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: 2026-04-25T23:00:46

Experience Level: 5-10 Years

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

🚀 Role Summary

• Drive the design and development of AI-native interaction paradigms for Sigma's platform, focusing on how users interact with intelligent systems within data contexts.

• Leverage AI tools, including LLMs and AI coding assistants, to accelerate the design and development lifecycle, from ideation and specification to implementation and production code.

• Build and refine AI skills, evaluation frameworks, and tooling to ensure the reliability, predictability, and continuous improvement of Sigma's AI features.

• Collaborate closely with engineering and ML research teams to define and deliver world-class AI-powered capabilities, influencing the future of data application development.

📝 Enhancement Note: This role is a unique blend of interaction design and AI engineering, requiring hands-on coding and AI tool utilization beyond traditional design responsibilities. The emphasis is on shipping AI-driven features rapidly and shaping the user experience of intelligent systems.

📈 Primary Responsibilities

• Utilize Large Language Models (LLMs) for scope clarification, specification drafting, edge case identification, and team alignment during the early stages of product development.

• Employ AI coding tools like Cursor and Claude Code to prototype and build functional interfaces, guiding structure, behavior, motion, and UX quality while AI assists with implementation.

• Partner directly with engineering teams to determine which AI-assisted prototypes and validated spikes are ready for production.

• Directly address and fix minor interaction and refinement issues in production code to maintain high UX standards.

• Invent, design, and validate novel interaction patterns for conversational AI interfaces, specifically tailored for data-intensive environments where precision and trust are paramount.

• Develop evaluation frameworks, reusable AI skills, and supporting tools to ensure Sigma's AI features operate predictably and continuously improve over time.

• Contribute to shaping AI model behavior by iterating on evaluations and training data to enhance design output quality and teach AI to function as a proficient designer.

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

📝 Enhancement Note: The responsibilities emphasize a "start with AI, stay with AI" philosophy, integrating AI throughout the entire product development lifecycle. This includes not only designing AI features but also using AI to expedite the design process and directly contributing code to production.

🎓 Skills & Qualifications

Education: While not explicitly stated, a Bachelor's or Master's degree in Design, Human-Computer Interaction, Computer Science, or a related field is typically expected for senior-level design roles.

Experience: 4+ years in interaction design or design engineering, with a demonstrated track record of using AI tooling to ship real product features.

Required Skills:

• Proven hands-on experience with AI tooling and AI coding assistants (e.g., Cursor, Claude Code) to ship production-ready features.

• Demonstrated ability to articulate the role of AI in accelerating product development and the specific ways you've steered AI-assisted work.

• Experience in developing AI systems, specifically writing evaluations, agents, prompt libraries, or skills, with a strong understanding of the challenges in AI product development.

• Strong interaction design fundamentals, with the ability to strategically select and extend design patterns and defend choices with clear reasoning.

• Well-defined opinions on AI UX, including expertise in trust signals, error recovery, and progressive disclosure of reasoning, backed by practical examples.

• Exceptional communication skills, capable of effectively conveying complex design decisions and strategies to Product Managers, Engineers, ML Researchers, and Executives.

Preferred Skills:

• Experience designing conversational interfaces.

• Familiarity with data warehousing concepts and SQL/Python for data manipulation and analysis.

• Understanding of machine learning principles and their application in product design.

• Experience in user research methodologies to validate AI-driven design concepts.

📝 Enhancement Note: The emphasis on "recent hands-on AI tooling experience — not just prompting, but building" signifies a need for candidates who have actively engaged with and developed AI-powered solutions, not just users of AI tools. The portfolio requirement is critical for demonstrating this practical application.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase elegant solutions to intricate interaction problems, with a preference for examples involving conversational interfaces.

• Present designs for successfully released products that demonstrate system-wide thinking, a breadth and depth of interactive design skills, and an AI-first approach.

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

Process Documentation:

• Clearly articulate your methodology for using AI tools (LLMs, coding assistants) to accelerate design and development processes, including how you manage scope, identify edge cases, and align teams.

• Demonstrate your approach to prototyping in code, detailing how you guide AI implementation for structure, behavior, motion, and UX quality.

• Provide examples of how you have developed and validated AI evaluation frameworks, skills, or tools to ensure predictable and improving AI performance.

📝 Enhancement Note: The portfolio requirements are highly specific, demanding evidence of practical AI application, system-wide thinking, and a clear demonstration of how design decisions drive business objectives. Candidates are expected to showcase their process and the iterative journey of their designs, particularly those involving AI.

💵 Compensation & Benefits

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

Benefits:

• Equity (Stock Options)

• 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: While not explicitly stated, a standard full-time work week of approximately 40 hours is assumed, with an on-site requirement of 4 days per week in the San Francisco office.

📝 Enhancement Note: The salary range provided is for base pay only and does not include variable pay (based on goal achievement) or stock options, indicating a competitive total compensation package for this senior role. The on-site requirement of 4 days per week in San Francisco is a critical factor for candidates.

🎯 Team & Company Context

🏢 Company Culture

Industry: Software / Data Analytics / AI Platforms. Sigma is transforming how businesses build applications, agents, and dashboards on top of governed enterprise data, with a strong focus on AI integration.

Company Size: The provided data does not explicitly state company size, but the Series D funding announcement in May 2024 suggests a rapidly growing, well-funded startup environment, likely in the range of 200-500 employees.

Founded: Sigma Computing was founded in 2017, indicating a company with several years of market presence and product development, now accelerating with significant investment.

Team Structure:

• The design team is growing, comprised of talented designers focused on making data accessible. This role is part of a broader engineering and product organization.

• The Senior Product Designer, AI will work closely with Product Managers, Engineers, and ML Researchers.

Methodology:

• Sigma utilizes AI extensively, from clarifying scope and drafting specs with LLMs to coding with AI assistants and developing AI evaluation frameworks.

• The company emphasizes rapid iteration and shipping features to production, often with direct code contributions from designers.

• Data-driven decision-making is inherent, given the company's focus on analytics and AI platforms.

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

📝 Enhancement Note: Sigma Computing is positioning itself at the forefront of AI-driven data analytics and application development. The company culture appears to be fast-paced, innovative, and highly collaborative, with a strong engineering-centric approach. The emphasis on AI integration across all aspects of the product and development process is a key differentiator.

📈 Career & Growth Analysis

Operations Career Level: This is a Senior Product Designer/Design Engineer role, indicating a position for an experienced individual contributor who can operate with a high degree of autonomy. The role requires not only design expertise but also technical proficiency in AI and coding.

Reporting Structure: The exact reporting structure is not specified, but it is likely a senior individual contributor role reporting to a Head of Design, Director of Product Design, or a similar leadership position within the product organization. The role emphasizes close partnership with engineering and product management.

Operations Impact: This role has a significant impact on Sigma's core product offering by shaping how users interact with AI capabilities. Success means delivering AI features that enhance user productivity, automate workflows, and drive adoption of Sigma's platform, directly contributing to the company's growth and market position.

Growth Opportunities:

• Technical Specialization: Deepen expertise in AI-native UX design, LLM integration, and AI development tooling, becoming a go-to expert in this cutting-edge field.

• Leadership & Mentorship: As a senior member, there will be opportunities to mentor junior designers and engineers, set design standards, and influence product strategy.

• Product Innovation: Play a pivotal role in defining and launching new AI-powered features that can significantly shape the future of data analytics and application development platforms.

• Cross-functional Leadership: Develop strong relationships and influence across engineering, product management, and ML research, potentially leading design initiatives for major AI product areas.

📝 Enhancement Note: This role offers a unique opportunity for career growth at the intersection of design and AI. The expectation to not only design but also to code and directly contribute to production code by leveraging AI presents a significant learning curve and a chance to develop highly in-demand skills.

🌐 Work Environment

Office Type: There is an in-office work environment in San Francisco. The description mentions a "dog-friendly office," indicating a more relaxed and potentially collaborative workspace.

Office Location(s): San Francisco, CA. Specific details about the office facilities or amenities beyond being dog-friendly are not provided.

Workspace Context:

• The role requires 4 days on-site in the San Francisco office, suggesting a hybrid model with one remote day. This encourages in-person collaboration, idea generation, and team building.

• The environment is likely fast-paced and innovative, given Sigma's focus on AI and its recent funding.

• Access to modern design and development tools is expected, including AI coding assistants and design software like Figma.

Work Schedule: The standard work week is assumed to be around 40 hours, with the specific schedule likely being flexible within operational needs, common in tech companies. The 4-day on-site requirement is a key aspect of the schedule.

📝 Enhancement Note: The 4-day on-site requirement in San Francisco is a critical element of the work environment. This structure aims to balance the benefits of in-person collaboration and team cohesion with some degree of flexibility.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A review of your resume and portfolio to assess experience with AI tooling, design skills, and product shipping capabilities.

• Design/Technical Interview: Expect to discuss your past projects, particularly those involving AI, your design process, and how you've used AI to accelerate development. This may include a coding exercise or discussion of your code contributions.

• Portfolio Presentation: A deep dive into your portfolio, focusing on AI-powered or AI-adjacent product work. Be prepared to articulate your process, the business problems solved, constraints, iterations, and the impact of your designs.

• Cross-functional Interviews: Discussions with Product Managers, Engineers, and potentially ML Researchers to assess collaboration style, technical understanding, and cultural fit.

• Final Interview: Likely with senior leadership to discuss strategic vision, leadership potential, and overall fit with the company.

Portfolio Review Tips:

• Highlight AI Impact: Clearly showcase projects where you leveraged AI (LLMs, coding assistants) to achieve tangible results, such as faster shipping times, improved feature quality, or novel interaction patterns.

• Demonstrate Process & Iteration: Detail your end-to-end design process, including how you translated user needs and business goals into elegant solutions, emphasizing your iterative approach and decision-making rationale.

• Showcase System-Wide Thinking: Present designs that demonstrate a holistic understanding of the product ecosystem and how your contributions fit into the larger platform strategy.

• Quantify Results: Where possible, provide metrics or evidence of the business impact and user value your designs have delivered. For AI-driven features, this could include adoption rates, efficiency gains, or user satisfaction scores.

• Code Proficiency: Be ready to discuss your code contributions and how you've used AI coding tools to build and iterate on interfaces.

Challenge Preparation:

• AI Use Case Scenarios: Be prepared for scenarios where you'll need to explain how you would use AI to solve specific design challenges or improve existing workflows.

• Design System Thinking: Understand how to build and maintain design systems for AI-native interfaces, ensuring consistency and scalability.

• Communication of Technical Concepts: Practice explaining complex AI and design concepts clearly and concisely to both technical and non-technical audiences.

📝 Enhancement Note: The interview process is rigorous and designed to assess a unique blend of design craft, technical AI proficiency, and the ability to ship production code. A strong portfolio that explicitly demonstrates AI tool usage and its impact is paramount.

🛠 Tools & Technology Stack

Primary Tools:

• Figma: For core UI/UX design, wireframing, and prototyping.

• AI Coding Assistants: Cursor, Claude Code, or similar tools for writing and iterating on production code.

• LLMs: For ideation, specification drafting, and identifying edge cases.

• Version Control: Git, likely integrated with CI/CD pipelines for code deployment.

Analytics & Reporting:

• Sigma's own platform for data analysis and application building.

CRM & Automation:

• While not directly mentioned, standard CRM and automation tools may be used by sales and marketing teams that designers would need to understand for context.

📝 Enhancement Note: The emphasis on specific AI tools like Cursor and Claude Code, along with LLMs, is a key differentiator for this role. Candidates are expected to be proficient not just in design software but also in leveraging AI for coding and development.

👥 Team Culture & Values

Operations Values:

• Innovation & Speed: A culture that encourages rapid prototyping, experimentation with AI, and quick iteration to ship features to production.

• Data-Driven Excellence: A strong focus on using data to inform design decisions and measure the impact of AI features.

• Collaboration & Partnership: Close working relationships between design, engineering, and ML research teams to co-create solutions.

• Craftsmanship & Quality: A commitment to delivering world-class technology with a high standard for UX quality, even when leveraging AI.

• User-Centricity: While AI-focused, the ultimate goal is to empower users and make data accessible, emphasizing user needs and trust in AI systems.

Collaboration Style:

• Highly collaborative, with designers working directly alongside engineers and ML researchers.

• Emphasis on clear communication and the ability to articulate design decisions and AI strategy effectively.

• A culture of constructive feedback and shared ownership of product outcomes.

📝 Enhancement Note: The company culture values individuals who are comfortable with ambiguity, eager to experiment with new technologies like AI, and possess a strong bias for action. The integration of AI into the design and development process suggests a culture that embraces cutting-edge approaches and values technical depth.

⚡ Challenges & Growth Opportunities

Challenges:

• Defining AI Interaction Paradigms: The evolving nature of AI means there are few established patterns for conversational interfaces, especially in data contexts, requiring innovation and validation.

• Balancing AI Assistance with Human Craft: Ensuring that AI tools augment rather than replace critical design thinking and craftsmanship, maintaining high UX quality.

• Technical Complexity: Working at the intersection of design, AI, and production code requires a broad and deep skill set, with continuous learning necessary.

• Establishing Trust and Predictability: Designing AI systems that users can trust and that behave predictably in complex data scenarios.

Learning & Development Opportunities:

• Cutting-edge AI UX: Become a leader in an emerging field, gaining expertise in designing for intelligent systems.

• Full-Stack Design Impact: Directly contribute to production code, bridging the gap between design and engineering and developing a unique hybrid skill set.

• Industry Leadership: Influence the direction of AI-driven product development within a fast-growing, well-funded company.

• Mentorship and Knowledge Sharing: Opportunity to guide and mentor other designers and engineers, and to contribute to Sigma's knowledge base on AI product development.

📝 Enhancement Note: This role presents significant challenges, particularly in pioneering new interaction models for AI. However, these challenges are directly tied to substantial growth opportunities for individuals looking to build expertise in the rapidly expanding field of AI product development.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you used AI coding assistants to ship a product feature. What was the feature, how did AI accelerate its development, and where did you have to provide significant direction?"

• "How do you approach designing for trust and transparency in AI-driven interfaces, especially when dealing with sensitive data? Provide specific examples of patterns you've used or would propose."

Company & Culture Questions:

• "What excites you about Sigma's mission to transform data analytics with AI, and how does your background align with our AI-first approach?"

• "How do you envision the collaboration between designers, engineers, and ML researchers evolving as AI becomes more integrated into product development?"

Portfolio Presentation Strategy:

• Structure around AI Impact: For each case study, clearly articulate the role AI played, the specific tools used, and the measurable impact on the product or user experience.

• Showcase Your Process: Detail your iterative journey, including initial concepts, challenges encountered, how you leveraged AI for prototyping/development, and the rationale behind key design decisions.

• Explain Technical Contributions: Be prepared to discuss your code contributions and how you collaborated with engineers to bring AI-powered features to life.

• Highlight Systemic Thinking: Demonstrate how your designs fit into the broader Sigma platform and contribute to its overall value proposition.

📝 Enhancement Note: Candidates should prepare to speak extensively about their practical experience with AI tools, their understanding of AI UX principles, and their ability to contribute code. The portfolio should serve as a narrative of their AI-driven design and development journey.

📌 Application Steps

To apply for this Senior Product Designer, AI position:

• Submit your application through the provided Greenhouse link.

• Tailor your resume: Emphasize your experience with AI tooling, design engineering, interaction design, and any production code shipped using AI assistance. Highlight specific AI tools and LLMs you've used.

• Curate your portfolio: Select projects that best showcase your AI-powered or AI-adjacent product work, focusing on system-wide thinking, your design process, and demonstrable impact. Ensure it includes examples of conversational interfaces or data-intensive AI applications if possible.

• Prepare your portfolio walkthrough: Practice presenting your case studies, focusing on articulating the business problem, your AI-driven solutions, your iterative process, technical contributions, and the outcomes.

• Research Sigma Computing: Understand their product, mission, and recent funding. Be ready to discuss how your skills and experience can contribute to their AI-first strategy and data analytics platform.

⚠️ 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.