Product Designer, LSP44

📍 Job Overview

Job Title: Product Designer, LSP44

Company: project44

Location: Chicago, IL

Job Type: Full-time

Category: Product Design / UX Design

Date Posted: 2026-08-03

Experience Level: Mid-Level (4+ years)

Remote Status: On-site

🚀 Role Summary

• Design end-to-end user experiences for AI-native agent and API infrastructure within the logistics sector, focusing on both operator and developer audiences.

• Collaborate closely with Product, Engineering, Sales, and Marketing to translate complex operational workflows into intuitive and trustworthy design solutions.

• Contribute to the evolution of a design system and interaction patterns for a growing portfolio of AI agents.

• Drive user research and rapid prototyping to validate design concepts and ensure alignment with real-world operational complexities.

📝 Enhancement Note: The role emphasizes a "builder" mentality in a lean, fast-moving environment, suggesting a need for a candidate comfortable with ambiguity and direct collaboration with engineering teams, rather than traditional hand-offs. The "AI-native" aspect and the dual audience (operators and developers) are critical differentiators for this role.

📈 Primary Responsibilities

• Design comprehensive user interfaces and interaction flows for LSP44’s AI agents, including dashboards, exception management, and configuration interfaces.

• Partner with cross-functional teams, including forward-deployed engineers, to understand and design for intricate logistics operational realities.

• Translate complex logistics processes and AI agent functionalities into clear, user-friendly designs that build trust and legibility for end-users.

• Develop and maintain design system components and interaction patterns to ensure consistency and scalability across the agent portfolio.

• Conduct and leverage user research, including usability testing with logistics service provider (LSP) operators, to inform and validate design decisions.

• Create rapid prototypes to test and iterate on agent interaction patterns, minimizing engineering effort on unproven concepts.

📝 Enhancement Note: The emphasis on designing for "two audiences at once" (LSP operators and developers) implies a need for a designer who can balance different user needs and technical requirements within a single product or platform. Designing for "real operational complexity, not abstractions" suggests a need for domain understanding or a strong ability to quickly grasp complex B2B workflows.

🎓 Skills & Qualifications

Education: Bachelor’s degree in Design, HCI, or a related field, or equivalent practical experience.

Experience: 4+ years of experience in product design or UX, with a strong preference for B2B SaaS, logistics, supply chain, or other operationally complex domains.

Required Skills:

• Proven experience in end-to-end product design, from user research and ideation through to shipped product delivery.

• Proficiency in design and prototyping tools, with Figma being a key requirement.

• Demonstrated ability to partner directly and collaboratively with engineering teams to build technical products.

• Strong communication and interpersonal skills, capable of effectively engaging with both technical and business stakeholders.

• Experience designing for AI-driven, agentic, or automation-heavy products is highly desirable.

• Ability to work effectively within distributed teams and across different time zones. Preferred Skills:

• Experience in the logistics, supply chain, or freight brokerage industry.

• Familiarity with AI concepts and their application in user-facing products.

• Experience contributing to or evolving design systems.

📝 Enhancement Note: The "4+ years" experience level, combined with the "0-to-1 environment" context, suggests they are looking for a designer who can operate with significant autonomy and influence, rather than a junior individual contributor. The explicit mention of "AI agents" and "API infrastructure" points to a need for designers comfortable with technical complexity and potentially abstract concepts.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrate a comprehensive end-to-end design process, showcasing your journey from initial research and problem definition to final shipped product.

• Include case studies that highlight your ability to tackle complex B2B SaaS challenges, particularly in operationally intensive domains.

• Showcase examples of designing for AI-driven products, agentic systems, or automation workflows if applicable.

• Present clear visuals and concise explanations of user flows, interaction patterns, and UI design decisions. Process Documentation:

• Clearly articulate your research methodologies, including how you gather insights from users and stakeholders.

• Detail your approach to problem-solving, including how you define user needs and translate them into design solutions.

• Illustrate your prototyping and iteration process, emphasizing how you test and validate design concepts before development.

• Provide examples of how you collaborated with engineering and other cross-functional teams throughout the design lifecycle.

📝 Enhancement Note: Given the role's focus on AI agents and API infrastructure, a portfolio demonstrating the ability to design for complex technical integrations and potentially abstract concepts will be highly valued. The emphasis on "trustworthy" and "legible" design suggests a need for case studies that show how the designer built user confidence in complex systems.

💵 Compensation & Benefits

Salary Range: $112,000 - $168,000 USD per year.

Benefits:

• Stock options for all employees.

• Bonus or commission eligibility, depending on the role.

• Comprehensive benefits package tailored to the country of employment, including:

  • Health coverage
  • Dental coverage
  • Vision coverage
  • Retirement plans
  • Paid time off

• Benefits packages will align with local market standards and statutory programs.

Working Hours: Standard 40-hour work week, with flexibility expected for collaboration across distributed teams and time zones.

📝 Enhancement Note: The salary range provided is specific and directly stated. The benefits are also clearly outlined, with a note that specifics vary by country. The inclusion of stock options and potential bonus/commission eligibility indicates a compensation structure common in growth-stage tech companies.

🎯 Team & Company Context

🏢 Company Culture

Industry: Logistics Technology / AI Infrastructure. LSP44 operates within the intersection of logistics technology and artificial intelligence, providing AI agents and API infrastructure to logistics service providers.

Company Size: Based on the information, project44 (and by extension, LSP44) is a significant player in the logistics tech space, likely mid-to-large sized, given its established data graph and carrier network.

Founded: LSP44's technology was built by project44 starting in 2014, with LSP44 launching as a distinct entity. This indicates a company with deep roots in the industry and a proven track record.

Team Structure:

• The Product Design team is described as "small" and "senior," working in close partnership with Product, Engineering, Sales, and Marketing.

• There's a mention of "forward-deployed engineers on-site with customers," suggesting a highly collaborative and customer-centric approach.

• The role emphasizes working in a "0-to-1 environment" with direct partnership with engineering, indicating a flat or agile team structure where designers are integrated into development cycles. Methodology:

• AI-First Approach: Every team member is expected to be an intelligent, hands-on user of AI, with Product Designers expected to define AI agents.

• Data-Driven: Built on "more than a decade of the largest logistics data graph," suggesting a strong reliance on data to inform product development.

• Customer-Centric: Designing for "real operational complexity" and working with "forward-deployed engineers" indicates a deep focus on understanding and solving customer problems.

• Agile Development: The mention of designing products that "ship in days instead of quarters" and partnering "tightly with engineering rather than through hand-offs" points to agile or lean development methodologies.

Company Website: https://www.project44.com/

📝 Enhancement Note: The context of LSP44 being the "original infrastructure project44 built" and launching "profitable on day one" with its own leadership team suggests a mature, well-resourced spin-off with a clear market position and established customer base. The emphasis on AI as a core tenet for all employees, especially product designers, is a significant cultural indicator.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned at a mid-level (4+ years of experience) in Product Design, with a significant scope of ownership. It's a "hands-on, builder role on a small, senior team," implying a high degree of individual contribution and potential for rapid learning and impact.

Reporting Structure: The designer will partner closely with Product, Engineering, Sales, and Marketing. While a direct manager isn't specified, the collaborative nature suggests reporting into a Head of Product Design or a Design Lead.

Operations Impact: The Product Designer will directly influence the usability, trustworthiness, and adoption of LSP44's core AI agent and API infrastructure. This impact is crucial for logistics service providers, directly affecting their operational efficiency, decision-making, and integration capabilities. The designs will be embedded into how LSPs operate, underscoring the critical business impact of this role.

Growth Opportunities:

• Technical Specialization: Deepen expertise in designing complex B2B SaaS products, AI-driven systems, and API interfaces within the logistics domain.

• Leadership Potential: As part of a small, senior team, there's an opportunity to grow into a design lead role, mentor junior designers, and influence the overall design strategy.

• Domain Expertise: Develop profound knowledge of the logistics and supply chain industry, becoming a subject matter expert in how technology and AI can transform freight operations.

• Product Influence: Directly contribute to defining and shipping new product lines (AI agents), gaining significant product ownership and strategic input.

📝 Enhancement Note: The "0-to-1 environment" and "small, senior team" context suggests that for individuals looking to make a significant mark and grow rapidly, this role offers substantial opportunities. The emphasis on "shipping in days instead of quarters" points to a fast-paced environment where individual contributions are quickly visible and impactful.

🌐 Work Environment

Office Type: The role is designated as "On-site" in Chicago, IL. This suggests a traditional office-based work environment, likely with a focus on in-person collaboration.

Office Location(s): Chicago, IL. This location offers a major metropolitan hub with access to talent and resources.

Workspace Context:

• Collaborative Hub: As an on-site role, expect a workspace designed for collaboration, with opportunities for spontaneous interactions with Product, Engineering, Sales, and Marketing teams.

• Tooling: Access to modern design tools like Figma and prototyping software will be standard. The company's focus on AI and data suggests potential for advanced analytics and research tools to be available.

• Team Interaction: Being in the office facilitates direct engagement with colleagues, fostering a strong team dynamic and enabling the close partnerships required for this role, especially with engineering.

Work Schedule: While a standard 40-hour work week is implied, the mention of working "across distributed teams and time zones" suggests a degree of flexibility may be required to accommodate collaboration with remote colleagues. However, the primary work location is on-site.

📝 Enhancement Note: The "on-site" requirement in Chicago, coupled with the mention of distributed teams, indicates a hybrid-like dynamic where core team members are co-located for intensive collaboration, while still needing to connect with remote counterparts. This environment likely fosters a strong sense of team cohesion and a direct pipeline to engineering and product leadership.

📄 Application & Portfolio Review Process

Interview Process:

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

• Portfolio Review & Design Exercise: Candidates will be expected to present their portfolio, showcasing their end-to-end design process and relevant case studies. A design challenge or take-home assignment focusing on a complex operational problem or AI agent interface may be part of this stage.

• Cross-Functional Interviews: Interviews with Product Managers, Engineers, and potentially Sales/Marketing stakeholders to assess collaboration skills, technical understanding, and ability to translate business needs into design solutions.

• Hiring Manager Interview: A final interview to discuss role specifics, team dynamics, and overall fit.

Portfolio Review Tips:

• Showcase Process: Clearly articulate your thought process, research methods, and design iterations for each case study.

• Highlight Impact: Quantify the impact of your designs whenever possible (e.g., improved efficiency, reduced errors, increased adoption).

• Tailor to LSP44: Emphasize experience with B2B SaaS, complex operational domains, and any work related to AI or automation.

• Design for Dual Audiences: If possible, showcase projects where you had to consider multiple user types or technical integrations.

• Focus on Collaboration: Demonstrate how you partnered with engineering and other teams, rather than working in isolation.

Challenge Preparation:

• Understand the Domain: Familiarize yourself with the logistics industry, common challenges faced by LSPs, and the concept of AI agents in operational contexts.

• AI Agent Thinking: Consider how users interact with and trust AI systems, how to visualize AI outputs, and how to design for exception handling.

• B2B SaaS Best Practices: Review common patterns for dashboards, configuration interfaces, and workflows in enterprise software.

• Rapid Prototyping: Be prepared to quickly mock up solutions and articulate your design rationale.

📝 Enhancement Note: The emphasis on "designing for real operational complexity" and "AI agents" means that candidates should be ready to discuss their approach to understanding and representing complex workflows and abstract AI functionalities. Demonstrating how they build "legibility and trustworthiness" in these systems will be key.

🛠 Tools & Technology Stack

Primary Tools:

• Figma: Explicitly required for design and prototyping. Proficiency is essential.

• Prototyping Tools: Modern prototyping tools are expected, likely integrated with Figma or standalone (e.g., ProtoPie, InVision).

Analytics & Reporting:

• While not explicitly stated, expect to work with product analytics tools (e.g., Amplitude, Mixpanel) to understand user behavior and inform design decisions.

• Reporting tools may be used for presenting design impact and user research findings. CRM & Automation:

• While this role is focused on design, understanding how designs integrate with CRM systems (e.g., Salesforce) and workflow automation tools is beneficial for context.

📝 Enhancement Note: The explicit mention of Figma and "modern prototyping tools" highlights the core design stack. Given the company's focus on AI and data infrastructure, familiarity with tools that facilitate data visualization and potentially AI output interpretation within the design process would be a strong plus.

👥 Team Culture & Values

Operations Values:

• AI-Centricity: A core expectation is to be an intelligent, hands-on user of AI, critically evaluating its outputs and responsibly governing its use in products and workflows.

• Speed & Agility: A mandate to "move at the speed of the LSPs it serves," with products shipping in "days instead of quarters."

• Customer Focus: Designing for "real operational complexity" and partnering with "forward-deployed engineers" emphasizes a deep commitment to solving customer problems.

• Collaboration: Close partnership with Product, Engineering, Sales, and Marketing is fundamental.

• Data-Driven: Leveraging a "decade of the largest logistics data graph" implies decisions are informed by robust data.

Collaboration Style:

• Integrated Teams: Designers work "tightly with engineering rather than through hand-offs," indicating a highly collaborative and integrated approach.

• Cross-Functional Partnership: Close collaboration is expected across Product, Engineering, Sales, and Marketing, requiring strong communication and alignment.

• Customer-Immersion: Working with "forward-deployed engineers on-site with customers" suggests a culture of understanding user environments firsthand.

📝 Enhancement Note: The company's emphasis on "every LSP44 team member is expected to be an intelligent, hands-on user of AI" is a critical cultural differentiator. For Product Designers, this means not just designing interfaces but understanding and advocating for the effective and responsible integration of AI capabilities.

⚡ Challenges & Growth Opportunities

Challenges:

• Designing for Dual Audiences: Balancing the needs of LSP operators (day-to-day users) and developers (integrators) with potentially different technical proficiencies and goals.

• AI Trust and Legibility: Creating designs that make AI agents understandable, predictable, and trustworthy for users who may be new to AI in their operational workflows.

• Operational Complexity: Translating highly intricate and often manual logistics processes into streamlined digital experiences.

• 0-to-1 Environment: Navigating ambiguity, defining new product areas, and building foundational design systems in a fast-paced startup setting.

Learning & Development Opportunities:

• AI Product Design Expertise: Gain specialized experience in designing for AI-driven products and agentic systems, a rapidly growing field.

• Logistics Domain Mastery: Develop deep expertise in the supply chain and logistics industry, understanding its unique challenges and opportunities.

• Design System Leadership: Contribute significantly to and evolve a design system for a core product offering, gaining experience in scalable design.

• Cross-Functional Influence: Hone skills in collaborating with and influencing engineering, product management, and sales teams in a high-growth environment.

📝 Enhancement Note: The "AI-native agent and API infrastructure" focus presents a unique challenge and opportunity. Designers will need to grapple with how to best represent AI decision-making, control, and monitoring in an intuitive and actionable way for logistics professionals.

💡 Interview Preparation

Strategy Questions:

• "How would you approach designing an interface for an AI agent that manages freight exceptions? What are the key considerations for building user trust in this system?" (Focus on AI trust, operational context, and user needs).

• "Describe a time you had to design for two distinct user groups with different technical needs within the same product. How did you balance their requirements?" (Focus on dual audience design, empathy, and trade-offs).

• "Walk us through a complex B2B SaaS product you designed. What was the problem, your process, and the outcome?" (Focus on end-to-end process, problem-solving, and impact). Company & Culture Questions:

• "What excites you about LSP44 and project44's mission in the logistics AI space?" (Demonstrate research and genuine interest).

• "How do you approach being an 'intelligent, hands-on user of AI' in your own work and product design?" (Showcase AI literacy and proactive engagement).

• "How do you collaborate with engineering teams when designing technical products?" (Highlight your partnership approach and communication skills). Portfolio Presentation Strategy:

• Structure: Organize your portfolio around 2-3 strong case studies that best represent your end-to-end process and relevant experience (B2B SaaS, complex domains, AI/automation).

• Storytelling: For each case study, clearly articulate the problem, your role, the constraints, your design process (research, ideation, iteration), key decisions, and the final outcome/impact.

• Visuals: Use high-quality mockups, wireframes, user flows, and potentially prototypes to illustrate your work.

• Collaboration Emphasis: Explicitly discuss how you worked with engineering, product managers, and other stakeholders.

• AI Focus: If applicable, highlight any projects involving AI, automation, or agentic systems, explaining your design considerations for these complex technologies.

📝 Enhancement Note: Candidates should be prepared to discuss their understanding of AI's role in logistics and how they translate abstract AI functionalities into concrete, user-friendly interfaces that are both efficient and trustworthy. Demonstrating an ability to grasp complex domain challenges quickly will be crucial.

📌 Application Steps

To apply for this Product Designer position:

• Submit your application through the provided link on greenhouse.io.

• Tailor your Resume: Highlight experience in B2B SaaS, product design, UX, and any relevant domain experience (logistics, supply chain, AI). Use keywords from the job description.

• Curate Your Portfolio: Select 2-3 of your strongest case studies that showcase your end-to-end design process, problem-solving skills, and experience with complex technical products or AI. Ensure it clearly demonstrates your ability to design for both operators and developers.

• Prepare Your Presentation: Be ready to walk through your portfolio, articulating your design rationale, process, and the impact of your work. Practice explaining how you build trust and legibility in complex systems.

• Research LSP44 & project44: Understand their mission, technology (AI agents, API infrastructure), and the logistics industry they serve. Be prepared to discuss why you are interested in this specific company and 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.