Staff AI Product Designer

📍 Job Overview

Job Title: Staff AI Product Designer

Company: AiDASH, Inc.

Location: Palo Alto, California, United States

Job Type: Full-Time

Category: Product Design / User Experience (AI-Focused)

Date Posted: April 28, 2026

Experience Level: 6+ Years

Remote Status: On-site

🚀 Role Summary

• Define and champion the standard for AI-augmented design practices across the organization, fundamentally rewiring design workflows around AI tools for daily use.

• Leverage AI tools for accelerated ideation, research synthesis, rapid prototyping, visual exploration, and the creation of production-ready design outputs.

• Collaborate closely with cross-functional teams (Product, Engineering, Research) to deliver comprehensive design solutions, including journey maps, service blueprints, roadmaps, prototypes, and design systems.

• Apply a diverse range of user research methodologies, augmented by AI for efficient data transcription, pattern identification, and insight generation.

📝 Enhancement Note: This role is distinctly focused on the integration and leadership of AI within the product design lifecycle, positioning the candidate as a key driver of technological transformation in design processes. The emphasis is on practical, daily application of AI, not just occasional use.

📈 Primary Responsibilities

• Drive Technology Transformation: Lead the design and implementation of AI-augmented design solutions, significantly accelerating the ideation-to-delivery timeline from days to hours using tools like Galileo AI, Uizard, Relume, or v0.

• Strategic Design Collaboration: Partner with product managers, engineers, and other stakeholders to produce high-quality design deliverables, ensuring alignment with business objectives and user needs.

• AI-Enhanced User Research: Employ a variety of user research methods (context analysis, interviews, user testing) and strategically integrate AI for tasks such as transcribing interviews, clustering qualitative data, and accelerating insight generation.

• Production-Ready AI Design: Utilize generative AI for mood boards, visual explorations, icon generation, and creating design variations at scale, refining AI-generated assets to meet production quality standards.

• Design System Evolution: Contribute to and scale AI-augmented design systems, leveraging AI for tasks like generating responsive variants, batch asset resizing, and automated content population to ensure consistency and efficiency.

• AI Adoption Evangelism: Act as a champion for AI adoption within the design and product teams, establishing best practices, standards, and playbooks for AI-assisted design.

• Project Management & Communication: Proactively manage project scope, identify and mitigate risks, and provide clear, consistent communication and updates to all stakeholders throughout the project lifecycle.

📝 Enhancement Note: The responsibilities highlight a blend of hands-on design execution, strategic thinking about AI's role in design, and leadership in driving adoption. The emphasis on accelerating delivery timelines and scaling design systems through AI is a critical aspect of this role.

🎓 Skills & Qualifications

Education: Bachelor’s degree in Design, Human-Computer Interaction (HCI), a related field, or equivalent practical experience.

Experience: 6+ years of experience in UX/product design, with a strong portfolio showcasing applied design principles across web and mobile platforms.

Required Skills:

• Demonstrated, hands-on proficiency with AI design tools (e.g., Galileo AI, Uizard, Relume, v0, Framer AI, Figma AI features). Portfolio must include examples of AI-assisted work.

• Proficiency in core design tools, with Figma being mandatory.

• Experience with at least two AI-powered design or prototyping tools.

• Strong understanding of AI's capabilities and limitations within a design context, knowing when to apply AI and when human craft is essential.

• Excellent verbal and written communication skills, with the ability to craft and deliver engaging presentations.

• Proven success in collaborating effectively with cross-functional teams in fast-paced startup environments.

Preferred Skills:

• Familiarity with generative image tools such as Midjourney, DALL-E, Stable Diffusion, or Adobe Firefly for design exploration and asset creation.

• Passion for climate tech, sustainability, or infrastructure modernization.

• Experience with AI-driven research synthesis and data analysis techniques.

• Deep understanding of design system architecture and scaling methodologies.

📝 Enhancement Note: The requirement for a strong portfolio demonstrating AI tool usage is paramount. The distinction between "required" and "preferred" skills emphasizes the innovative and forward-thinking nature of this role, specifically seeking individuals who are not just users but pioneers of AI in design.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• AI Integration Showcase: At least two detailed case studies explicitly demonstrating the strategic use of AI tools within the design process.

• Workflow Acceleration & Improvement: Before-and-after examples illustrating how AI accelerated workflows or led to tangible improvements in design quality or efficiency.

• AI Tooling & Prompting: Clear documentation of the AI tools used, the methodologies for crafting effective prompts, and the process for refining AI-generated outputs.

• Value Articulation: Clear articulation of where AI added significant value versus where human judgment, craft, and strategic decision-making were critical.

• Iterative Process Documentation: Showcase the messy, iterative process of integrating AI, demonstrating a willingness to experiment and learn.

Process Documentation:

• Evidence of documenting design processes, workflows, and AI integration methodologies.

• Ability to create journey maps, service blueprints, and roadmaps that reflect AI-augmented insights and accelerated timelines.

• Experience in establishing and scaling design systems, potentially leveraging AI for component generation or documentation updates.

📝 Enhancement Note: The portfolio requirements are highly specific, focusing on the practical application and strategic integration of AI. Candidates are expected to demonstrate not just proficiency with AI tools but also a thoughtful understanding of their impact and limitations within the design lifecycle.

💵 Compensation & Benefits

Salary Range: $190,000 - $230,000 per year (base pay).

Benefits:

• Comprehensive Medical, Dental, and Vision Coverage: 100% employer-paid for employees and 80% for spouses and children.

• Health Reimbursement Account (HRA): Fully funded by AiDASH to cover medical deductibles.

• 401(k) Plan: Available after three months of employment (no company match currently offered).

• Parental Leave: 16 weeks for primary caregivers and 4 weeks for secondary caregivers.

• Generous Vacation Policy: Accrue 20 vacation days per year, plus one additional flex holiday.

• Winter Break: Paid time off from December 25th to January 1st.

Working Hours: Standard 40 hours per week, with an expectation of on-site presence in Palo Alto, California.

📝 Enhancement Note: The salary range is competitive for a Staff-level AI Product Designer in the Palo Alto/Bay Area tech market, reflecting the specialized skills and experience required. The benefits package is robust, with a notable emphasis on comprehensive health coverage and generous paid time off, including a winter break. The absence of a 401(k) match is typical for some high-growth startups but should be noted.

🎯 Team & Company Context

🏢 Company Culture

Industry: Enterprise AI, Vegetation Risk Intelligence for Electric Utilities. AiDASH leverages proprietary VegetationAI™ technology and a SatelliteFirst approach to provide remote grid inspection and monitoring.

Company Size: Series C growth company, recognized by Forbes as one of "America's Best Startup Employers" and by Time Magazine as one of "America's Top GreenTech Companies 2024". Deloitte Technology Fast 500 ranked them highly for 2024. This indicates a dynamic, rapidly scaling environment with significant market traction and investor backing.

Founded: While the founding date isn't explicitly stated, its Series C funding and recognition suggest a company that has moved beyond its early startup phase into a growth trajectory, likely founded in the last 5-10 years.

Team Structure:

• The role operates within a Product Design function, likely collaborating closely with Product Management, Engineering, and potentially Data Science/AI teams.

• As a "Staff" level designer, this individual will be expected to operate with a high degree of autonomy and influence, potentially mentoring junior designers.

Methodology:

• Data-Driven Innovation: Emphasizes using data (from satellites, grid inspections) and AI to drive product development and client solutions.

• Prevention-First Strategy: Focuses on mitigating risks (wildfire, storm impacts) through proactive intelligence and monitoring.

• AI Integration: Actively incorporates AI into its core technology (VegetationAI™) and is now seeking to embed AI into its design processes as well.

Company Website: https://www.aidash.com

📝 Enhancement Note: AiDASH operates in a critical and growing sector (utility infrastructure and climate tech) with a strong emphasis on AI and data. The company culture is likely fast-paced, innovative, and focused on impact, as evidenced by its rapid growth, investor profile, and industry recognition. The "Securing Tomorrow!" slogan suggests a mission-driven organization.

📈 Career & Growth Analysis

Operations Career Level: Staff AI Product Designer. This is a senior individual contributor role, implying significant autonomy, strategic input, and the potential to influence design direction and best practices across the company. It's a step beyond senior designer, often involving mentorship, thought leadership, and leading complex initiatives.

Reporting Structure: While not explicitly stated, a Staff Product Designer typically reports to a Design Lead, Head of Product Design, or potentially a Director of Product. They will work closely with Product Managers and Engineering Leads.

Operations Impact: The role's impact is significant, directly contributing to the development of AI-driven features and user experiences that enhance the effectiveness and efficiency of AiDASH's vegetation risk intelligence platform. By defining AI-augmented design standards, this role will shape how the company's products are perceived and utilized by enterprise clients, ultimately impacting reliability, cost reduction, and risk mitigation for utilities.

Growth Opportunities:

• Technical Specialization: Deepen expertise in AI for design, becoming a recognized leader in prompt engineering, AI tool integration, and generative design within the company and potentially the broader industry.

• Leadership & Mentorship: Transition into a formal leadership role (e.g., Design Lead) or serve as a primary mentor for other designers, guiding them in AI adoption and advanced design techniques.

• Strategic Influence: Play a key role in shaping the product roadmap and design strategy, particularly concerning AI integration and user experience innovation.

• Industry Recognition: Contribute to thought leadership in AI-augmented design, potentially through conference presentations or internal best practice publications.

📝 Enhancement Note: This role offers a unique opportunity to be at the forefront of AI adoption in product design within a specialized, high-impact industry. The "Staff" title indicates a trajectory towards significant influence and potential leadership, with a focus on pioneering new methodologies.

🌐 Work Environment

Office Type: The role is listed as "On-site," suggesting a traditional office environment in Palo Alto, California. This implies a need for in-person collaboration and adherence to office norms.

Office Location(s): Palo Alto, California, United States. This is a prime location within the Silicon Valley tech hub, offering access to a rich ecosystem of innovation and talent.

Workspace Context:

• Collaborative Environment: Expect a dynamic, fast-paced startup environment that values cross-functional teamwork. The on-site nature facilitates spontaneous collaboration and team cohesion.

• Tools & Technology: Access to industry-standard design software (Figma) and cutting-edge AI design tools will be provided. The company's focus on AI suggests a commitment to equipping designers with the latest technological resources.

• Team Interaction: Opportunities for direct interaction with diverse teams, including engineering, product management, and potentially AI/data science specialists, fostering a rich learning and problem-solving environment.

Work Schedule: While standard full-time hours are implied (40 hours/week), the startup environment may occasionally require flexibility. However, the emphasis on work-life balance through generous vacation and winter break suggests a commitment to sustainable work practices.

📝 Enhancement Note: The on-site requirement in Palo Alto signifies a commitment to a traditional office culture, likely fostering strong team bonds and enabling effective in-person collaboration. This environment is well-suited for individuals who thrive on direct interaction and the energy of a physical workspace.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: Review of resume and portfolio by a recruiter or hiring manager to assess qualifications and AI experience.

• Portfolio Presentation & Discussion: A dedicated session where the candidate presents their portfolio, specifically highlighting AI integration case studies. Expect deep dives into their process, prompt engineering, and critical evaluation of AI's role.

• Design Challenge/Workshop: Potentially a practical exercise to assess design thinking, problem-solving skills, and how they would apply AI in a given scenario. This might involve rapid prototyping or ideation.

• Cross-Functional Interviews: Meetings with Product Managers, Engineers, and potentially other designers to evaluate collaboration style, communication, and cultural fit.

• Final Round: Discussion with senior leadership to assess strategic thinking and overall fit for the Staff-level role.

Portfolio Review Tips:

• AI Case Study Focus: Dedicate significant space to your AI integration case studies. Clearly outline the problem, your AI-assisted approach, the tools used, prompt examples, iterative refinement, and the final outcome/impact.

• Quantify Impact: Where possible, quantify the benefits of AI (e.g., "reduced prototyping time by X%", "generated Y design variations in Z hours").

• Showcase Critical Thinking: Articulate the rationale behind tool selection and prompt design. Be prepared to discuss the limitations of AI and why your human judgment was essential at specific stages.

• Visual Storytelling: Use visuals effectively to demonstrate the "before and after" of AI integration, showcasing the evolution of designs.

• Prompt Engineering Examples: Include examples of prompts used and explain how they were refined to achieve desired results.

Challenge Preparation:

• AI Application Scenarios: Anticipate design challenges that could be solved or accelerated with AI. Consider how you would approach creating a mood board, generating initial UI concepts, or synthesizing user feedback using AI.

• Prompting Practice: Be ready to demonstrate your ability to craft effective prompts for various AI design tools.

• Articulate Design Strategy: Be prepared to discuss your overall design philosophy, how AI fits into it, and how you would establish best practices for AI adoption within a team.

📝 Enhancement Note: The interview process will heavily scrutinize the candidate's practical experience and strategic thinking regarding AI in design. The portfolio is the primary vehicle for demonstrating this, so candidates must be prepared to deconstruct their AI-assisted work with clarity and evidence.

🛠 Tools & Technology Stack

Primary Tools:

• Figma: Required for core UI/UX design, prototyping, and collaboration.

Mastery is essential.

• AI Design & Prototyping Tools: Proficiency in at least two is required, with preferred experience in:

  • Galileo AI

  • Uizard

  • Relume

  • v0 by Vercel

• Framer AI

• Figma AI features

• Generative Image Tools: Familiarity is preferred, including:

  • Midjourney

  • DALL-E

  • Stable Diffusion

  • Adobe Firefly Analytics & Reporting: While not explicitly listed for this design role, understanding how design impacts user behavior and business metrics will be necessary. Familiarity with analytics platforms (e.g., Google Analytics, Mixpanel) and data visualization tools (e.g., Tableau, Power BI) could be beneficial for understanding user feedback and design performance.

CRM & Automation: Not directly applicable to this design role, but understanding the user journey within enterprise software contexts is important.

📝 Enhancement Note: The emphasis on specific AI tools is critical. Candidates should be prepared to discuss their experience with these tools in detail, including specific use cases, prompt engineering strategies, and how they integrate them into a broader design workflow alongside traditional tools like Figma.

👥 Team Culture & Values

Operations Values:

• Innovation & Technology Leadership: A strong drive to be at the forefront of technological advancements, particularly in AI, and to apply them to solve complex industry problems.

• Impact & Mission-Driven: A focus on delivering tangible value to clients (utilities) by improving grid reliability, safety, and efficiency, contributing to climate tech and infrastructure modernization.

• Collaboration & Cross-Functional Partnership: A belief in the power of diverse teams working together to achieve ambitious goals, especially in a fast-paced startup environment.

• Efficiency & Speed: A culture that values rapid iteration, accelerated delivery cycles, and leveraging tools (like AI) to maximize productivity.

• User-Centricity (AI-Augmented): While leveraging AI, the ultimate goal remains creating effective and user-friendly solutions for enterprise clients.

Collaboration Style:

• Proactive & Transparent: Open communication regarding project scope, risks, and progress is highly valued.

• Mentorship & Knowledge Sharing: As a Staff Designer, there's an expectation to mentor others and share best practices, particularly around AI adoption.

• Iterative & Experimental: A willingness to experiment with new tools and methodologies, embracing the iterative nature of design and AI development.

• Stakeholder Alignment: A focus on ensuring all stakeholders are informed and aligned throughout the design and development process.

📝 Enhancement Note: The company culture appears to be a blend of cutting-edge technological innovation, a strong sense of purpose tied to critical infrastructure and sustainability, and the dynamic pace of a growth-stage startup. The emphasis on AI adoption suggests a forward-thinking and experimental mindset.

⚡ Challenges & Growth Opportunities

Challenges:

• Defining AI Design Standards: Establishing clear, effective, and scalable standards for AI-augmented design across a growing organization.

• Balancing AI Efficiency with Human Craft: Ensuring that the drive for AI-accelerated design doesn't compromise quality, creativity, or strategic user insight.

• Rapidly Evolving AI Landscape: Staying current with the fast-paced advancements in AI design tools and techniques.

• Cross-Functional Buy-in: Evangelizing and gaining adoption of new AI-driven design workflows from various teams who may have different levels of AI familiarity.

• Managing AI Output Quality: Effectively refining and integrating AI-generated assets into production-ready designs.

Learning & Development Opportunities:

• Pioneering AI Design Practices: Opportunity to be a trailblazer in AI-augmented design, developing novel methodologies and best practices.

• Deep Dive into Enterprise AI: Gain in-depth understanding of AI applications within the critical utility infrastructure sector.

• Mentorship & Leadership Development: Grow into a leadership role through mentoring junior designers and influencing design strategy.

• Industry Exposure: Potential to attend industry events or participate in knowledge-sharing initiatives related to AI in design.

• Continuous Skill Enhancement: Access to resources and opportunities to continuously learn and adapt to new AI technologies and design trends.

📝 Enhancement Note: This role presents significant challenges related to pioneering new methodologies in a rapidly evolving field. However, these challenges are intertwined with substantial growth opportunities for individuals looking to shape the future of AI in design and gain leadership experience in a high-impact industry.

💡 Interview Preparation

Strategy Questions:

• "How would you establish the initial best practices for AI-assisted design within a team that has varying levels of AI adoption?"

• "Describe a time you used AI to significantly accelerate a design process. What were the key steps, tools, and challenges?"

• "Walk us through a complex design problem you solved. Where did AI play a role, and where was your human craft essential?"

• "How do you approach prompt engineering for design tools like Galileo AI or Midjourney? Can you give an example?"

Company & Culture Questions:

• "What excites you about AiDASH's mission and our focus on vegetation risk intelligence for utilities?"

• "How does your approach to AI-augmented design align with a fast-paced, growth-stage startup environment?"

• "Describe your experience collaborating with product managers and engineers. How do you ensure alignment and effective communication?"

Portfolio Presentation Strategy:

• Narrative Arc: Structure your portfolio presentation around a clear narrative for each AI case study: problem, AI-driven solution, process (including prompts/refinement), outcomes, and key learnings.

• Visual Evidence: Use clear visuals (screenshots, prototypes, before/after comparisons) to illustrate the impact of AI.

• Quantify Results: Whenever possible, present metrics that demonstrate the efficiency gains or quality improvements achieved through AI.

• Articulate Your Role: Be very clear about your specific contributions, the strategic decisions you made, and how you leveraged AI as a tool, not a replacement for your expertise.

• Prepare for Deep Dives: Expect detailed questions about your prompt engineering, AI tool choices, and how you validated or refined AI outputs.

📝 Enhancement Note: Interview preparation should heavily focus on demonstrating practical, hands-on experience with AI design tools and a strategic understanding of their application. Candidates must be able to articulate their process, justify their choices, and showcase quantifiable results.

📌 Application Steps

To apply for this Staff AI Product Designer position:

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

• Portfolio Customization: Tailor your portfolio to prominently feature at least two case studies that explicitly demonstrate your strategic use of AI in the design process. Highlight before/after scenarios, your specific AI integration methodology, and the value AI added.

• Resume Optimization: Ensure your resume clearly outlines your 6+ years of UX/product design experience, with specific mentions of AI design tools proficiency, Figma expertise, and collaborative project successes. Use keywords from the job description.

• Interview Preparation: Practice articulating your AI design process, preparing specific examples of prompt engineering, and discussing the balance between AI efficiency and human craft. Be ready to present your portfolio confidently.

• Company Research: Familiarize yourself with AiDASH's mission, technology (VegetationAI™), target market (utilities), and recent achievements (Forbes, Deloitte recognition) to demonstrate genuine interest and cultural alignment. Understand their "Securing Tomorrow!" ethos.

⚠️ 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.