Senior Product Designer, AI

📍 Job Overview

Job Title: Senior Product Designer, AI

Company: Sigma Computing

Location: San Francisco, CA

Job Type: Full-Time

Category: Product Design / Design Engineering (AI Focus)

Date Posted: April 14, 2026

Experience Level: 4+ Years

Remote Status: On-site (4 days/week)

🚀 Role Summary

• This role is at the forefront of designing and engineering user experiences for AI-powered applications and intelligent systems, blending interaction design with AI development.

• You will leverage AI tools, including Large Language Models (LLMs) and AI coding assistants, to accelerate the design and development lifecycle, from ideation to production code.

• The position demands a deep understanding of conversational interfaces and the ability to invent and validate novel interaction paradigms for AI-driven data contexts.

• You will be responsible for developing evaluation frameworks, skills, and tooling to ensure AI features behave predictably and improve over time, directly influencing model behavior and design output.

• This is a hands-on role requiring not only design expertise but also practical experience in building and shipping AI-assisted product features.

📝 Enhancement Note: This role is distinct from traditional product design. It requires a hybrid skillset where design craft is augmented by practical AI engineering and development experience, with a strong emphasis on shipping code and directly contributing to production. The "4-day on-site" requirement is crucial for candidates to note.

📈 Primary Responsibilities

• Utilize LLMs for scope clarification, specification drafting, edge case identification, and team alignment during the initial phases of product development.

• Employ AI coding tools like Cursor and Claude Code for rapid prototyping, guiding interface structure, behavior, motion, and overall UX quality while AI assists with implementation.

• Collaborate closely with engineering teams to determine which prototypes and validated spikes are ready for integration into the production product.

• Directly address and resolve minor interaction and refinement issues within the production codebase.

• Design, invent, and validate new interaction paradigms specifically for conversational AI interfaces, with a focus on data contexts requiring precision and user trust.

• Develop and implement evaluation frameworks, reusable "skills," and specific tooling to enhance the reliability and predictability of Sigma's AI features.

• Iterate on evaluation metrics and training data to refine AI performance in generating design outputs, effectively "teaching" AI to act as a skilled designer.

• Establish and champion the standards for AI-native UX craft at Sigma, creating patterns and principles that guide the broader design and engineering teams.

📝 Enhancement Note: The responsibilities highlight a highly integrated workflow between design, AI development, and direct code contribution. The emphasis on "setting the craft bar" and "teaching AI how to be a great designer" indicates a strategic and influential role within the product development process, requiring strong technical acumen alongside design expertise.

🎓 Skills & Qualifications

Education: While no specific degree is mandated, a strong foundation in computer science, design, human-computer interaction, or a related field is implied by the technical requirements.

Experience: 4+ years in interaction design or design engineering, with significant recent hands-on experience leveraging AI tooling for product development.

Required Skills:

• Demonstrated experience using AI coding assistants (e.g., Cursor, Claude Code) to build and ship real product features or substantial side projects.

• Proven ability to articulate how AI accelerated development, the specific features built, and how AI was guided or steered.

• Experience developing AI systems through writing evaluations, agents, prompt libraries, or skills, with an understanding of AI product development challenges.

• Strong interaction design fundamentals, including the ability to select and defend design patterns based on user needs and business objectives.

• Well-defined opinions and practical experience addressing key AI UX challenges such as trust signals, error recovery, and progressive disclosure of reasoning.

• Exceptional communication skills to effectively convey design decisions and technical concepts to Product Managers, Engineers, ML Researchers, and Executives.

Preferred Skills:

• Experience with conversational interfaces, especially in data-intensive domains.

• Familiarity with cloud data warehouse concepts and data analytics platforms.

• Background in data visualization and understanding of system-wide thinking in complex software products.

• Experience in prompt engineering and fine-tuning AI models for specific outputs.

📝 Enhancement Note: The requirement for "recent hands-on AI tooling experience — not just prompting, but building" is a critical differentiator. Candidates must be prepared to demonstrate tangible contributions using AI in their past roles. The portfolio requirement explicitly asks for AI-powered or AI-adjacent product work, underscoring this specialization.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase intricate interaction problems transformed into elegant, user-friendly flows, with a preference for examples involving conversational interfaces.

• Present designs that have been successfully released into production, demonstrating system-wide thinking, breadth and depth in interactive design skills, and an AI-first approach.

• Detail your design process, including the evolution of your designs from initial concept to final product, highlighting the business problem, constraints, assumptions, and significant iterations.

Process Documentation:

• Evidence of a structured design process that incorporates AI tools for ideation, prototyping, and iteration.

• Examples of how you have documented design decisions, user flows, and interaction specifications, particularly for AI-driven features.

• Demonstrations of how you have used AI to assist in evaluating design outcomes and iterating on AI model behavior for improved design output.

• Case studies that illustrate your ability to translate complex data or AI capabilities into intuitive user interfaces.

📝 Enhancement Note: The portfolio requirements are heavily weighted towards demonstrating practical application of design skills in an AI context, with a strong emphasis on released products and a clearly articulated process. Candidates should be prepared to walk through their work, explaining the "why" and "how," with specific examples of AI integration and its impact.

💵 Compensation & Benefits

Salary Range: $210,000 - $250,000 annually.

Benefits:

• Equity

• Generous health benefits

• Flexible time off policy

• Paid bonding time for all new parents

• Traditional and Roth 401k

• Commuter benefits

• FSA benefits

• Lunch Program

• Dog friendly office

Working Hours: The job description implies a standard 40-hour work week, with the specific requirement of 4 days on-site in the San Francisco office.

📝 Enhancement Note: The salary range provided is a base pay. The total compensation package also includes variable pay based on goal achievement, stock options, and the comprehensive benefits listed. The "4 day on-site" policy is a significant aspect of the work arrangement. For San Francisco, CA, this salary range is competitive for senior-level design roles, especially those with specialized AI and engineering skills. Cost of living in San Francisco is high, making this range appropriate for the experience and location.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology, specifically focusing on AI-powered applications and analytics platforms connected to cloud data warehouses. Sigma is transforming how businesses build apps, agents, and dashboards on top of governed enterprise data.

Company Size: Sigma Computing announced $200M in Series D financing in May 2024, indicating substantial growth and investment. While an exact employee count isn't provided, this funding suggests a company that is past the startup phase and is scaling aggressively, likely with several hundred employees.

Founded: The company has secured Series D funding, with its Series C round occurring three years prior, indicating a history of successful product development and market traction since its founding.

Team Structure:

• The design team is growing, seeking designers excited about solving challenging problems and delivering impactful capabilities across the stack.

• Collaboration is expected with a talented team of designers, engineers, and ML researchers.

Methodology:

• Sigma's platform integrates a spreadsheet interface, SQL and Python editors, visual builders, and native AI for data application development.

• The company emphasizes building "production-ready AI apps that accelerate and automate operational workflows."

• There's a strong focus on data accessibility for all users and innovation in AI infrastructure and data application development.

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

📝 Enhancement Note: Sigma Computing is positioned as an innovator in the BI and AI space, leveraging cloud data warehouses. The company culture likely values rapid innovation, technical excellence, and a collaborative approach to solving complex problems, particularly those involving AI and data. The Series D funding signifies strong market validation and potential for significant growth and impact.

📈 Career & Growth Analysis

Operations Career Level: This is a Senior Product Designer / Design Engineer role, indicating a mid-to-senior level position within the design function. It requires seasoned professionals who can operate with a high degree of autonomy and influence product direction, particularly in the emerging field of AI-native UX.

Reporting Structure: While not explicitly stated, this role likely reports into a Design Lead, Head of Design, or potentially a VP of Product/Engineering, depending on the organizational structure. The emphasis on close collaboration with engineering and PMs suggests a matrixed reporting structure or strong cross-functional alignment.

Operations Impact: The role has a direct impact on how users interact with Sigma's core AI capabilities, influencing the usability, efficiency, and adoption of the platform. By defining AI-native UX patterns and improving AI model behavior, this role significantly contributes to the product's overall value proposition and competitive differentiation.

Growth Opportunities:

• Specialization: Deepen expertise in AI-native interaction design, conversational AI, and AI product development methodologies.

• Leadership: Potential to become a domain expert and thought leader within Sigma for AI UX, mentoring junior designers and influencing strategic product decisions.

• Technical Advancement: Further develop skills in coding, AI model evaluation, and integrating AI tools into the product development lifecycle.

• Cross-functional Influence: Gain deeper understanding of ML research and engineering challenges, leading to more impactful and feasible design solutions.

📝 Enhancement Note: The "Senior" title combined with the specialized AI and engineering requirements suggests this role offers significant opportunities for career advancement within a high-growth, innovative tech company. Candidates looking to specialize in the cutting edge of AI product design will find ample room for growth and impact.

🌐 Work Environment

Office Type: The job explicitly states a "4 day on-site role in our San Francisco office." This indicates an in-office work environment with a hybrid component, but with a strong emphasis on in-person collaboration.

Office Location(s): San Francisco, CA. The description also notes that Sigma has offices in NYC and London, implying potential for cross-office collaboration or future mobility, though this specific role is tied to SF.

Workspace Context:

• The San Francisco office is described as "dog friendly," suggesting a more relaxed and employee-centric work environment.

• The "4 day on-site" model promotes in-person collaboration, team synergy, and spontaneous idea generation.

• Expect a dynamic environment within a growing tech company, likely with access to modern design and development tools.

Work Schedule: While not explicitly detailed beyond the 4-day on-site requirement, it's typical for such roles to operate on a standard full-time schedule (e.g., 40 hours per week), with flexibility often offered around the specific daily hours as long as core collaboration times are met.

📝 Enhancement Note: The "4 day on-site" model is a defining characteristic of this role's work environment. Candidates must be comfortable and willing to commute to the San Francisco office for four days a week, emphasizing the company's commitment to in-person collaboration and team cohesion.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screen: Likely a recruiter screen to assess basic qualifications, experience, and cultural fit, with a focus on AI and design background.

• Portfolio Review & Design Challenge: Candidates will present their portfolio, focusing on AI-powered or AI-adjacent product work, process, and impact. A design challenge, potentially involving AI tools or AI UX principles, may be presented.

• Technical/Engineering Deep Dive: Interviews with engineers and ML researchers to assess technical proficiency, coding skills (especially with AI assistants), and understanding of AI systems.

• Cross-functional Interviews: Discussions with Product Managers and other designers to evaluate collaboration style, communication skills, and strategic thinking.

• Hiring Manager Interview: Final discussion to assess overall fit, career aspirations, and alignment with the team's vision.

Portfolio Review Tips:

• Highlight AI Integration: Clearly showcase projects where AI was instrumental in the design or development process. Quantify the impact of AI where possible (e.g., time saved, efficiency gained, new capabilities enabled).

• Demonstrate Process: Walk through your design methodology, emphasizing how you used AI tools (LLMs, coding assistants) at different stages. Show iterations, pivots, and decision-making rationale.

• Focus on Released Work: Prioritize designs that have shipped, demonstrating your ability to bring ideas to production. Explain the business problem, user needs, and how your solution addressed them.

• Showcase Interaction Design Craft: Even with AI, strong interaction design fundamentals must be evident. Explain your choices for UI patterns, conversational flows, and how you ensured user trust and clarity.

• Be Ready for Technical Questions: Prepare to discuss your experience with code, AI evaluation frameworks, and how you collaborate with engineers and ML specialists.

Challenge Preparation:

• Familiarize yourself with current AI UX best practices, including trust, safety, error handling, and transparency in AI systems.

• Practice using AI coding assistants and LLMs to generate ideas, draft specifications, or even prototype simple interfaces.

• Be prepared for a challenge that might require you to design a new AI interaction paradigm or outline an evaluation framework for an AI feature.

• Practice articulating your thought process clearly and concisely, as if explaining it to a mixed audience of designers and engineers.

📝 Enhancement Note: The interview process is designed to thoroughly assess a candidate's hybrid skillset. Success hinges on demonstrating not just design talent but also practical AI development and engineering capabilities, coupled with strong communication and collaboration skills. The portfolio is the central piece of evidence.

🛠 Tools & Technology Stack

Primary Tools:

• Design & Prototyping: Figma (explicitly mentioned), potentially other prototyping tools.

• AI Coding Assistants: Cursor, Claude Code (explicitly mentioned).

• LLMs: General use for ideation, clarification, spec drafting (e.g., GPT-4, Claude).

• Development Environments: Likely standard IDEs and version control systems (e.g., Git), with a focus on integrating AI coding tools.

Analytics & Reporting:

CRM & Automation:

• Not directly relevant to this design role, but the product itself is an "AI apps and analytics platform connected to the cloud data warehouse," so understanding data integration and workflow automation concepts is beneficial.

📝 Enhancement Note: The technology stack is heavily skewed towards AI development tools. Proficiency in Figma is a baseline, but deep practical experience with AI coding assistants like Cursor and Claude Code, alongside a strong understanding of how to leverage LLMs in the design and development workflow, is paramount.

👥 Team Culture & Values

Operations Values:

• Innovation & AI-First: A strong commitment to pushing the boundaries of AI in product development and user experience.

• Data-Driven: Emphasizing the use of data and rigorous evaluation to inform design decisions and improve AI performance.

• Collaboration & Cross-Functional Partnership: Valuing close teamwork between design, engineering, and ML research to achieve shared goals.

• Craftsmanship & Excellence: Setting high standards for both design quality and technical execution, particularly in the AI domain.

• Impact & Ownership: Encouraging individuals to take ownership of their work and drive meaningful impact on the product and users.

Collaboration Style:

• Integrated Teams: Designers work hand-in-hand with engineers and ML researchers, participating in code reviews and development sprints.

• Open Communication: Expect a culture that encourages sharing ideas, constructive feedback, and open dialogue across disciplines.

• Agile & Iterative: A methodology that likely involves rapid prototyping, testing, and iteration, with AI playing a key role in accelerating these cycles.

• Learning-Oriented: A continuous learning environment where team members are encouraged to explore new AI technologies and design approaches.

📝 Enhancement Note: The culture at Sigma Computing, particularly within the product and design teams, appears to be fast-paced, technically sophisticated, and highly collaborative. The emphasis on AI means embracing experimentation and a willingness to learn and adapt as the technology evolves.

⚡ Challenges & Growth Opportunities

Challenges:

• Defining Novel AI UX: Creating intuitive and trustworthy user experiences for AI-driven features, especially in complex data contexts, is an ongoing challenge.

• Bridging Design and Engineering: Effectively translating AI capabilities into tangible user value requires seamless collaboration and communication between design and engineering.

• Rapidly Evolving AI Landscape: Staying abreast of the fast-paced advancements in AI technology and adapting design strategies accordingly.

• Ensuring AI Reliability & Predictability: Developing robust evaluation frameworks and AI skills to ensure consistent and predictable performance of AI features.

• On-site Requirement: Balancing the benefits of on-site collaboration with the efficiency and flexibility that remote work can offer.

Learning & Development Opportunities:

• Cutting-Edge AI Exposure: Direct involvement with the latest AI tools and methodologies, providing hands-on experience in a rapidly growing field.

• Deep Dive into AI Product Development: Gaining comprehensive knowledge of the end-to-end process of building AI-powered products.

• Skill Expansion: Opportunities to hone both interaction design skills and practical engineering capabilities, including coding and AI model interaction.

• Mentorship: Potential to learn from experienced engineers and ML researchers, as well as to mentor junior designers in AI UX.

• Industry Influence: Contributing to establishing best practices for AI-native UX, which can be a significant career differentiator.

📝 Enhancement Note: This role presents significant challenges due to the cutting-edge nature of AI product development. However, these challenges are directly tied to substantial growth opportunities for individuals looking to become leaders in the AI UX space.

💡 Interview Preparation

Strategy Questions:

• "Describe a project where you used AI coding assistants to accelerate product development. What were the key benefits, and where did you need to provide significant human guidance?"

• "How would you approach designing a conversational interface for [a specific data analysis task] within Sigma's platform? What are the key trust and clarity considerations?"

Company & Culture Questions:

• "What excites you most about Sigma Computing's mission and its approach to AI?"

• "How do you envision collaborating with engineers and ML researchers to define and refine AI capabilities?"

Portfolio Presentation Strategy:

• Structure Your Narrative: For each project, clearly articulate: 1) The Business/User Problem, 2) Your Role & Responsibilities, 3) The AI Tools/Methods Used, 4) Your Design Process & Iterations, 5) The Solution & Its Impact.

• Quantify Impact: Wherever possible, use metrics to demonstrate the success of your designs (e.g., increased user engagement, reduced task completion time, improved accuracy).

• Highlight AI Specifics: For AI-powered projects, be explicit about how AI was integrated, what challenges it solved, and what unique UX considerations arose.

• Showcase Process & Iteration: Don't just show final screens; illustrate your journey, including sketches, wireframes, prototypes, and how user feedback or AI evaluations informed changes.

• Be Prepared for Live Design/Coding: While not explicitly stated, have a basic understanding of how you might approach a quick design exercise or demonstrate your familiarity with coding assistants.

📝 Enhancement Note: Interview preparation should focus on demonstrating a blend of design acumen, technical understanding of AI, and practical experience with AI development tools. Be ready to discuss both your "why" (strategic thinking) and your "how" (execution and collaboration).

📌 Application Steps

To apply for this Senior Product Designer, AI position:

• Submit your application through the provided Greenhouse link.

• Tailor Your Resume: Highlight your 4+ years of experience in interaction design or design engineering, with specific emphasis on any hands-on AI tooling experience, including LLMs and AI coding assistants. Use keywords from the job description.

• Curate Your Portfolio: Ensure your portfolio prominently features AI-powered or AI-adjacent product work. Clearly articulate your process, the business problems solved, and the impact of your designs, particularly those involving conversational interfaces or complex data interactions. Be ready to discuss your use of Figma, Cursor, and Claude Code.

• Prepare Your Narrative: Practice walking through your portfolio projects, focusing on how you leveraged AI to accelerate development, define new interaction paradigms, and contribute to production code. Be ready to discuss your opinions on AI UX and your experience with evaluation frameworks.

• Research Sigma Computing: Understand their platform, mission, and recent funding news. Be prepared to discuss why you are specifically interested in their AI-focused product development and how your skills align with their innovative approach.

⚠️ 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.