AI Native - UX - Software Engineer

📍 Job Overview

Job Title: AI Native - UX - Software Engineer

Company: Salesforce

Location: San Francisco, California, United States (with potential for full remote)

Job Type: Full-time

Category: Software Engineering / UX Engineering

Date Posted: September 14, 2026

Experience Level: Mid-Senior Level (5-10 years)

Remote Status: Hybrid/Remote Eligible

🚀 Role Summary

• Architect and develop end-to-end control-plane and telemetry experiences for AI-driven agentic systems, focusing on human oversight and intervention.

• Translate complex, data-intensive, and distributed systems into intuitive, high-trust user interfaces that enhance explainability and usability.

• Design and implement information architecture and visualization strategies to make high-dimensional and temporal system states easily understandable.

• Create nuanced interaction designs for human-agent collaboration, defining feedback loops, state-reversal mechanisms, and sensible defaults.

• Drive the full lifecycle from UX prototyping to production-grade code, ensuring high-quality user experiences in an AI-native product environment.

📝 Enhancement Note: This role is a unique blend of deep systems engineering and sophisticated UX/information design, specifically tailored for the emerging field of AI agents and human-agent interaction. The emphasis on "AI Native," "Agentforce," and "Agentic Engineering" indicates a focus on building systems where AI agents perform tasks, and humans are primarily responsible for supervision, intent expression, and understanding system behavior. The "control-plane" and "telemetry" aspects point towards building the interfaces that allow users to manage, monitor, and diagnose complex AI operations.

📈 Primary Responsibilities

• End-to-End Control-Plane & Telemetry Surfaces: Architect, design, and build domain models, APIs, and high-density visual interfaces for expressing intent, supervising AI agents, and diagnosing anomalies.

• Information Architecture & Visualization: Apply core information design principles (e.g., hierarchy, progressive disclosure, small multiples, data provenance) to ensure high-dimensional, temporal, and non-deterministic system states are instantly understandable to users.

• Interaction Design for Human-Agent Systems: Design sophisticated interaction models, feedback loops, and state-reversal mechanisms for automated workflows, defining micro-interactions, sensible default states, and clear affordances for human oversight.

• Human-in-the-Loop Frameworks: Intentionally balance synchronous approvals, asynchronous audit trails, and automated guardrails, making informed decisions based on risk, uncertainty, and reversibility of AI actions.

• UX Prototyping to Production: Rapidly prototype new interaction models, evaluate them against technical constraints, and ship production-grade code that elevates the bar for explainability and usability in AI-driven products.

• Systems & Platform Engineering: Leverage deep understanding of distributed architecture, state management, consistency models, asynchronous failure modes, and observability principles in the design and implementation of interfaces.

📝 Enhancement Note: The responsibilities highlight a "systems-to-interface" mandate. This implies not just building front-end components but also defining the underlying data models, APIs, and backend logic that support complex AI agent interactions and provide the necessary telemetry for human understanding and control. The emphasis on "AI-native product thinking" suggests a need to go beyond traditional UI/UX paradigms to design for scenarios where agents are primary actors.

🎓 Skills & Qualifications

Education: While not explicitly stated, a Bachelor's or Master's degree in Computer Science, Human-Computer Interaction (HCI), or a related field is typically expected for senior engineering roles at Salesforce.

Experience: 5-10 years of professional software engineering experience, with a strong emphasis on building complex systems and user-facing experiences.

Required Skills:

• Systems & Platform Engineering: Deep understanding of distributed architecture, state management, consistency models, asynchronous failure modes, and observability.

• Advanced UX & Information Design: Strong proficiency in information architecture, interaction design, and data visualization. Familiarity with foundational thinkers in these fields (e.g., Edward Tufte, Bret Victor, Tamara Munzner, Ben Shneiderman).

• Full-Stack Execution: Ability to work across backend system concepts (events, policies, lineages) and craft fine-grained, production-ready user experiences in code.

• AI-Native Product Thinking: Expertise designing interfaces for agentic execution beyond simple chat/copilot flows, focusing on delegation, governance, context-awareness, and trust.

• Nuanced Interaction Design: Mastery of balancing friction and fluidity—knowing precisely when to insert a confirmation step, how to clearly show system causality, and how to represent uncertainty effectively.

• API Development: Experience designing and implementing robust APIs for data exchange and system control.

• UX Prototyping: Ability to rapidly create and iterate on prototypes to test and validate interaction models.

Preferred Skills:

• Experience building developer platforms, observability systems, control planes, or investigative analytics tools.

• Background in human-computer interaction (HCI), design systems, or data visualization for enterprise/safety-critical software.

• Track record of building tool-using AI models, agent supervision interfaces, or zero-to-one developer tools.

📝 Enhancement Note: The "You're Our Person If" section directly translates into required skills. The "Even Better If" section lists preferred qualifications that would make a candidate stand out. The emphasis on specific design thinkers indicates a high bar for conceptual understanding in information design.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Systems Design Case Studies: Examples showcasing your ability to architect and build robust, scalable distributed systems, including details on state management, fault tolerance, and observability strategies.

• UX/Information Design Projects: Demonstrations of complex information visualization, interaction design for intricate workflows, and how you translated technical concepts into user-friendly interfaces.

• Human-Agent Interaction Design: Examples of interfaces or concepts designed for human oversight, control, or understanding of automated systems, showcasing an understanding of trust, explainability, and intervention mechanisms.

• Full-Stack Implementations: Prototypes or production code that exhibits proficiency across backend system logic and front-end user experience development.

• AI/Agentic System Exposure: Projects that demonstrate an understanding of designing for AI-driven processes, beyond basic chatbots, focusing on governance, context, or delegation.

Process Documentation:

• Workflow Optimization Examples: Showcase how you've analyzed existing workflows and implemented improvements through system design or UX enhancements, with quantifiable results.

• System Architecture Diagrams: Visual representations of complex systems you've designed, illustrating components, data flow, and interaction patterns.

• User Journey Maps & Wireframes/Prototypes: Demonstrations of your UX design process, from understanding user needs to creating interactive prototypes for complex systems.

• Technical Documentation Snippets: Examples of how you document complex system behaviors, API specifications, or interaction patterns for clarity and maintainability.

📝 Enhancement Note: For a role like this, a portfolio is crucial. It needs to demonstrate not just coding ability but also a deep understanding of complex systems and how to make them accessible and controllable via sophisticated UX. The ability to show a complete process from understanding system requirements to designing and implementing user-facing solutions will be key.

💵 Compensation & Benefits

Salary Range:

• General US Range: $197,300 - $313,700 annually (base salary).

• Select Metropolitan Areas (SF/NYC): $237,700 - $344,700 annually (base salary).

Note: These ranges represent base salary only and do not include company bonus, incentive compensation (for sales roles), equity, or benefits. The specific salary offered will depend on factors such as location, job level, job-related knowledge, skills, and experience.

Benefits:

• Time off programs

• Medical insurance

• Dental insurance

• Vision insurance

• Mental health support

• Paid parental leave

• Life insurance

• Disability insurance

• 401(k)

• Employee stock purchasing program

• Potential for company bonus, incentive compensation, and equity.

Working Hours: 40 hours per week (standard full-time). Flexibility may be available, especially for remote-eligible candidates, but core responsibilities will require dedicated engagement.

📝 Enhancement Note: The salary ranges provided are specific to the US market and highlight a significant premium for roles located in or near major tech hubs like San Francisco and New York City. This reflects the high demand for specialized engineering talent in these regions. The inclusion of "AI Native" and "Agentforce" in the job title suggests that compensation may also be benchmarked against specialized AI/ML engineering roles, which often command higher salaries. The note about "fully remote employee" for the right person indicates potential for remote work, which can influence location-based salary adjustments.

🎯 Team & Company Context

🏢 Company Culture

Industry: Enterprise Software, Cloud Computing, CRM, Artificial Intelligence (AI). Salesforce is a leader in AI-driven CRM solutions, transforming how businesses connect with their customers.

Company Size: Large Enterprise (approx. 70,000+ employees globally). This indicates a structured environment with established processes, ample resources, and opportunities for large-scale impact, but also potentially more complex decision-making hierarchies.

Founded: 1999. Salesforce has a long history of innovation and market leadership, evolving significantly with cloud and now AI technologies.

Team Structure:

• Agentforce Focus: The role is within "Agentforce," Salesforce's initiative focused on the future of AI and agentic systems. This suggests a dedicated, forward-thinking team working on cutting-edge AI product development.

• Cross-Functional Collaboration: The role requires close collaboration with product management, other engineering teams (backend, AI/ML), and UX design teams.

• Reporting: Likely reports into a Senior Engineering Manager or Director within the Agentforce or a related AI/Platform engineering group.

Methodology:

• Agile Development: Salesforce typically employs agile methodologies for software development, emphasizing iterative development, collaboration, and rapid feedback loops.

• Data-Driven Decision Making: A strong emphasis on using data and metrics to inform product development, system design, and user experience improvements.

• Focus on Trust and Explainability: Given the AI focus, there's a cultural emphasis on building trustworthy, secure, and explainable AI systems.

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

📝 Enhancement Note: Salesforce's "Trailblazer" culture emphasizes innovation, customer success, and a strong set of core values. The specific mention of "Agentforce" and "AI Native" suggests this team is at the forefront of the company's AI strategy, likely attracting engineers who are passionate about shaping the future of AI-powered software and human-AI collaboration.

📈 Career & Growth Analysis

Operations Career Level: This is a Senior Software Engineer role with a specialized focus on UX and AI-native systems. It sits at the intersection of deep technical expertise in distributed systems and advanced skills in user interface design and human-computer interaction, particularly in the context of AI agents.

Reporting Structure: The role likely reports to a Senior Engineering Manager or Director responsible for AI platform development or agentic systems. The team is expected to be highly collaborative, working closely with product managers, designers, and other engineers.

Operations Impact: This role has a direct impact on how users interact with and control sophisticated AI agents. It's crucial for building trust, ensuring effective supervision, and enabling users to understand complex AI behaviors, thereby directly influencing the adoption and success of Salesforce's AI offerings.

Growth Opportunities:

• Technical Specialization: Deepen expertise in distributed systems, AI/agentic technologies, and advanced UX/information design for complex systems.

• Leadership Development: Potential to grow into a Tech Lead or Principal Engineer role, guiding architectural decisions and mentoring junior engineers.

• Cross-Functional Exposure: Opportunity to work closely with product management, research, and other engineering disciplines, broadening understanding of the product lifecycle.

• Impact on Future AI Products: Contribute to shaping the next generation of AI-powered enterprise software at a leading tech company.

📝 Enhancement Note: The "rare systems-to-interface role" description suggests this position offers a unique opportunity to bridge two critical disciplines. For an operations professional interested in the underlying technology that drives GTM efficiency or customer success platforms, understanding how complex systems are built and made usable is paramount. This role provides that insight at a very advanced level.

🌐 Work Environment

Office Type: Salesforce operates a modern, collaborative office environment. The San Francisco office is a significant hub. However, the role is also eligible for full remote work for the right candidate, indicating flexibility.

Office Location(s): While the primary posting is San Francisco, California, a comprehensive list of other potential US locations is provided, including Palo Alto, Chicago, Boston, New York City Metro, Seattle, and others. This suggests a distributed team structure is possible.

Workspace Context:

• Collaborative Spaces: Offices are designed to foster collaboration with open workspaces, meeting rooms, and common areas.

• Tools & Technology: Access to state-of-the-art development tools, cloud infrastructure, and internal platforms.

• Team Interaction: Opportunities for regular team meetings, design reviews, and cross-functional syncs, both in-person and virtually.

Work Schedule: Standard 40-hour work week. While core hours may apply, there's an expectation of flexibility and dedication to meeting project deadlines, especially for a role that bridges backend and frontend development.

📝 Enhancement Note: The explicit mention of "Please note for the right person, we would consider a fully remote employee" is significant. For candidates prioritizing remote work, this opens up possibilities beyond the primary listed location, though it might still require occasional travel to key offices for critical meetings or team events.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: Likely a recruiter screen to assess basic qualifications, interest, and cultural fit.

• Technical Phone Screen: A focused interview with an engineer to evaluate core systems engineering and UX design principles, potentially including coding challenges.

• On-Site (or Virtual) Loop: Multiple interviews covering:

  • Systems Design: Deep dive into architecting complex distributed systems.
  • UX/Information Design: Discussions on your approach to information architecture, data visualization, and interaction design for complex scenarios.
  • Coding/Problem Solving: Hands-on coding exercises, potentially focused on data structures, algorithms, or API implementation.
  • Behavioral/Situational: Assessing your experience with human-agent systems, collaboration, and problem-solving approach.
  • Portfolio Review: A dedicated session to walk through your most relevant projects.

• Hiring Manager Interview: Final discussion to assess overall fit, career aspirations, and alignment with team goals.

Portfolio Review Tips:

• Curate Selectively: Focus on 2-3 projects that most directly showcase your ability to handle complex systems and translate them into intuitive UX, especially for AI/agentic contexts.

• Highlight the "Why": For each project, clearly articulate the problem, your role, the technical challenges, the UX challenges, your design decisions, and the quantifiable outcomes or impact.

• Showcase Process: Demonstrate your thought process, from initial requirements gathering and system design to UX research, prototyping, and final implementation. Include diagrams, wireframes, and code snippets where appropriate.

• Emphasize AI/Agentic Experience: If you have experience with AI, machine learning, or agent-based systems, make sure these projects are prominent and highlight your understanding of their unique interaction patterns.

• Prepare for Deep Dives: Be ready to discuss the technical details of your systems architecture and the rationale behind your UX/information design choices.

Challenge Preparation:

• Systems Design: Practice designing scalable, fault-tolerant systems. Consider topics like API design, data consistency, caching, and load balancing.

• UX/Information Design: Review principles of information hierarchy, visual encoding, interaction patterns, and usability testing. Think about how to represent uncertainty, causality, and high-dimensional data.

• Coding: Brush up on data structures, algorithms, and common programming paradigms. Practice coding in your primary language (likely Java, Python, or JavaScript/TypeScript).

• AI/Agentic Concepts: Familiarize yourself with current trends in AI agents, human-in-the-loop systems, prompt engineering, and AI explainability.

📝 Enhancement Note: The emphasis on a "rare systems-to-interface role" means interviewers will be looking for a candidate who can think holistically about the entire stack, from backend data structures to front-end interactions, and specifically how these elements support human understanding and control of AI agents. The portfolio review will be a critical component.

🛠 Tools & Technology Stack

Primary Tools:

• Programming Languages: Likely Java, Python, or JavaScript/TypeScript for backend and frontend development.

• Cloud Platforms: Salesforce utilizes its own cloud infrastructure, but familiarity with AWS, Azure, or GCP concepts is beneficial.

• Frontend Frameworks: React, Angular, or Vue.js are common, though Salesforce may use proprietary frameworks.

• Backend Technologies: Experience with microservices architecture, distributed databases, and message queues (e.g., Kafka, RabbitMQ).

Analytics & Reporting:

• Telemetry & Observability Tools: Experience with tools like Splunk, Datadog, Prometheus, or Grafana for monitoring system performance and diagnosing issues.

• Data Visualization Libraries: D3.js, Chart.js, or similar libraries for building custom visualizations.

CRM & Automation:

• Salesforce Platform: While not explicitly required for this engineering role, understanding the Salesforce ecosystem can be advantageous.

• API Development Tools: Postman, Swagger/OpenAPI for API design and testing.

• CI/CD Tools: Jenkins, GitLab CI, CircleCI for automated builds and deployments.

📝 Enhancement Note: The role requires proficiency across the stack, from backend systems and APIs to frontend UX implementation. The emphasis on "telemetry" and "observability" suggests a need for experience with tools that provide deep insights into system behavior and performance, crucial for understanding AI agent operations.

👥 Team Culture & Values

Operations Values:

• Innovation & Trailblazing: A culture that encourages pushing boundaries and exploring new technologies, especially in AI and agentic systems.

• Customer Success: A core Salesforce value, emphasizing building products that genuinely help customers achieve their goals.

• Trust & Transparency: Critical for AI systems, this value promotes building reliable, secure, and explainable technologies.

• Equality & Inclusion: Salesforce is committed to fostering a diverse and inclusive workplace.

• Efficiency & Impact: Driving results and making a tangible impact through well-designed systems and user experiences.

Collaboration Style:

• Cross-Functional Partnership: Engineers are expected to work closely with product managers, designers, and other engineering teams to bring ideas to fruition.

• Data-Informed Design: Decisions are often backed by data and user research, fostering a collaborative approach to problem-solving.

• Open Communication: Encouragement of direct feedback and open discussion to refine designs and technical solutions.

• Mentorship & Learning: A culture that supports knowledge sharing and continuous learning, especially in rapidly evolving fields like AI.

📝 Enhancement Note: The "Agentforce" team likely embodies Salesforce's core values with an even stronger emphasis on innovation, future-proofing, and the ethical considerations surrounding AI. Collaboration will be key to bridging the gap between complex AI capabilities and user needs.

⚡ Challenges & Growth Opportunities

Challenges:

• Bridging Systems and UX: The primary challenge is translating highly complex, abstract, and data-intensive distributed systems and AI agent behaviors into interfaces that are intuitive, trustworthy, and actionable for human users.

• Designing for Uncertainty: Developing interfaces that effectively communicate the inherent uncertainty and non-deterministic nature of AI agents, enabling informed human judgment and intervention.

• Rapidly Evolving AI Landscape: Staying abreast of the fast-paced advancements in AI and agentic technologies to ensure the designed interfaces remain relevant and effective.

• Balancing Automation and Control: Finding the optimal balance between agent autonomy and human oversight, designing interfaces that facilitate seamless delegation, supervision, and intervention.

Learning & Development Opportunities:

• Cutting-Edge AI/Agentic Technology: Direct exposure to and contribution in the rapidly growing field of AI agents and human-AI collaboration.

• Advanced UX/Information Design: Opportunities to hone skills in designing for highly complex, data-rich environments, potentially influencing industry best practices.

• Architectural Leadership: Potential to grow into technical leadership roles, guiding the architecture of critical AI platform components.

• Industry Conferences & Training: Access to internal and external resources for continuous learning in AI, software engineering, and UX.

📝 Enhancement Note: This role presents a significant opportunity to be at the forefront of AI product development, tackling novel challenges in human-AI interaction. The ability to navigate ambiguity and drive innovation in a nascent field will be key to success and growth.

💡 Interview Preparation

Strategy Questions:

• Systems Design: "Design a system to monitor and control a fleet of AI agents performing [specific task]. How would you represent their state, provide diagnostic tools, and allow for human intervention?" Focus on scalability, fault tolerance, and data representation.

• UX/Information Design: "Imagine you need to visualize the decision-making process of an AI agent in real-time. What principles would you apply? How would you handle uncertainty or potential errors?" Emphasize clarity, hierarchy, and effective data encoding.

• Human-Agent Interaction: "Describe a scenario where a human needs to supervise an AI agent. What are the critical interaction points, feedback mechanisms, and potential failure modes you would design for?" Focus on trust, explainability, and user control.

Company & Culture Questions:

• "Why are you interested in Salesforce's 'Agentforce' initiative and the AI-native direction?" Demonstrate your understanding of the company's strategic focus.

• "How do you approach building trust and explainability into complex systems, especially AI?" Align your approach with Salesforce's values.

• "Describe a time you had to translate highly technical concepts for a non-technical audience. How did you ensure clarity and understanding?" Showcase your communication skills. Portfolio Presentation Strategy:

• Storytelling: Frame each project as a narrative: the problem, your innovative solution (both system and UX), the technical challenges you overcame, and the impact achieved.

• Visuals are Key: Use clear diagrams, mockups, and interactive prototypes to illustrate your design and system architecture. For code, show well-structured, clean examples.

• Quantify Impact: Whenever possible, use metrics to demonstrate the success of your solutions (e.g., reduced error rates, improved user efficiency, faster diagnosis times).

• Explain Your Choices: Be prepared to articulate the rationale behind every significant architectural and design decision you made, linking it back to user needs and system constraints.

📝 Enhancement Note: The interview will heavily scrutinize your ability to bridge the gap between complex backend systems and user-facing experiences, with a specific lens on AI agent interaction. Your portfolio should be tailored to highlight this unique skill set, and your answers should demonstrate a forward-thinking approach to AI product development.

📌 Application Steps

To apply for this AI Native - UX - Software Engineer position:

• Submit your application through the Salesforce Careers portal using the provided link.

• Tailor your resume: Highlight experience with distributed systems, API development, advanced UX/information design, data visualization, and any exposure to AI, ML, or agentic systems. Use keywords from the job description.

• Prepare your portfolio: Curate 2-3 key projects that best demonstrate your ability to design and build complex systems with sophisticated user interfaces, particularly for AI-driven applications. Be ready to present these with detailed explanations of your process and impact.

• Research Salesforce's AI initiatives: Familiarize yourself with "Agentforce," "AI CRM," and Salesforce's vision for the future of AI to articulate your interest and understanding during interviews.

• Practice system design and UX/information design scenarios: Prepare for technical discussions and whiteboard exercises related to building and visualizing complex systems and human-AI interactions.

⚠️ 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.