Senior Software Engineer, Autonomous Freight Systems

The Opportunity

The Autonomous Freight Systems team is a brand new, AI-first engineering team in San Francisco, building Flexport's client-facing rates platform and self-serve freight booking experience from the ground up. We own two of the highest-leverage surfaces in the Client App: how clients see pricing and how they book freight without manual intervention.

As a Senior Engineer, you will own significant technical domains end-to-end, not just features, but whole problem spaces. You will drive the engineering of systems that power rate visibility, pricing intelligence, and AI-assisted booking across ocean, air, and trucking. You don't wait to be told what to build next; you identify the highest-leverage problems, propose solutions, and see them through to production. You will be a technical force multiplier on the team: raising the bar on code quality, helping junior engineers grow, and shipping with a velocity and confidence that comes from deep ownership.

This is a ground-floor opportunity to build the platform that moves Flexport from an assisted-sales model to a tech-run one for the long tail of our client base—turning the complexity of global trade into a seamless digital experience for thousands of shippers.

You Will

• Take end-to-end technical ownership of core systems: from schema design and backend APIs to the React surfaces our customers use and drive them to production without needing oversight.
• Proactively identify gaps, inefficiencies, and engineering problems within your domain and lead the effort to resolve them.
• Design and build AI-powered features and integrations, moving beyond "AI familiarity" to hands-on implementation of agent workflows and LLM-backed automation in production.
• Drive technical design for significant features, producing well-reasoned proposals and aligning teammates before writing the first line of code.
• Mentor and support P2 engineers through code review, pairing, and design feedback, raising the quality of the team's output.
• Collaborate closely with product, design, pricing, and operations to translate complex domain problems into elegant, production-ready solutions.
• Build and ship incrementally: this team deploys to production dozens of times per day, and you are comfortable with that pace.
• Ensure reliability and quality by building in metrics, monitoring, and applying learnings from incidents to all systems you own.

You Should Have

• 5+ years of professional software engineering experience with a proven track record of shipping production-grade systems with increasing levels of independence.
• Deep Ownership Instinct: You hold yourself accountable for outcomes, not just outputs. When something breaks, you fix it—and you make sure it doesn't break again.
• Full-Stack Fluency: You can own a feature from the database to the browser. You are opinionated about schema design, API contracts, and frontend architecture, not just one layer.
• AI/LLM Hands-On Experience: You have built software that integrates LLMs into real user workflows—not just proof-of-concepts, but production systems. You understand the practical challenges: latency, reliability, prompt fragility, and cost.
• Agency and Drive: You identify the next most important problem without being asked. You default to action, propose solutions, and bring others along.
• Technical Rigor: A genuine passion for simple, well-tested, well-structured code. You push back on complexity and leave systems better than you found them.
• Communication: You can explain a technical tradeoff clearly to a product manager and to a staff engineer. Your design docs and code reviews are worth reading.
• Proficiency with deploying, monitoring, and maintaining production services on cloud infrastructure (AWS).

  It's a Plus If You Have

• Experience with elements of our tech stack: Java, Spring Boot, Ruby on Rails, React, AWS.
• Familiarity with agentic patterns, RAG, or workflow orchestration (e.g., Temporal).
• Experience in logistics, supply chain, freight technology, or pricing systems.
• A bias for action: when you see a problem, you own the fix.

#LI-onsite