Principal Software Engineer, Agentic UX

📍 Job Overview

Job Title: Principal Software Engineer, Agentic UX

Company: Workday

Location: Pleasanton, CA, United States

Job Type: Full Time

Category: Software Engineering / AI & Machine Learning

Date Posted: 2026-11-04T00:00:00

Experience Level: 10+ years

Remote Status: Hybrid

🚀 Role Summary

• This role is pivotal in shaping the future of Workday's intelligent agent capabilities, focusing on the user experience of conversational AI and ambient computing features.

• You will be instrumental in designing and delivering production-grade AI solutions, deeply integrated into Workday's core platform, impacting millions of users globally.

• This position requires a blend of advanced software engineering, AI-native development, and a strong understanding of user-centric design principles to bridge the gap between complex AI logic and intuitive user interfaces.

• You will operate within a high-trust, high-expectation environment, leading projects from conception through to deployment and ensuring the scalability, reliability, and responsible implementation of AI-driven user experiences.

📝 Enhancement Note: The job title "Principal Software Engineer, Agentic UX" and the description of "Agent Factory" indicate a highly specialized role focused on the intersection of AI, user experience, and enterprise software. This is not a typical front-end or back-end engineering role; it demands expertise in how AI agents interact with users and how to design those interactions seamlessly within a complex SaaS platform. The emphasis on "AI-native builder" and "bridging the gap between AI capabilities and user intent" suggests a need for engineers who can think about AI as a core component of the user interface, not just a backend service.

📈 Primary Responsibilities

• Design, develop, and deploy intuitive conversational AI experiences and ambient capabilities that define the user interaction model for Workday's intelligent agents.

• Architect and implement robust solutions that connect agentic logic directly to user-facing interfaces, ensuring a seamless and responsive user experience.

• Lead end-to-end feature ownership, from conceptualization and design to implementation, testing, and operationalization within a production SaaS environment.

• Collaborate closely with Product Managers, AI Engineers, Designers, and fellow Software Engineers in a cross-functional team setting to define and deliver innovative AI-powered features.

• Drive technical excellence by establishing and upholding best practices in software development, including DevOps, CI/CD, automated testing, and observability for AI systems.

• Mentor junior engineers, share technical expertise, and contribute to raising the overall technical proficiency and engineering standards within the Agent Factory pods.

• Contribute to architectural decisions concerning the scalability, reliability, and security of AI-driven user experiences operating at a global scale.

• Ensure the responsible and ethical application of AI by considering fairness, transparency, and user privacy in the design and implementation of agentic UX.

📝 Enhancement Note: The responsibilities highlight a senior-level individual contributor role with significant ownership and influence. The emphasis on "design and deliver," "own features end-to-end," and "lead projects" points to a Principal Engineer expected to drive technical direction and execution for key aspects of the agentic UX. The mention of "production-grade AI—deeply embedded into Workday’s platform—not research experiments" signifies a focus on robust, scalable, and maintainable solutions.

🎓 Skills & Qualifications

Education:

• While no specific degree is mandated, a Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field is highly recommended, given the complexity and seniority of the role. Experience:

• A minimum of 12+ years of progressive experience in software engineering is required.

• A strong track record of 7+ years in building and shipping user-facing software products is essential.

• A minimum of 3+ years of dedicated experience in building conversational or agentic AI applications is a core requirement.

• Proven experience of 5+ years in leading technical projects or teams, demonstrating leadership and mentorship capabilities. Required Skills:

• Proficiency in TypeScript and React: Essential for building modern, dynamic user interfaces and full-stack applications.

• Expertise in Python and FastAPI: Critical for backend development, API creation, and integration with AI services.

• Experience building Conversational or Agentic AI Applications: Demonstrated ability to develop systems that understand and respond to user intent through dialogue or agentic actions.

• Strong understanding of SaaS product development: Experience in building and operating software within a Software-as-a-Service model.

• Cloud Environment Experience (AWS Preferred): Familiarity with cloud infrastructure, services, and deployment strategies, particularly on AWS.

• Distributed Systems Architecture: Knowledge of designing, building, and operating scalable, resilient distributed systems.

• Software Development Best Practices: Deep understanding and practical application of DevOps principles, CI/CD pipelines, automated testing frameworks, and observability tools.

• Containerization Technologies (Docker, Kubernetes): Experience in deploying and managing applications using containerization and orchestration platforms.

• Project/Team Leadership: Proven ability to lead technical initiatives, mentor engineers, and drive project success.

Preferred Skills:

• UX/UI Design Principles: Experience collaborating with product designers or a portfolio demonstrating a strong grasp of high-quality UX/UI design.

• Elasticsearch: Familiarity with search and analytics engines.

• Java (Backend): Exposure to Java can be beneficial for understanding Workday's broader backend ecosystem.

• Agile Methodologies: Proven success working in fast-paced, agile development environments.

• Cross-functional Collaboration: Ability to work effectively with both technical and non-technical stakeholders.

• Problem-Solving in Ambiguity: Comfort and skill in translating complex, ambiguous problems into clear, actionable technical solutions.

• Inclusive and Team-Oriented Environment: Commitment to fostering a positive, collaborative team culture.

📝 Enhancement Note: The "Other Qualifications" section heavily implies a need for practical, hands-on experience with modern cloud-native technologies and established software engineering practices. The emphasis on "shipping user-facing software products" and "conversational or agentic AI applications" suggests that candidates should be prepared to showcase specific projects and contributions in these areas, rather than just theoretical knowledge. The leadership experience requirement is a strong indicator of the Principal Engineer's expected contribution to team growth and technical direction.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrated AI-Native UX Projects: Showcase projects where you've directly connected AI/agentic logic to user interfaces, illustrating how you translated complex AI capabilities into intuitive user experiences.

• Shipped User-Facing Products: Evidence of successfully designing, building, and launching user-facing software products, highlighting your role and impact.

• Conversational AI or Agentic Flow Design: Examples of designing and implementing conversational flows, dialogue management, or agentic decision-making processes that led to positive user outcomes.

• Scalable System Architecture: Portfolio pieces that demonstrate your ability to design and implement scalable, reliable, and performant distributed systems, ideally in a SaaS context.

• Technical Leadership Examples: Projects where you led a technical initiative, mentored team members, or significantly influenced technical direction.

Process Documentation:

• Workflow Design and Optimization: Evidence of designing or optimizing complex workflows, particularly those involving AI or automated processes, to improve efficiency and user satisfaction.

• System Implementation and Automation: Documentation of systems you've implemented, with a focus on automation strategies, CI/CD pipelines, and infrastructure-as-code practices.

• Performance Measurement and Analysis: Examples of how you've instrumented systems for observability, defined key performance indicators (KPIs) for AI features, and used data to drive improvements.

• Cross-functional Collaboration Artifacts: Examples of how you've collaborated with product management, design, and other engineering teams, potentially including design documents, API specifications, or post-mortem analyses.

📝 Enhancement Note: For a Principal Engineer role, especially one focused on Agentic UX, the portfolio is critical. It's not just about listing technologies but demonstrating the application of those technologies to solve complex problems at the intersection of AI and user experience. Candidates should be prepared to articulate the "why" behind their technical choices, the trade-offs made, and the measurable impact of their work. The emphasis on "shipping products" and "production-grade AI" means focusing on real-world solutions rather than theoretical concepts.

💵 Compensation & Benefits

Salary Range:

• Primary Location (Pleasanton, CA): $246,000 USD - $370,000 USD annually.

• Additional US Locations: $206,000 USD - $370,000 USD annually.

Benefits:

• Workday Bonus Plan: Eligibility for a performance-based bonus.

• Role-Specific Commission/Bonus: Potential for additional bonuses tied to specific role objectives.

• Annual Refresh Stock Grants: Opportunity to receive equity awards periodically.

• Comprehensive Health, Dental, and Vision Insurance: Standard benefits package.

• Retirement Savings Plan (401k) with Company Match: Support for long-term financial planning.

• Paid Time Off (PTO): Including vacation, sick leave, and holidays.

• Parental Leave: Generous policies for new parents.

• Professional Development: Opportunities for learning, training, and attending industry conferences.

• Employee Assistance Program (EAP): Support for personal and professional well-being.

• Life and Disability Insurance: Protection for employees and their families.

Working Hours:

• The standard working hours are 40 hours per week.

• The role operates under a Hybrid work arrangement, requiring employees to spend at least 50% of their time each quarter in the office or in the field. This allows for flexibility in scheduling while ensuring collaborative time.

📝 Enhancement Note: The salary range provided is for base pay. The total compensation package will likely be significantly higher due to the bonus plan, stock grants, and other benefits typical for a Principal Engineer role at a Fortune 500 company like Workday. The Hybrid work model is clearly defined, emphasizing intentional in-person collaboration at least half the time per quarter, which is a key detail for candidates evaluating work arrangements.

🎯 Team & Company Context

🏢 Company Culture

Industry: Enterprise Software (AI Platform for Human Capital Management, Financial Management, and Planning)

Company Size: Fortune 500 company with a large global employee base (likely 10,000+ employees).

Founded: 2005. Workday has a history of innovation in cloud-based enterprise applications, evolving from HR and finance to a broader AI platform.

Team Structure:

• Agent Factory Pods: Small, senior, cross-functional teams composed of Product Leaders, AI Engineers, and Full-Stack Builders.

• Reporting Structure: Principal Engineers typically report to an Engineering Manager or Director, with significant autonomy and influence within their pod and on their technical domain.

• Cross-functional Collaboration: High emphasis on tight collaboration across disciplines (Product, Design, AI Engineering, Full-Stack Engineering) within each pod and with broader platform teams.

Methodology:

• Production-Grade AI: Focus on building and shipping real, deeply embedded AI solutions into the core platform, not experimental research.

• End-to-End Ownership: Teams are responsible for problems from inception to deployment and operation.

• Iterative Development: Agile and team-first environment valuing strong engineering practices and continuous learning.

• Data-Driven Decision Making: Implied by the nature of AI development and Workday's platform, focusing on metrics and user feedback.

• AI-Native Builder Approach: Emphasizing building intelligence directly into the user experience.

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

📝 Enhancement Note: Workday's culture is described as rooted in integrity, empathy, and shared enthusiasm, emphasizing "meaningful work" and "bold ideas." The "Agent Factory" initiative represents a strategic investment in AI, suggesting a forward-thinking and innovative environment. The company's established presence as a Fortune 500 leader provides stability and resources, while the "Agent Factory" teams aim to foster a startup-like agility and impact.

📈 Career & Growth Analysis

Operations Career Level: Principal Software Engineer. This is a senior individual contributor role, typically one or two levels below Staff or Distinguished Engineer, signifying a high degree of technical expertise, leadership, and impact.

Reporting Structure: Likely reports to an Engineering Manager or Director within the AI or Platform organization. The role involves significant autonomy in technical decision-making within their domain and team.

Operations Impact: This role directly influences the user experience of Workday's AI platform, impacting how millions of users interact with Workday's core products. Success here translates to increased user adoption, efficiency gains for customers, and a competitive edge for Workday in the AI-driven enterprise software market.

Growth Opportunities:

• Technical Specialization: Deepen expertise in conversational AI, agentic systems, large language models (LLMs), and AI/ML deployment at scale.

• Leadership Development: Transition into technical leadership roles, such as Tech Lead for a pod, mentoring other senior engineers, or influencing broader architectural decisions.

• Cross-functional Exposure: Gain broader exposure to product strategy, AI research, and platform engineering across Workday.

• Architectural Influence: Contribute to the design and evolution of Workday's AI platform architecture.

• Industry Recognition: Potential to contribute to publications, conferences, or open-source projects related to AI and enterprise software.

📝 Enhancement Note: The "Principal" title signifies a role focused on technical leadership, mentorship, and driving significant technical initiatives. Growth will likely involve expanding scope, influencing broader architectural strategies, and potentially moving towards Staff Engineer or management tracks if desired, though the primary path is deep technical contribution and leadership.

🌐 Work Environment

Office Type: Hybrid work model. Workday emphasizes combining the benefits of in-person collaboration with remote flexibility.

Office Location(s): Pleasanton, CA is the primary location. Additional US locations are also mentioned, indicating a distributed team structure within the US.

Workspace Context:

• Collaborative Environment: The hybrid model is designed to foster deeper connections and a strong community through intentional in-person time.

• Technology and Tools: Access to Workday's robust internal toolchain, cloud infrastructure (AWS), and development environments.

• Team Interaction: Opportunities for close collaboration with immediate pod members (Product, Design, AI, Full-Stack Engineers) during in-office days, as well as broader engineering and product teams.

Work Schedule:

• Standard 40-hour work week.

• Flexible scheduling is encouraged, provided that at least 50% of time per quarter is spent in the office or field to ensure collaborative engagement.

📝 Enhancement Note: The "Flex Work" approach at Workday aims to provide a balanced work environment. Candidates should be comfortable with the expectation of spending a significant portion of their time in the office to facilitate collaboration, team building, and knowledge sharing, which is crucial for complex, cross-functional projects like those in Agent Factory.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: HR or Recruiter screen to assess basic qualifications and alignment with the role.

• Technical Phone Screen: May involve a coding exercise or discussion of technical concepts related to software engineering, AI, and distributed systems.

• On-site/Virtual Interviews (Multiple Rounds):

  • Coding/System Design Interviews: Focus on practical problem-solving, algorithm design, and architectural thinking, potentially involving live coding or system design scenarios related to agentic UX or scalable systems.
  • Behavioral Interviews: Assessing leadership, collaboration, problem-solving approach, and cultural fit, aligned with Workday's values.
  • Technical Deep Dive: Discussion of past projects, portfolio items, and specific expertise in AI, UX, and relevant technologies.
  • Hiring Manager/Team Lead Interview: Final assessment of fit, vision, and alignment with the team's goals.

Portfolio Review Tips:

• Highlight AI-UX Integration: Clearly articulate your role in bridging AI capabilities with user interfaces. Show how you translated user needs and AI logic into concrete product features.

• Showcase Impactful Projects: Select 2-3 key projects that best represent your experience in building user-facing products, conversational AI, or scalable systems. Quantify achievements where possible (e.g., performance improvements, user adoption rates).

• Detail Technical Choices: Be prepared to explain the rationale behind your technology choices, architectural decisions, and trade-offs made, especially concerning AI integration, scalability, and user experience.

• Demonstrate Leadership: Include examples of technical leadership, mentorship, or driving initiatives.

• Prepare for Technical Questions: Be ready to discuss specific technologies like TypeScript, React, Python/FastAPI, AWS, Docker, Kubernetes, and distributed systems design.

Challenge Preparation:

• System Design Challenge: Expect a challenge that requires designing a scalable system, potentially involving AI components, user interaction, and data processing. Focus on architecture, scalability, reliability, and trade-offs.

• Coding Challenge: Prepare for problems that test your proficiency in TypeScript/React or Python, focusing on clean, efficient, and well-tested code.

• AI/UX Scenario Discussion: Be ready to discuss how you would approach designing an agentic UX for a specific Workday scenario, considering user intent, AI capabilities, and interface design.

📝 Enhancement Note: The interview process for a Principal Engineer at Workday will be rigorous, emphasizing both deep technical skills and strong leadership/collaboration abilities. A well-curated portfolio that directly addresses the "Agentic UX" aspect is paramount. Candidates should prepare to discuss their contributions in detail, demonstrating a strategic understanding of how AI and UX intersect to deliver business value.

🛠 Tools & Technology Stack

Primary Tools:

• Programming Languages: TypeScript, Python, Java (backend exposure beneficial).

• Frontend Frameworks: React.

• Backend Frameworks: FastAPI (preferred), potentially others.

• Cloud Platform: AWS (preferred), including services for compute, storage, databases, and AI/ML.

• Containerization: Docker.

• Orchestration: Kubernetes.

Analytics & Reporting:

• Observability Tools: For monitoring system health, performance, and user interactions (e.g., Datadog, Prometheus, Grafana).

• Logging Frameworks: For capturing system events and debugging.

• Data Analysis Tools: For understanding user behavior and AI performance.

CRM & Automation:

• Workday Platform: Deep integration with Workday's existing enterprise software ecosystem.

• CI/CD Tools: Jenkins, GitLab CI, GitHub Actions, or similar for automated build, test, and deployment pipelines.

• Testing Frameworks: Jest, Mocha, Pytest, or similar for unit, integration, and end-to-end testing.

• Version Control: Git.

📝 Enhancement Note: The technology stack is modern and cloud-native, with a strong emphasis on TypeScript/React for the frontend and Python/FastAPI for the backend. Experience with AWS, Docker, and Kubernetes is crucial for operating in a SaaS environment. Familiarity with observability and CI/CD practices is expected for a Principal Engineer responsible for shipping and operating production systems.

👥 Team Culture & Values

Operations Values:

• Integrity, Empathy, Shared Enthusiasm: Core Workday values that guide interactions and decision-making.

• Curiosity and Courage: Encouragement to explore new ideas and take calculated risks.

• Focus on Impact: Driving meaningful work that benefits customers and the organization.

• Collaboration and Belonging: Fostering an inclusive environment where everyone feels valued and empowered.

• Continuous Improvement: Commitment to learning, growth, and refining processes and products.

Collaboration Style:

• Team-First Environment: Emphasis on collective success and mutual support within the "Agent Factory" pods and the broader engineering organization.

• Cross-functional Integration: Tight collaboration between engineering, product, and design is fundamental to success.

• Knowledge Sharing: Active sharing of expertise, best practices, and lessons learned across teams.

• Iterative Feedback Loops: Openness to feedback and continuous refinement of solutions.

📝 Enhancement Note: The culture at Workday, particularly within new initiatives like "Agent Factory," is likely a blend of established corporate values and the agile, innovative spirit required for cutting-edge AI development. Candidates should demonstrate alignment with Workday's core values and a proactive, collaborative approach to teamwork.

⚡ Challenges & Growth Opportunities

Challenges:

• Bridging AI Complexity and User Simplicity: The primary challenge is translating advanced, often abstract, AI capabilities into intuitive, reliable, and easy-to-use user experiences.

• Scalability and Performance: Ensuring that agentic AI features perform consistently and reliably for millions of users across Workday's global platform.

• Navigating Ambiguity: Working in a rapidly evolving AI landscape and defining product direction with incomplete information.

• Ethical AI Implementation: Ensuring that AI agents are fair, unbiased, transparent, and respect user privacy, adhering to Workday's commitment to responsible AI.

• Integration with Existing Systems: Seamlessly integrating new AI-driven UX components into Workday's extensive enterprise software suite.

Learning & Development Opportunities:

• Deep Dive into Conversational AI & Agentic Systems: Opportunities to become a subject matter expert in cutting-edge AI technologies and their application in enterprise software.

• Advanced Cloud and Distributed Systems Training: Further development of skills in building and operating large-scale, resilient cloud-native applications.

• Leadership and Mentorship Programs: Formal and informal opportunities to hone leadership skills, mentor junior engineers, and influence technical strategy.

• Industry Conferences and Certifications: Support for attending relevant AI, software engineering, and UX conferences to stay abreast of industry trends.

📝 Enhancement Note: The challenges presented are inherent to developing advanced AI features in a large enterprise context. The growth opportunities are substantial, offering a path for deep technical mastery and leadership within a critical and rapidly expanding area of Workday's product strategy.

💡 Interview Preparation

Strategy Questions:

• AI-UX Integration: "Describe a complex AI capability and how you would translate it into a simple, intuitive user experience. What are the key considerations for the interface and interaction design?" (Prepare a case study from your portfolio or a hypothetical scenario).

• Scalable System Design: "Design a system for real-time conversational AI interactions that can scale to millions of concurrent users. What are the core components, potential bottlenecks, and how would you ensure reliability?" (Focus on architecture, microservices, data flow, and fault tolerance).

• Technical Leadership & Mentorship: "How do you approach mentoring junior engineers or leading technical initiatives? Describe a time you influenced technical direction within a team." (Be ready with specific examples of leadership and collaboration).

Company & Culture Questions:

• Workday Values: "How do Workday's values of integrity, empathy, and shared enthusiasm translate into your approach to software development and teamwork, especially in an AI context?" (Research Workday's values and prepare examples).

• Hybrid Work: "How do you ensure effective collaboration and productivity within a hybrid work environment, particularly when working on complex, cross-functional AI projects?" (Highlight strategies for communication and team cohesion).

• AI Ethics: "What are the most critical ethical considerations when building agentic AI experiences, and how would you address them in your designs and implementations?" (Demonstrate awareness of responsible AI principles).

Portfolio Presentation Strategy:

• Focus on Impact: For each project, clearly articulate the problem, your solution, your specific contributions, the technologies used, and the measurable impact or outcome.

• Quantify Achievements: Use metrics whenever possible (e.g., performance improvements, user satisfaction scores, adoption rates, reduction in manual effort).

• Tell a Story: Structure your presentation to tell a compelling story about how you tackled a challenge, innovated, and delivered value.

• Demonstrate Technical Depth: Be prepared to dive deep into the technical details of your projects, explaining design choices and trade-offs.

• Highlight AI-UX Connection: Explicitly draw connections between your AI/ML work and the resulting user experience.

📝 Enhancement Note: The interview preparation should focus on demonstrating not just technical prowess but also strategic thinking, leadership potential, and a deep understanding of how to deliver sophisticated AI features that provide real user value within an enterprise context. The portfolio is the cornerstone of the interview process for this role.

📌 Application Steps

To apply for this Principal Software Engineer, Agentic UX position:

• Submit your application through the official Workday Careers portal.

• Portfolio Customization: Tailor your resume and any linked portfolio (e.g., GitHub, personal website) to prominently feature projects demonstrating experience with conversational AI, agentic UX, TypeScript/React, Python/FastAPI, and scalable SaaS architectures.

• Resume Optimization: Ensure your resume clearly highlights your 12+ years of software engineering experience, 7+ years in shipping user-facing products, and 3+ years specifically in conversational/agentic AI. Quantify achievements and leadership experiences.

• Interview Preparation: Thoroughly review your past projects, focusing on those that best showcase your ability to connect AI logic with user interfaces. Prepare to discuss technical challenges, solutions, and the impact of your work. Practice system design and coding problems relevant to the technologies mentioned.

• Company Research: Understand Workday's mission, AI strategy, and company values. Familiarize yourself with their enterprise software offerings and the "Agent Factory" initiative to articulate how your skills and experience align with their goals.

⚠️ 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.