggesting a tech-forward workspace equipped with the necessary software and infrastructure.

• Expect significant interaction with product managers, engineers, and UX leadership, fostering a dynamic and collaborative atmosphere focused on rapid iteration and problem-solving.

Work Schedule: While a standard 40-hour work week is implied, the hybrid and fast-paced nature of a growing tech company, especially one undergoing significant AI transformation, may necessitate flexibility to accommodate project timelines, cross-functional meetings, and critical operational needs.

📝 Enhancement Note: The hybrid work arrangement in a key tech hub like Austin, coupled with a collaborative, pod-based structure, indicates a modern work environment. The emphasis on AI tooling and cross-functional interaction suggests a dynamic and intellectually stimulating atmosphere for operations professionals.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter or hiring manager will likely conduct an initial phone screen to assess general qualifications, experience, and cultural fit. Be prepared to discuss your background in UX Operations and AI-driven workflows.

• Hiring Manager Interview: Deeper dive into your experience with AI-first design, AX operations, and operating models. Expect questions about how you've driven change, managed processes without direct authority, and your perspective on AI in design.

• Cross-Functional Interviews: Meetings with UX Director, pod leads, and potentially engineering/product managers. These will focus on your ability to collaborate, run planning cadences, and understand technical constraints and opportunities.

• Portfolio Review/Case Study: A key component will be presenting your portfolio, focusing on specific operational achievements. Be ready to walk through case studies demonstrating your ability to implement operational models, improve handoffs, and manage AI integration.

• Final Interview: May involve senior leadership to assess strategic thinking, leadership potential, and overall fit with the company's vision and culture.

Portfolio Review Tips:

• Focus on Operations, Not Just Design: Showcase your ability to build and optimize processes, systems, and workflows. Highlight metrics and quantifiable outcomes related to efficiency, velocity, and quality.

• AI & AX Case Studies: Dedicate specific sections to your experience with AI-enabled design and Agent Experience operations. Detail the challenges, your approach, the tools used, and the measurable impact.

• Process Transition Examples: Clearly articulate instances where you've transitioned teams or processes (e.g., from centralized to embedded models) and the operational strategies employed.

• Metrics and ROI: For each case study, present clear, data-driven results. Quantify improvements in cycle time, prototyping velocity, handoff accuracy, or AI tool adoption. Demonstrate the ROI of your operational initiatives.

• Tailor to SecurityScorecard: Research SecurityScorecard's product and mission. Be prepared to discuss how your operational experience can directly support their AI-first transformation and cybersecurity focus.

Challenge Preparation:

• Operational Model Design: You may be asked to outline how you would design or refine the operating model for a specific AI-first product pod.

• Process Improvement Scenario: Present a hypothetical scenario where design-to-engineering handoffs are breaking down and ask how you would diagnose and fix it.

• AI Guardrail Definition: You might be asked to conceptualize guardrails or evaluation criteria for an AI agent performing a specific task within the SecurityScorecard product.

• Metrics Definition: Be prepared to propose key metrics for evaluating the success of AI-first design practices or AX operations.

📝 Enhancement Note: The interview process is designed to assess not only operational expertise but also strategic thinking regarding AI integration and adaptability to a flat, collaborative structure. A strong portfolio showcasing tangible operational improvements, particularly in AI contexts, will be crucial.

🛠 Tools & Technology Stack

Primary Tools:

• AI Design Tools: Experience with or ability to quickly master AI tools like Claude (or similar LLMs) for design prototyping and potentially code interaction.

• Design Systems Tools: Proficiency with tools used for managing and leveraging design systems (e.g., Figma, Sketch, Zeroheight, Storybook).

• Prototyping Tools: Familiarity with tools that support interactive prototyping and potentially direct integration with live codebases.

Analytics & Reporting:

• Metrics & Dashboard Tools: Experience with tools for defining, tracking, and visualizing operational KPIs (e.g., Tableau, Looker, Power BI, or internal dashboarding solutions).

• Product Analytics: Familiarity with platforms that track user behavior and product adoption, which can inform operational improvements.

CRM & Automation:

• Project Management Software: Proficiency in tools like Jira, Asana, Trello, or Monday.com for managing workflows, tracking tasks, and facilitating cross-functional collaboration.

• Collaboration Platforms: Deep familiarity with tools like Slack, Microsoft Teams, and Confluence for communication, documentation, and knowledge sharing.

• Design Collaboration Tools: Experience with platforms that facilitate collaborative design reviews and feedback loops.

📝 Enhancement Note: The technology stack is heavily influenced by the "AI-first" mandate. A candidate's ability to adapt to and leverage AI-powered design and development tools, alongside traditional design operations and project management software, will be critical. Familiarity with tools that enable direct interaction with codebases and interactive prototyping is a significant plus.

👥 Team Culture & Values

Operations Values:

• Innovation & AI-Forward Thinking: A strong commitment to embracing and driving AI technologies within product development, encouraging experimentation and forward-thinking solutions.

• Collaboration & Transparency: A culture that values open communication, cross-functional teamwork, and transparency in processes and decision-making, particularly within a flat organizational structure.

• Data-Driven Decision Making: Reliance on metrics and data to inform operational strategies, measure success, and drive continuous improvement across all design and development processes.

• Efficiency & Velocity: A focus on optimizing workflows and processes to accelerate product development cycles and deliver value to customers rapidly, characterized by a bias towards action and iterative progress.

• Ownership & Accountability: Empowering teams and individuals to take ownership of their product areas and operational processes, fostering a sense of responsibility and accountability for outcomes.

Collaboration Style:

• Embedded & Cross-Functional: Collaboration occurs primarily within cross-functional product pods, where designers work intimately with product managers and engineers.

• Standardization through Coordination: The role emphasizes coordinating standards and best practices across multiple teams without direct management, requiring strong influencing and communication skills.

• Knowledge Sharing: A culture that encourages sharing learnings, best practices, and insights across the design team and broader organization to foster collective growth and alignment.

📝 Enhancement Note: The company culture appears to be highly dynamic, leaning into innovation (especially AI) and a collaborative, results-oriented environment. Professionals who thrive in agile settings, can influence without direct authority, and are excited by the prospect of shaping new operational paradigms will find this a compelling culture.

⚡ Challenges & Growth Opportunities

Challenges:

• Navigating a New Paradigm: The primary challenge will be establishing and refining operational models for an emerging AI-first design and AX environment, which requires adaptability and continuous learning.

• Driving Adoption: Convincing and enabling designers to shift from traditional workflows to AI-assisted, code-integrated prototyping and design processes.

• Defining AI Agent Operations: Establishing clear, safe, and effective operational frameworks for AI agents, including guardrails, permissions, and human-agent handoffs, in a production environment.

• Maintaining Alignment in a Flat Org: Ensuring consistency in standards, processes, and quality across multiple embedded design pods without a traditional hierarchical management structure.

• Measuring Impact: Developing robust metrics and attribution models to clearly demonstrate the value and ROI of AI-first initiatives and operational improvements.

Learning & Development Opportunities:

• Pioneering AX Operations: Become a leader in the field of Agent Experience (AX) operations, a rapidly growing and critical area of AI product development.

• AI Tool Mastery: Gain deep expertise in leveraging advanced AI tools like Claude for design and product development workflows.

• Strategic Operational Design: Develop advanced skills in designing and implementing scalable operational models for cutting-edge technology adoption.

• Cross-Functional Leadership: Enhance leadership and influencing skills by working closely with diverse teams (Product, Engineering, Security) in a highly collaborative environment.

• Industry Trends: Stay at the forefront of AI, cybersecurity, and product development trends through practical application and company-supported learning initiatives.

📝 Enhancement Note: The challenges presented are significant but are directly tied to growth opportunities. Success in this role will position the candidate as an expert in a future-forward domain, offering substantial career advancement potential.

💡 Interview Preparation

Strategy Questions:

• "Describe your experience in transitioning a design team from a centralized intake model to an embedded, pod-based structure. What were the key operational changes you implemented, and how did you measure success?" (Focus on process, metrics, and change management.)

• "How would you approach defining and enforcing AI guardrails for agent operations within a product like SecurityScorecard? What key metrics would you track to ensure safety and effectiveness?" (Focus on risk mitigation, operational frameworks, and data-driven evaluation.)

• "Walk me through your process for optimizing design-to-engineering handoffs, especially when dealing with complex interactions and new technologies like AI-assisted prototyping. What are the most common failure points, and how do you address them?" (Focus on process detail, problem-solving, and technical understanding.) Company & Culture Questions:

• "Based on your understanding of SecurityScorecard's AI-first transformation, what do you see as the biggest operational opportunities and challenges for the UX/AX team?" (Demonstrate research and strategic thinking about their specific context.)

• "How do you foster collaboration and drive adoption of new standards in a flat organizational structure where you don't have direct management authority over most stakeholders?" (Focus on influencing, communication, and relationship-building skills.)

• "How do you measure the impact and ROI of design operations initiatives, particularly those related to AI adoption and workflow efficiency?" (Focus on data analysis, metrics, and value articulation.) Portfolio Presentation Strategy:

• Structure for Impact: Organize your portfolio to highlight operational achievements. Use a STAR (Situation, Task, Action, Result) or similar method for each case study, emphasizing quantifiable results.

• AI & AX Focus: Dedicate a significant portion of your presentation to your experience with AI-driven design and AX operations. Be prepared to demo or explain specific workflows you've built or improved.

• Metrics & Data Visualization: Clearly present the metrics you've used to track performance and demonstrate improvements. Use charts and graphs where appropriate to make data digestible.

• Role-Play Scenarios: Be ready to engage in role-playing exercises, such as presenting a new operational process to a group of designers or engineers, or discussing how to resolve a conflict in prioritization between product pods.

• Company Relevance: Connect your experience directly to SecurityScorecard's business and their AI-first strategy. Show that you understand their mission and how operations can support it.

📝 Enhancement Note: Interview preparation should heavily focus on demonstrating practical experience with AI integration in operational contexts, change management, and data-driven performance measurement. The ability to articulate a strategic vision for AX operations and influence stakeholders will be key.

📌 Application Steps

To apply for this operations position:

• Submit your application through the SecurityScorecard careers portal via the provided Greenhouse link.

• Customize Your Resume: Tailor your resume to highlight keywords and experiences directly related to UX Operations, AX Operations, AI-first workflows, program management, B2B SaaS, and cross-functional leadership. Quantify your achievements with metrics whenever possible.

• Prepare Your Portfolio: Curate a portfolio that showcases your operational achievements. Focus on case studies demonstrating process optimization, AI integration, successful handoffs, and measurable improvements in efficiency and velocity.

• Research SecurityScorecard: Deeply understand the company's mission, product, and their current AI-first transformation. Be prepared to discuss how your operational expertise can contribute to their specific goals.

• Practice Your Narrative: Rehearse your responses to common interview questions, focusing on articulating your experience clearly and concisely, especially regarding your operational strategies and impact. Be ready to present your portfolio with confidence.

⚠️ 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.