Product Owner

About Draiver

Draiver is an AI-first, technology-driven logistics company transforming how vehicles move across the U.S. and Latin America. We build smart, scalable solutions that simplify complex automotive operations, from planning and routing to execution and real-time visibility.

As a fast-growing startup, we operate in a highly dynamic environment where ownership, adaptability, and execution matter. Our teams work closely across product, engineering, operations, and commercial areas, leveraging AI-native tools, data, and automation to solve real-world problems with tangible impact.

At Draiver, we value people who take responsibility, think critically, and are comfortable navigating ambiguity. If you enjoy building products from the ground up, working in an AI-first mindset, and turning complex challenges into simple, effective solutions, you’ll feel at home here.

Product Ownership & Delivery

• Own and prioritize the product backlog with a focus on maximizing business value
• Translate ambiguous problems into clear user stories, requirements, and acceptance criteria.
• Partner closely with engineering to shape scalable, AI-ready product capabilities.
• Actively participate in sprint planning, reviews, and retrospectives, ensuring rapid learning and iteration.

AI-First Product Thinking

• Identify opportunities to embed AI, automation, and intelligence into product features and workflows.
• Collaborate with engineering, data, and internal teams to define use cases, experiments, and AI-enabled MVPs
• Stay current on emerging AI tools, patterns, and best practices, and proactively apply them to product challenges.

Hands-On Design & Discovery

• Contribute directly to product design, including wireframes, user flows, prototypes, and UX improvements.
• Use AI-assisted design, research, and prototyping tools to accelerate discovery and validation.
• Conduct user research, interviews, usability testing, and rapid experimentation.
• Test hypotheses quickly using prototypes, MVPs, and data-driven experiments.

Data & Insights

• Use quantitative and qualitative data to inform prioritization and product decisions.
• Define success metrics and track performance for both traditional and AI-driven features.
• Partner with analytics and operations to interpret signals, patterns, and outcomes.
• Continuously refine solutions based on learnings, feedback, and measured impact.

Stakeholder Collaboration

• Act as a key connector between engineering, operations, sales, support, leadership, and external partners.
• Communicate product vision, AI capabilities, trade-offs, and outcomes clearly and effectively.
• Gather insights from internal and external stakeholders to inform discovery and prioritization.

Day One Mindset & Continuous Improvement

• Operate comfortably in ambiguity and help define processes, standards, and best practices as the product and team scale.
• Apply AI-first approaches to your day-to-day work, including research, documentation, analysis, and decision-making.
• Think creatively and “outside the box” to solve problems where there is no playbook.
• Take on increasing responsibility and ownership as the role and organization grow.

What Makes This Role Unique

• AI-first product environment with real opportunities to implement intelligent, automated solutions.
• High exposure to leadership, multiple teams, and evolving product strategy.
• Hands-on impact across product strategy, design, discovery, and delivery.
• Room for growth, expanded ownership, and influence.
• Fast-paced, entrepreneurial culture where experimentation and learning are encouraged.

Qualifications & Skills Required

• Experience as a Product Owner, Product Manager, or similar product role.
• Strong understanding of Agile/Scrum frameworks.
• Comfort working hands-on with design tools (e.g., Figma or similar).
• Strong analytical skills and data-driven decision-making mindset.
• Familiarity with AI-enabled tools and workflows (e.g., AI-assisted research, analysis, prototyping, or automation).
• Excellent communication, collaboration, and problem-solving skills.

Preferred (Nice to Have)

• Experience building or supporting AI-driven or data-intensive products.
• Background in UX, design, analytics, operations, or engineering.
• Experience running experiments, MVPs, or rapid product iterations.
• Experience in startup or early-stage environments.