Product Manager, UX

📍 Job Overview

Job Title: Product Manager, UX

Company: Everpure

Location: Santa Clara, California, United States

Job Type: Full-time

Category: Product Management / UX

Date Posted: 2026-08-10T23:08:07

Experience Level: 5-10 years

Remote Status: On-site

🚀 Role Summary

• Lead the definition and ownership of the horizontal User Experience (UX) for Artificial Intelligence (AI) across all Everpure products, ensuring a cohesive and intuitive interaction model.

• Standardize agentic user interaction patterns, approval workflows, and safety guardrails across Command Line Interface (CLI), Application Programming Interface (API), and Model Context Protocol (MCP) surfaces.

• Architect robust human-in-the-loop (HITL) trust models and end-to-end supervision/auditability features to balance autonomy with customer infrastructure protection.

• Drive cross-functional product strategy alignment with Engineering, Design, and Product teams to integrate siloed agent surfaces into a unified, trusted enterprise platform.

• Formulate and manage quantitative quality metrics to continuously measure and elevate agent performance, guardrail compliance, and product reliability.

📝 Enhancement Note: While the provided job title is "Product Manager, UX," the core responsibilities and required skills heavily lean into product management for AI-driven systems with a strong emphasis on user experience and safety. This role acts as a crucial bridge between AI capabilities and user interaction, requiring a deep understanding of both technical systems and user-centric design principles. The focus on agentic interaction, guardrails, and HITL models positions this as a highly specialized product management role within the AI/ML product development lifecycle.

📈 Primary Responsibilities

• Define and document the unified agentic UX strategy, encompassing how autonomous agents perceive system state, request approvals, and execute actions across various interfaces (CLI, API, MCP, UI).

• Develop comprehensive interaction patterns, user flows, and visual design guidelines for AI-driven features to ensure consistency and ease of use across the Everpure product suite.

• Design and implement robust safety frameworks and guardrails for AI agent autonomy, ensuring secure and compliant operations within customer infrastructure.

• Collaborate closely with AI, Fusion, and Enterprise Data Cloud teams to translate complex technical capabilities into user-friendly product experiences.

• Establish clear criteria for human intervention and supervision, defining the boundaries of agent autonomy and auditability requirements.

• Develop and track key performance indicators (KPIs) related to agent task success rates, guardrail adherence, user trust signals, and operational efficiency.

• Conduct user research, gather customer feedback, and analyze usage data to iterate on and improve the agentic UX and overall product reliability.

• Lead product roadmap planning and prioritization for AI UX initiatives, aligning with broader company objectives and market demands.

• Facilitate communication and consensus-building among diverse engineering, design, and product stakeholders to ensure successful product development and launch.

• Advocate for customer needs and trust-centric principles throughout the product development lifecycle, ensuring that security, auditability, and operational guardrails are paramount.

📝 Enhancement Note: The responsibilities highlight a significant focus on defining and enforcing safety and trust mechanisms for AI agents, which is a critical aspect of enterprise AI product management. This role requires not just defining features but also establishing frameworks and metrics for their success and safety, indicating a need for deep analytical and strategic thinking beyond typical UX roles.

🎓 Skills & Qualifications

Education: Bachelor's degree in Computer Science, Engineering, Human-Computer Interaction, Product Management, or a related field. Master's degree or equivalent practical experience is a plus.

Experience: 5-10 years of experience in product management, with a significant focus on user experience, AI/ML products, or complex technical systems.

Required Skills:

• Systems Thinking & Product Vision: Proven ability to analyze complex, multi-product architectures and synthesize disparate interfaces (CLI, API, UI, MCP) into a cohesive and actionable product model.

• Hands-On AI & Technical Proficiency: Demonstrated experience in prototyping agent workflows, applying evaluation frameworks for AI capabilities, and utilizing data tools such as SQL and Git for hypothesis testing and data-informed decision-making.

• Cross-Functional Leadership: Strong track record of building consensus, navigating complex cross-team dependencies, and leading technical strategy across engineering, design, and product organizations without direct authority.

• Customer & Trust-Centric Approach: Mastery of jobs-to-be-done principles, with the ability to gather deep customer insights and translate complex enterprise security, auditability, and operational guardrails into tangible product features.

• UX Design Principles: Deep understanding of UX best practices, interaction design, and user-centered design methodologies, specifically as applied to complex technical products and AI interfaces.

• Product Strategy & Roadmapping: Ability to define product vision, set strategic direction, and develop detailed roadmaps that align with business objectives and market opportunities.

• Agile Methodologies: Experience working within agile development environments, including sprint planning, backlog grooming, and iterative product development.

Preferred Skills:

• Experience with data storage technologies and enterprise infrastructure.

• Familiarity with agentic AI concepts, large language models (LLMs), and their application in enterprise settings.

• Experience defining and managing quantitative metrics for AI product performance and user trust.

• Knowledge of security protocols, compliance standards, and auditability requirements in enterprise software.

• Proficiency with modern prototyping tools and design software.

📝 Enhancement Note: The "Hands-On AI & Technical Proficiency" requirement suggests that candidates should be comfortable with technical details and potentially even capable of light scripting or data analysis to validate product hypotheses. The emphasis on "Systems Thinking" and "Cross-Functional Leadership" points to a senior-level role that requires influencing without direct authority.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Case studies demonstrating the successful launch of complex technical products or features with a strong UX component.

• Examples of how you have synthesized fragmented technical capabilities into a unified product experience.

• Documentation showcasing your approach to defining user workflows, interaction patterns, and safety guardrails for AI or complex systems.

• Evidence of your ability to define and track quantitative metrics related to product performance, user adoption, or system reliability.

• Prototypes or mockups that illustrate your understanding of intuitive and trusted AI interaction models. Process Documentation:

• Showcase your methodology for user research, requirements gathering, and translating complex technical requirements into product specifications.

• Provide examples of how you have collaborated with engineering and design teams to define and implement product features, emphasizing process optimization and efficiency.

• Illustrate your approach to defining and iterating on product roadmaps, including prioritization frameworks and stakeholder alignment strategies.

• Include documentation on how you have defined and monitored key product performance indicators (KPIs) and used data to drive product decisions.

📝 Enhancement Note: Given the emphasis on AI and agentic interactions, a portfolio should ideally include examples of how the candidate has approached designing for autonomy, trust, and human oversight in technical systems. Demonstrating an understanding of the "jobs-to-be-done" framework in the context of enterprise AI will be highly valuable.

💵 Compensation & Benefits

Salary Range: For a Product Manager, UX role with 5-10 years of experience in Santa Clara, California, a competitive salary range is estimated to be between $160,000 and $220,000 annually. This estimate considers the high cost of living in the Bay Area, the specialized nature of AI/UX product management, and the general compensation benchmarks for tech roles at established companies like Everpure (a subsidiary of Pentair).

Benefits:

• Innovation & Growth: Opportunities to work on cutting-edge technology and contribute to reshaping the data storage industry, with a supportive environment for professional development.

• Recognition: Named Fortune's Best Workplaces in Technology™, Fortune's Best Workplaces in the Bay Area™, and certified as a Great Place to Work®.

• Work-Life Balance: Flexible time off policies to promote employee well-being.

• Wellness: Access to comprehensive wellness resources to support physical and mental health.

• Team Engagement: Company-sponsored team events designed to foster collaboration and camaraderie.

• Healthcare: Comprehensive health insurance plans.

• Retirement: 401(k) plan with company match.

Working Hours: Standard full-time working hours are expected, likely around 40 hours per week. While the role is on-site, the company culture emphasizes a balance, suggesting flexibility where possible within the on-site requirement, particularly concerning time off and personal wellness.

📝 Enhancement Note: The salary estimate is based on industry benchmarks for Product Managers in the Santa Clara, CA area with 5-10 years of experience, particularly those specializing in technical or AI-focused product roles. The benefits listed are directly pulled from the job description and highlight the company's commitment to employee well-being and a positive work environment.

🎯 Team & Company Context

🏢 Company Culture

Industry: Data Storage / Technology. Everpure operates within the rapidly evolving technology sector, specifically focusing on advanced data storage solutions and the integration of AI into enterprise infrastructure. This market is characterized by intense innovation, a strong emphasis on performance, security, and increasingly, intelligent automation.

Company Size: While not explicitly stated for Everpure, its parent company, Pentair, is a large, established enterprise (over 10,000 employees). This suggests Everpure benefits from the resources and stability of a larger corporation while potentially maintaining a more agile, innovative culture within its specific tech domain. For operations professionals, this can mean access to robust systems and processes, but also the need to navigate larger organizational structures.

Founded: The founding date for Everpure is not specified, but its parent company, Pentair, was founded in 1924. This history provides a foundation of stability and long-term vision, which can be beneficial for product development cycles in complex technology areas.

Team Structure:

• The role requires horizontal collaboration across multiple teams, including Fusion, AI, and Enterprise Data Cloud. This indicates a matrixed or highly collaborative team structure where product managers must influence and align with various functional groups.

• The product manager will likely work closely with engineering leads, UX designers, AI/ML specialists, and other product managers responsible for adjacent product areas.

• The reporting structure is not detailed, but the emphasis on leading without direct authority suggests a culture that values initiative and influence over hierarchical command. Methodology:

• Data-Driven Decision Making: The role emphasizes defining and managing quantitative quality metrics, indicating a strong reliance on data analysis to inform product strategy and performance evaluation for AI agents.

• Systems Integration: A core methodology involves unifying disparate systems (CLI, API, MCP) into a cohesive platform, requiring a systems-thinking approach to architecture and user experience design.

• Agile & Iterative Development: The requirement for prototyping, hypothesis testing, and continuous improvement suggests an agile and iterative product development process.

• Customer-Centricity: A focus on "jobs-to-be-done" and gathering deep customer insights points to a methodology that prioritizes understanding and addressing user needs.

Company Website: pentair.com (as Everpure is part of Pentair)

📝 Enhancement Note: The context of Everpure being part of Pentair is crucial. It implies that while Everpure might operate with a tech-startup-like focus on innovation, it benefits from the resources, stability, and established corporate processes of a large, publicly traded company. For operations roles, this balance is important to understand in terms of tooling, processes, and career growth.

📈 Career & Growth Analysis

Operations Career Level: This role represents a senior-level Product Manager position with a specialized focus on AI and UX. It requires a blend of strategic product vision, deep technical understanding, and strong leadership skills. The scope of responsibility is horizontal, impacting multiple product lines and teams, indicating a significant level of influence and impact on the company's AI strategy.

Reporting Structure: The Product Manager will likely report into a Director or VP of Product Management. However, their day-to-day work will involve extensive collaboration and influence across Engineering, Design, AI/ML, and other Product teams, often requiring them to lead initiatives without direct managerial authority over these groups. This emphasizes a peer-to-peer leadership style.

Operations Impact: The Product Manager's work is central to how customers interact with and trust Everpure's AI-driven products. By defining the UX, safety guardrails, and approval workflows, they directly influence customer adoption, operational efficiency gains, and the overall reliability and security of the enterprise platform. This role has a direct impact on revenue by enabling the successful deployment and scaling of advanced AI capabilities.

Growth Opportunities:

• Specialization in AI Product Management: Deepen expertise in AI UX, agentic systems, and human-in-the-loop design, becoming a recognized authority in this emerging field.

• Leadership Expansion: Potential to move into senior leadership roles, managing larger product portfolios, teams, or strategic initiatives within AI or core product development.

• Cross-Functional Mobility: Opportunity to gain broad exposure to different product areas (Fusion, Enterprise Data Cloud) and potentially transition into roles with broader strategic oversight.

• Industry Influence: Contribute to shaping industry standards for AI interaction and safety through thought leadership and product innovation.

• Mentorship: Develop skills in mentoring junior product managers and guiding cross-functional teams.

📝 Enhancement Note: The "Operations Impact" section is adapted to reflect the Product Manager's influence on business outcomes through product strategy and execution, which is a key aspect of how operations professionals view their contributions. The growth opportunities are framed to appeal to ambitious individuals looking for career progression within the tech product management sphere.

🌐 Work Environment

Office Type: The job explicitly states an "in-office environment" and requires working from the Santa Clara, CA office. This suggests a traditional office setting designed for collaboration and focused work, rather than a remote or hybrid setup.

Office Location(s): Santa Clara, California. This location places the role within the heart of Silicon Valley, offering access to a rich ecosystem of tech talent, innovation, and networking opportunities. The office environment is expected to be professional and conducive to collaborative work.

Workspace Context:

• Collaborative Environment: The on-site requirement indicates a workspace designed to facilitate in-person collaboration, brainstorming, and team synergy, essential for aligning complex cross-functional product strategies.

• Tooling & Technology: As a tech company, the office is likely equipped with modern technology, including robust networking, communication tools, and access to the necessary software and hardware for product development and analysis.

• Team Interaction: Expect frequent face-to-face interactions with engineering, design, AI/ML specialists, and fellow product managers, fostering a strong sense of team cohesion and shared purpose.

Work Schedule: The role is full-time, with a likely standard 40-hour work week. While the primary mode is on-site, the company mentions "flexible time off" and "wellness resources," suggesting an understanding of work-life balance within the structured office environment. Adherence to company policies regarding attendance in the Santa Clara office is expected.

📝 Enhancement Note: The emphasis on "in-office" and specific location in Santa Clara is a key differentiator. This section clarifies what that environment likely entails for a product manager, focusing on the collaborative and technologically rich aspects expected in Silicon Valley.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter or hiring manager will review your application and resume, looking for alignment with the core requirements, especially systems thinking, AI/UX experience, and cross-functional leadership.

• Hiring Manager Interview: A deeper dive into your product management philosophy, experience with AI products, and approach to UX strategy. Expect questions about your systems thinking capabilities and how you handle cross-team dependencies.

• Technical/Product Deep Dive: Interviews with engineering leads, designers, or AI specialists. This stage will likely involve discussing your technical proficiency, ability to prototype, and understanding of data tools (SQL, Git). You may be asked to walk through a technical product you managed.

• Cross-Functional Panel: Interviews with peers from different departments (e.g., AI, Enterprise Data Cloud) to assess your ability to build consensus and lead without direct authority. Questions will focus on collaboration and strategic alignment.

• Portfolio Review Session: A dedicated session to present your portfolio, focusing on case studies that demonstrate your ability to unify complex systems, define AI UX, and implement safety guardrails.

• Final Round: Often with senior leadership (e.g., VP of Product), focusing on strategic thinking, cultural fit, and overall leadership potential.

Portfolio Review Tips:

• Showcase Systems Thinking: Present case studies where you successfully synthesized disparate technical components or interfaces into a cohesive product. Clearly articulate the problem, your solution, and the impact.

• Highlight AI UX & Safety: Include examples of designing for AI interactions, defining trust models, or implementing safety guardrails. Quantify the impact of these features on user trust, adoption, or operational efficiency.

• Demonstrate Cross-Functional Leadership: Use examples where you influenced multiple teams to achieve a common product goal. Detail your communication strategies and how you navigated dependencies.

• Quantify Results: For each case study, present clear, measurable outcomes. Use metrics related to task success rates, guardrail compliance, time-to-human intervention, or customer satisfaction.

• Focus on Process: Explain your product development process, from ideation and research to execution and iteration, emphasizing how you used data and customer insights.

Challenge Preparation:

• AI UX Scenario: Be prepared for a hypothetical scenario where you need to design the UX for a new AI agent or feature. Focus on defining interaction patterns, trust mechanisms, and safety protocols.

• System Synthesis Challenge: You might be asked to outline a strategy for unifying fragmented technical surfaces into a single, coherent user experience.

• Metric Definition Exercise: Prepare to define key metrics for an AI product's success, focusing on both performance and user trust.

📝 Enhancement Note: This section provides actionable advice tailored to a Product Manager role, emphasizing the unique aspects of AI UX and cross-functional leadership. The portfolio tips are specifically designed to address the requirements mentioned in the job description.

🛠 Tools & Technology Stack

Primary Tools:

• Product Management & Collaboration: Jira, Confluence, Asana, Trello, Slack, Microsoft Teams.

• Prototyping & Design: Figma, Sketch, Adobe XD, InVision, Axure RP.

• Data Analysis & Querying: SQL (essential for data validation and hypothesis testing), Python (for scripting, data analysis, or prototyping).

• Version Control: Git (essential for code management and collaboration, indicating comfort with developer workflows).

Analytics & Reporting:

• Product Analytics: Google Analytics, Mixpanel, Amplitude, Pendo.

• Business Intelligence: Tableau, Power BI, Looker (for creating dashboards and reporting on KPIs).

• Experimentation Platforms: Optimizely, VWO (for A/B testing and feature validation).

CRM & Automation:

• CRM: Salesforce, HubSpot (for understanding customer data and sales processes, though less direct for this role, awareness is beneficial).

• Workflow Automation: Zapier, Make (formerly Integromat), or internal automation tools.

• Integration Platforms: Understanding of API integrations and how different systems connect.

📝 Enhancement Note: The inclusion of SQL and Git as required skills strongly suggests that the Product Manager will be expected to work closely with engineering and data teams, potentially performing some level of data analysis or validation themselves. This is a key differentiator from purely UX-focused roles.

👥 Team Culture & Values

Operations Values:

• Innovation & Trailblazing: A culture that encourages critical thinking, challenging the status quo, and pioneering new solutions in the tech industry. Operations professionals are expected to contribute innovative ideas for process improvement and efficiency.

• Growth & Meaningful Contribution: Emphasis on personal and professional growth, providing space for individuals to develop alongside the company and contribute to impactful projects. Operations roles should align with long-term company vision and strategic objectives.

• Collaboration & Ego-Setting Aside: A team-oriented environment where collective success is prioritized over individual ego. Operations professionals are encouraged to collaborate openly and support colleagues for the greater good.

• Trust & Reliability: In the context of AI and enterprise platforms, trust is paramount. Operations roles are expected to uphold the highest standards of reliability, security, and data integrity in all processes and systems.

• Customer Focus: A commitment to understanding and serving customer needs, translating those needs into product features and operational efficiencies that deliver value.

Collaboration Style:

• Horizontal Alignment: The role demands strong collaboration across diverse teams (Engineering, AI, Enterprise Data Cloud, Design), requiring effective communication and consensus-building skills to align roadmaps and strategies.

• Data-Informed Partnerships: Collaboration will be heavily influenced by data analysis and metrics, with operations professionals expected to share insights and work with data to drive decisions.

• Iterative Feedback Loops: A culture that encourages continuous feedback exchange between product, engineering, and UX, allowing for rapid iteration and improvement of processes and products.

• Knowledge Sharing: Openness to sharing best practices, learnings, and challenges across teams to foster collective growth and efficiency.

📝 Enhancement Note: The "Operations Values" are interpreted through the lens of how an operations professional would contribute to and embody these values within a tech company focused on AI and complex systems. The emphasis is on how these values translate into daily work and decision-making for roles supporting GTM or product development.

⚡ Challenges & Growth Opportunities

Challenges:

• Unifying Fragmented Systems: The primary challenge is synthesizing diverse CLI, API, and MCP interfaces into a single, intuitive agentic interaction model, requiring significant systems thinking and strategic product definition.

• Building Trust in AI Autonomy: Establishing robust human-in-the-loop (HITL) models and safety guardrails to ensure customers trust AI agents with critical infrastructure operations.

• Cross-Functional Alignment: Navigating complex organizational dependencies and leading product strategy across multiple, potentially siloed, teams without direct authority.

• Defining and Measuring AI UX Success: Developing effective quantitative metrics to evaluate the performance, reliability, and trustworthiness of AI-driven user experiences.

• Rapidly Evolving AI Landscape: Keeping pace with the fast-changing AI technology and ensuring product strategies remain relevant and competitive.

Learning & Development Opportunities:

• AI Product Specialization: Deepen expertise in AI product management, focusing on agentic systems, LLMs, and human-AI interaction design.

• Enterprise Architecture & Systems Integration: Gain in-depth knowledge of complex enterprise data storage architectures and how to integrate AI capabilities seamlessly.

• Leadership & Influence: Develop advanced skills in influencing stakeholders, managing cross-functional teams, and driving product vision in a large organization.

• Data Science & Analytics: Enhance understanding and application of data analysis techniques, SQL, and metrics frameworks for AI product evaluation.

• Industry Trends: Stay at the forefront of AI, UX, and data storage advancements through conferences, training, and continuous learning.

📝 Enhancement Note: Challenges are framed to be specific to the role's requirements, such as unifying systems and building trust in AI. Growth opportunities are designed to show a clear path for career advancement and skill development within this specialized area of product management.

💡 Interview Preparation

Strategy Questions:

• AI UX Strategy: "How would you approach defining the horizontal UX for AI across multiple product lines like CLI, API, and MCP? What are the key considerations for ensuring a unified and trusted experience?" (Prepare to discuss systems thinking, interaction patterns, and safety guardrails.)

• Building Trust in AI: "Describe your methodology for architecting human-in-the-loop (HITL) trust models for autonomous agents. How do you balance automation with necessary human oversight and auditability?" (Prepare to discuss risk assessment, intervention points, and user control.)

• Cross-Functional Leadership: "Give an example of a time you had to lead a complex product initiative across multiple engineering and product teams without direct authority. How did you build consensus and navigate dependencies?" (Prepare to use the STAR method and highlight communication and influence strategies.)

Company & Culture Questions:

• Everpure's AI Vision: "Based on your understanding of Everpure and the data storage industry, where do you see the biggest opportunities for AI-driven UX innovation?" (Research Pentair/Everpure's current tech stack and market position.)

• Collaboration Style: "How do you foster collaboration and alignment between product, engineering, and design teams, especially when dealing with cutting-edge technologies like AI?" (Discuss your approach to team dynamics and feedback.)

• Measuring Success: "How would you define and measure success for a product focused on agentic AI UX, particularly in terms of trust, reliability, and operational velocity?" (Prepare to discuss specific KPIs and evaluation frameworks.)

Portfolio Presentation Strategy:

• Structure Your Narrative: For each case study, clearly articulate the problem, your role, the solution you designed, the process you followed, and the quantifiable results achieved.

• Focus on Systems Integration: Emphasize how you took fragmented components or complex technical requirements and unified them into a coherent product experience.

• Showcase AI UX & Safety Design: Dedicate specific slides or sections to how you addressed AI interaction patterns, user trust, and safety guardrails. Use visuals and mockups effectively.

• Quantify Impact: Present metrics related to user adoption, efficiency gains, error reduction, or improved customer trust. Explain the ROI or business value generated.

• Be Prepared for Deep Dives: Anticipate detailed questions about your decision-making process, technical challenges, and stakeholder management.

📝 Enhancement Note: These interview questions are crafted to probe the specific skills and experiences highlighted in the job description, particularly systems thinking, AI/UX, and cross-functional leadership. The portfolio advice is geared towards demonstrating these capabilities effectively.

📌 Application Steps

To apply for this Product Manager, UX position:

• Submit your application through the provided link on the Greenhouse platform.

• Customize Your Resume: Tailor your resume to highlight your experience in product management, UX design for technical products, AI/ML, systems thinking, and cross-functional leadership. Use keywords from the job description, such as "agentic interaction," "guardrails," "human-in-the-loop," and "systems thinking."

• Prepare Your Portfolio: Curate a portfolio that showcases 2-3 strong case studies demonstrating your ability to define and launch complex technical products, especially those involving AI or intricate system integrations. Focus on projects where you synthesized fragmented interfaces, designed for user trust, and implemented safety mechanisms.

• Practice Your Presentation: Rehearse your portfolio presentation, ensuring you can clearly articulate the problem, your solution, the process, and the quantifiable outcomes for each case study. Be ready to discuss your approach to AI UX and cross-functional collaboration.

• Research Everpure/Pentair: Understand the company's mission, its position in the data storage market, and any publicly available information about its AI initiatives or product strategy. This will help you tailor your responses and demonstrate genuine interest.

⚠️ 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.

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