Staff Product Designer, Agentic Coding

📍 Job Overview

Job Title: Staff Product Designer, Agentic Coding

Company: Databricks

Location: Mountain View, California; San Francisco, California; Seattle, Washington

Job Type: Full-time

Category: Product Design / UX Design (with a focus on AI/Developer Tools)

Date Posted: 2026-09-29

Experience Level: 10+ years

Remote Status: On-site

🚀 Role Summary

• Lead product design strategy and execution for Databricks' Omnigent platform, focusing on human-AI interaction for coding agents.

• Drive the end-to-end design of desktop and mobile experiences for live agent sessions, encompassing strategy, interaction models, and visual polish.

• Act as a builder-designer, comfortable with direct codebase contributions and using AI tools to explore complex, ambiguous problems.

• Define and refine the interaction language for agentic work, including real-time multi-agent sessions, human-in-the-loop approvals, and trust-building mechanisms.

• Collaborate deeply with product management and engineering to translate cutting-edge AI capabilities into intuitive, controllable, and trustworthy user experiences.

📝 Enhancement Note: This role is heavily focused on the intersection of AI, developer tools, and user experience design. The "Agentic Coding" aspect signifies a deep dive into how users will interact with, control, and trust AI agents that perform coding, review, and exploration tasks. The emphasis on "builder-designer" and direct codebase contribution is a key differentiator for senior individual contributor roles in design.

📈 Primary Responsibilities

• Own the complete design lifecycle for Omnigent's desktop and mobile interfaces, from initial concept and strategy to final shipped details.

• Develop and iterate on high-density orchestration workflows for desktop environments and lightweight monitoring, review, and intervention flows for mobile.

• Directly contribute to the codebase for well-scoped design changes, ensuring seamless integration and rapid iteration with engineering partners.

• Utilize interactive prototyping as a primary tool for exploring, de-risking, and aligning teams on solutions for large, undefined problems.

• Invent and establish the core interaction language for agentic work, addressing aspects like multi-agent coordination, co-driving/forking sessions, approval processes, agent transparency, and error/recovery states.

• Formulate durable UX principles and reusable interaction frameworks for agent collaboration, observability, and recovery to ensure consistency across the Omnigent platform.

• Drive cross-platform consistency by leveraging and extending a robust design system for both desktop and mobile applications.

• Employ user research instincts and analyze real-world usage data to validate design decisions and inform future product development.

📝 Enhancement Note: The responsibilities highlight a blend of strategic thinking (defining interaction languages, UX principles) and hands-on execution (direct coding, prototyping). The focus on both desktop and mobile experiences for a complex AI product requires strong systems thinking and the ability to manage diverse user contexts.

🎓 Skills & Qualifications

Education: While no specific degree is mandated, a strong foundation in Human-Computer Interaction (HCI), Computer Science, Design, or a related field is expected, demonstrated through experience and portfolio.

Experience: 10+ years of experience in product design, with a proven track record of shipping complex, high-quality products, particularly in the developer tools, AI/ML, or enterprise software space.

Required Skills:

• Builder-Designer Mindset: Proven ability to contribute directly to codebases for design implementation and leverage AI tools in your design workflow.

• End-to-End Design Craft: Demonstrated expertise in interaction design, visual/UI polish, and design systems thinking.

• Systems Thinking: Ability to design complex, interconnected systems and define reusable frameworks.

• Prototyping Fluency: Proficient in using interactive prototypes as a primary tool for exploration, validation, and team alignment.

• AI/Agentic Workflows: Experience or strong understanding of designing for AI-driven products, particularly coding agents, LLMs, and multi-agent systems.

• Cross-Platform Design: Expertise in designing cohesive experiences across both desktop and mobile environments.

• Product Strategy Acumen: Ability to shape product direction, particularly in ambiguous or undefined problem spaces.

• Collaboration & Communication: Excellent skills in partnering with engineering and product management, providing and receiving high-quality critique.

• User Research & Data Analysis: Instincts for grounding design decisions in user needs and usage data.

Preferred Skills:

• Experience designing coding tools, IDEs, agent frameworks, or developer platforms.

• Familiarity with multi-agent systems, LLM harnesses, or governance/observability tooling.

• Understanding of enterprise software adoption and governance requirements.

📝 Enhancement Note: The "builder-designer" requirement is critical. Candidates must be able to demonstrate not just conceptual design skills but also the technical aptitude and willingness to implement designs directly, working alongside engineers. A strong portfolio showcasing complex technical products is essential.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase end-to-end design projects, emphasizing the problem, your process, design decisions, and measurable outcomes.

• Include examples of complex interaction models, particularly those involving AI, automation, or technical users.

• Demonstrate proficiency in designing for both desktop and mobile platforms, highlighting cross-platform consistency and adaptation.

• Feature examples of systems thinking, including the creation or contribution to design systems, interaction frameworks, or reusable components.

• Present case studies where prototyping was a key tool for exploration and validation.

• Highlight projects where direct contributions to code or close collaboration with engineering led to successful product launches.

• Include examples demonstrating your ability to navigate ambiguity and shape product direction. Process Documentation:

• Clearly articulate your design process, from problem definition and user research to ideation, prototyping, iteration, and final implementation.

• For each project, detail how you gathered requirements, conducted user research, tested hypotheses, and made trade-offs.

• Explain your approach to defining and evolving interaction languages and design principles for new technological paradigms like agentic work.

• Document your methods for ensuring design quality, consistency, and scalability across platforms.

📝 Enhancement Note: For a Staff-level role, the portfolio needs to demonstrate not just individual contribution but also leadership in design strategy, systems thinking, and the ability to influence product direction. The "builder-designer" aspect should be evident through examples of direct implementation or very close collaboration with engineering.

💵 Compensation & Benefits

Salary Range:

• Zone 1: $166,600 - $229,150 USD per year

• Zone 2: $158,300 - $217,700 USD per year

• Zone 3: $128,400 - $179,700 USD per year

Benefits:

• Annual performance bonus eligibility

• Equity (stock options or grants)

• Comprehensive benefits and perks (specifics available via provided link)

Working Hours: 40 hours per week (standard full-time)

📝 Enhancement Note: The salary ranges provided are location-dependent, categorized into three zones. Zone 1 represents the highest range, typically for high-cost-of-living areas like the specified California locations. Zone 2 and Zone 3 represent progressively lower ranges for other areas. The compensation structure includes base salary, performance bonus, and equity, which is standard for senior technical roles at growth-stage tech companies.

🎯 Team & Company Context

🏢 Company Culture

Industry: Data and AI Platform, Enterprise Software. Databricks is a leader in unifying data, analytics, and AI, serving over 20,000 organizations globally.

Company Size: Large (over 20,000 employees worldwide). This implies a structured environment with established processes but also opportunities for impact within specialized teams.

Founded: Databricks was founded in 2013. This relatively young but rapidly growing company is known for its innovation and fast-paced culture.

Team Structure: The role is within the "Omnigent" team, focused on AI coding agents. This team likely comprises Product Managers, Engineers (front-end, back-end, AI/ML), and Designers. As a Staff Designer, you will be a key individual contributor, potentially mentoring junior designers and influencing the design direction across the team. The structure encourages deep collaboration between design, product, and engineering.

Methodology: Databricks emphasizes a data-driven approach to product development. For the Omnigent team, this likely involves:

• Iterative Development: Rapid prototyping and shipping small, impactful design changes.

• User-Centric Design: Grounding decisions in user research and real usage data, especially critical for a novel area like agentic work.

• Cross-Functional Partnership: Tight integration between design, engineering, and product to ensure cohesive product strategy and execution.

• Leveraging AI: Utilizing AI tools not just for product features but also within the design and development workflow itself.

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

📝 Enhancement Note: Databricks is a high-growth tech company with a strong focus on innovation in the AI and data space. The culture likely values technical expertise, collaboration, and a "builder" mentality. The Omnigent team is at the forefront of a new product category, suggesting an environment that embraces experimentation and tackling complex, novel challenges.

📈 Career & Growth Analysis

Operations Career Level: This is a Staff-level Product Designer role, indicating a senior individual contributor position. It signifies a high degree of autonomy, ownership, and the expectation to lead design direction on complex, ambiguous problems. Staff designers are expected to have significant impact, influence product strategy, and mentor others.

Reporting Structure: While not explicitly stated, a Staff Designer typically reports to a Design Manager or Director of Design. Within the Omnigent team, they will partner closely with the Product Manager and Engineering Lead for the agentic coding initiatives.

Operations Impact: The role has a direct impact on how users interact with and trust AI agents for critical tasks like coding. Success in this role will be measured by the adoption, usability, and perceived trustworthiness of the Omnigent platform, directly influencing Databricks' position in the emerging agentic AI market. This role shapes the user experience of a foundational technology for future AI-powered workflows.

Growth Opportunities:

• Technical Specialization: Deepen expertise in AI/ML product design, human-agent interaction, and developer tools.

• Leadership & Mentorship: Lead design initiatives, mentor junior designers, and influence design best practices across the organization.

• Strategic Influence: Contribute significantly to the product strategy and vision for agentic AI at Databricks.

• Cross-Functional Development: Gain exposure to cutting-edge AI research and engineering challenges, enhancing understanding of the broader technology landscape.

• System Design Mastery: Develop advanced skills in creating scalable design systems and interaction frameworks for complex software.

📝 Enhancement Note: Staff-level roles are critical for career progression, offering opportunities to operate at a strategic level without necessarily moving into management. The impact of this role is substantial, given its focus on a nascent and rapidly evolving area of AI.

🌐 Work Environment

Office Type: Databricks offers on-site work. The offices in Mountain View, San Francisco, and Seattle are likely modern, collaborative workspaces designed to foster innovation and teamwork.

Office Location(s): Mountain View, California; San Francisco, California; Seattle, Washington. These are major tech hubs, offering access to talent and a vibrant ecosystem.

Workspace Context:

• Collaborative Environment: Expect an office setting that encourages spontaneous interactions, brainstorming sessions, and close collaboration with cross-functional teams (engineering, product).

• Tools & Technology: Access to state-of-the-art design tools, prototyping software, and potentially internal AI tools that can aid the design process.

• Team Interaction: Regular opportunities for design critiques, team syncs, and working sessions with engineers and product managers. The "builder-designer" aspect implies close proximity and frequent interaction with the engineering team.

Work Schedule: Standard full-time (40 hours/week) with the expectation of flexibility as needed to meet project deadlines and collaborate effectively across time zones and teams. The on-site requirement emphasizes in-person collaboration.

📝 Enhancement Note: The on-site requirement suggests a preference for in-person collaboration, which is often beneficial for complex design challenges and rapid iteration, especially when working directly with code.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screen: HR or Recruiter call to assess basic qualifications and cultural fit.

• Hiring Manager Interview: Discussion about experience, role expectations, and team dynamics.

• Portfolio Presentation & Design Deep Dive: Present your portfolio, focusing on 1-2 key projects. Expect in-depth questions about your process, decision-making, and impact. This is where the "builder-designer" aspect will be scrutinized.

• Cross-Functional Interviews: Interviews with Product Managers and Engineers to assess collaboration skills, technical understanding, and ability to work within a team.

• Staff-Level Challenge (Potential): May involve a take-home assignment or an on-site whiteboard exercise focusing on a complex design problem, requiring systems thinking and rapid ideation.

• Final Round: Could involve a broader group of stakeholders or senior leadership.

Portfolio Review Tips:

• Highlight Builder-Designer Skills: Explicitly showcase projects where you contributed to code or used AI tools extensively in your workflow. Show, don't just tell.

• Focus on Impact & Ambiguity: Select projects that demonstrate significant user impact and your ability to navigate complex, undefined problems. Quantify outcomes wherever possible.

• Demonstrate Systems Thinking: Clearly articulate how you approached designing scalable systems, interaction frameworks, or design components.

• Showcase Process & Rationale: Be prepared to walk through your entire design process for each case study, explaining the "why" behind your decisions.

• Tailor to Agentic Work: If possible, include projects related to AI, developer tools, or complex workflows that resonate with the Omnigent team's focus.

• Prepare for Codebase Discussion: Be ready to discuss your direct code contributions, the tools you used, and how you collaborated with engineers on implementation details.

Challenge Preparation:

• Anticipate AI/Agentic Problems: Practice thinking through problems related to human-AI collaboration, trust, control, and observability in AI-driven workflows.

• Systems Design Exercises: Prepare for challenges that require you to design complex systems with multiple interacting components.

• Prototyping & Ideation: Be ready to quickly sketch, wireframe, or prototype solutions to ambiguous problems.

• Cross-Functional Communication: Practice articulating design decisions clearly and concisely to technical and non-technical audiences.

📝 Enhancement Note: The interview process for a Staff-level designer, especially in a cutting-edge field like agentic AI, will be rigorous. Emphasis will be placed on not just design craft but also strategic thinking, technical aptitude (builder-designer), and the ability to operate autonomously and collaboratively.

🛠 Tools & Technology Stack

Primary Tools:

• Prototyping Tools: Figma, Sketch, Adobe XD, InVision, or similar for wireframing and interactive prototyping.

• Design Systems: Experience working with and contributing to established design systems; familiarity with component libraries and style guides.

• AI Tools: Regular use of AI tools in the design workflow (e.g., AI-powered ideation, content generation, code assistance for prototypes).

• Codebase Contribution: Proficiency in relevant coding languages (likely JavaScript/TypeScript, HTML, CSS for front-end) and willingness to work within a production codebase.

Analytics & Reporting:

• Familiarity with product analytics tools (e.g., Amplitude, Mixpanel, Google Analytics) to understand user behavior and inform design iterations.

• Ability to interpret data to identify pain points and opportunities for design improvement. CRM & Automation:

• While not a primary focus for this design role, understanding how user data flows from CRM and other systems can be beneficial for designing integrated experiences.

• Familiarity with project management and collaboration tools like Jira, Confluence, Asana.

📝 Enhancement Note: The explicit mention of "design directly in the codebase" is a significant indicator of the required technical skill set. Candidates should be prepared to discuss their experience with front-end development technologies and their comfort level working within a production engineering environment.

👥 Team Culture & Values

Operations Values:

• Innovation & Cutting-Edge Technology: A drive to work on the forefront of AI and data technology.

• Collaboration & Partnership: Strong emphasis on working closely with engineering and product teams to achieve shared goals.

• Builder Mentality: A proactive, hands-on approach to problem-solving and product development.

• User Focus & Empathy: Deep understanding of user needs, particularly those of technical users and developers.

• Data-Driven Decisions: Utilizing data and research to inform design choices and measure impact.

• Trust & Transparency: Building user trust in AI systems is paramount, influencing design decisions around clarity and control.

Collaboration Style:

• Integrated Teams: Designers are embedded within product and engineering teams, fostering a unified approach.

• Open Critique Culture: Encouraging constructive feedback and debate to elevate design quality.

• Prototyping as Communication: Using interactive prototypes as a common language to align stakeholders and explore ideas.

• Knowledge Sharing: Active participation in design reviews, sharing insights, and contributing to the collective knowledge base.

📝 Enhancement Note: The culture at Databricks, especially within a forward-looking team like Omnigent, likely values autonomy, intellectual curiosity, and a willingness to tackle challenging, ambiguous problems. The "builder-designer" aspect points to a culture that bridges traditional silos between design and engineering.

⚡ Challenges & Growth Opportunities

Challenges:

• Defining Novel Interaction Patterns: Creating intuitive and trustworthy user experiences for entirely new paradigms like agentic coding and multi-agent collaboration.

• Balancing Open Source vs. Enterprise Needs: Designing for a diverse user base, from individual developers in the open-source community to large enterprise teams with governance requirements.

• Building Trust in AI: Developing interaction models that foster user confidence and mitigate risks associated with autonomous AI agents.

• Technical Complexity: Working with advanced AI models and infrastructure requires a steep learning curve and continuous adaptation.

• Cross-Platform Consistency: Maintaining a cohesive and high-quality experience across desktop and mobile for complex functionalities.

Learning & Development Opportunities:

• AI & Agentic Systems Expertise: Become a leader in designing for the next generation of AI-powered workflows.

• Developer Tooling Mastery: Gain deep insights into the needs and workflows of developers and technical users.

• Strategic Design Leadership: Hone skills in shaping product strategy, defining UX principles, and influencing organizational direction.

• Advanced Prototyping & Implementation: Enhance skills in rapid prototyping and direct codebase contribution.

• Industry Exposure: Engage with the cutting edge of AI research and development within a leading tech company.

📝 Enhancement Note: The primary challenge lies in the novelty of the domain. Designing for agentic AI requires pioneering new interaction models and user experiences, which presents both a significant challenge and a unique growth opportunity.

💡 Interview Preparation

Strategy Questions:

• "How would you approach designing the core interaction for a user to supervise and intervene in a fleet of AI coding agents simultaneously?" (Focus on systems thinking, clarity, and control)

• "Describe a time you had to design for a complex, ambiguous problem where the technology or user needs were not well-defined. What was your process?" (Highlight ambiguity navigation, prototyping, and iterative approach)

• "How do you balance the needs of an open-source community with the requirements of enterprise customers when designing a platform?" (Focus on user segmentation, governance, and scalability)

• "What are the key principles for building user trust in AI agents, especially when they are performing critical tasks like coding?" (Emphasize transparency, error handling, and user control) Company & Culture Questions:

• "Why Databricks and why this role specifically? What excites you about agentic coding?" (Demonstrate genuine interest and alignment with Databricks' mission)

• "How do you see your 'builder-designer' skills contributing to the Omnigent team's success?" (Connect your technical abilities to the role's unique requirements)

• "Describe your ideal collaboration dynamic with product managers and engineers." (Showcase strong cross-functional partnership skills) Portfolio Presentation Strategy:

• Structure: For each project, clearly define: Problem -> Your Role -> Process -> Solution -> Impact/Outcome.

• Highlight Builder-Designer Aspect: Explicitly call out any code contributions, AI tool usage, or close engineering collaboration. If you can't show code directly, explain how you worked with engineers to implement designs.

• Focus on Systems: If a project involved building a design system, interaction framework, or complex interconnected components, dedicate time to explaining its architecture and benefits.

• Quantify Impact: Use metrics (e.g., increased adoption, reduced errors, improved efficiency) to demonstrate the success of your designs.

• Be Ready for Deep Dives: Prepare for detailed questions about your rationale, trade-offs, and alternative solutions considered.

📝 Enhancement Note: Preparation should focus on demonstrating a unique blend of strategic design thinking, hands-on technical ability (builder-designer), and the capacity to pioneer new user experiences in a rapidly evolving AI landscape.

📌 Application Steps

To apply for this Staff Product Designer position:

• Submit your application through the Databricks careers portal linked in the job posting.

• Tailor your resume: Emphasize experience with developer tools, AI/ML products, enterprise software, and direct codebase contributions. Highlight staff-level impact and leadership.

• Curate your portfolio: Select 1-2 projects that best showcase your end-to-end craft, systems thinking, builder-designer capabilities, and experience with complex/ambiguous problems. Ensure clear articulation of your process and impact.

• Prepare your presentation: Practice walking through your portfolio projects, focusing on the "why" behind your design decisions and your direct contributions. Be ready to discuss your experience with AI tools and coding.

• Research Databricks and Omnigent: Understand their mission, products, and the emerging field of agentic AI. Be prepared to articulate why you are a good fit for their culture and this specific role.

⚠️ 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.