Senior Software Engineer, AI Platform

About Flexport:

At Flexport we believe global trade can move the human race forward. Thats why its our mission to make global commerce so easy there will be more of it. Were shaping the future of a $10T industry with solutions powered by innovative technology and exceptional people. Today companies of all sizesfrom emerging brands to Fortune 500suse Flexport technology to move more than $19B of merchandise across 112 countries a year.

The recent global supply chain crisis has put Flexport center stage as we continue to play a pivotal role in how goods move around the world. We are proud to have the support of the best investors in the game who believe in our mission solutions and people. Ready to tackle global challenges that impact business society and the environment Come join us.

The $8.6 trillion freight forwarding industry runs on phone calls faxes and emails. At Flexport were changing that with softwareand now with AI were accelerating the transformation by orders of magnitude.

Our AI Platform team in Amsterdam is building the intelligence layer that will make every person at Flexport exponentially more effective. Were not just building chatbotswere creating autonomous agents that eliminate toil catch errors before they cascade and handle the long tail of logistics operations that traditional software could never economically address. This isnt hypotheticalwe already have agents saving thousands of hours per week. Youll be building the platform that multiplies that impact across the entire company.

This is a rare opportunity to work at the intersection of AI and a massive real-world problem space. Youll build systems that directly impact how $19 billion of goods move across 112 countries touching everything from customs compliance to document processing to incident response.

What Youll Build:

Automation Engineering Platform

• Build the infrastructure that lets operators create AI-powered workflows without writing codeparsing emails against SOPs extracting data from documents creating smart work queues and deploying ambient quality agents that catch problems before they become incidents
• Create the tooling that transforms subject matter experts into automation engineers
• Create AI powered safeguards and security that monitor usage and warn (or even intervene) when we have potential problems.

Secure AI Infrastructure

• Build a production-grade internal AI chat surface with granular MCP (Model Context Protocol) integration giving different teams secure access to the right internal tools and data
• Create an MCP gateway that safely exposes internal services to client-side AI agents enabling developers to use tools like Claude Code against Flexports systems
• Navigate the rapidly evolving auth and security landscape of AI toolingyoull be solving problems that dont have Stack Overflow answers yet

Agent Templates & Deployment

• Turn our most successful AI agentssecurity monitoring data repair compliance checking incident responseinto reusable templates
• Build the deployment infrastructure that makes it trivial to spin up new specialized agents for different use cases
• Design systems that make agents observable debuggable and improvable over time

Why This Role Is Special:

• Youre early: AI in enterprise is still being figured out. The patterns you build here could become industry standards
• Real problems: Youre not optimizing ad clicksyoure helping businesses move physical goods across borders more efficiently
• Autonomy: Youll own entire projects from conception to deployment

Learning: Youll work alongside people who have built successful AI agents in production and know what works (and what doesnt)

You Should Have:

• 5 years of software engineering experience and having built at least one or two production LLM applications
• Full-stack capability: Youre comfortable deploying services on Kubernetes/AWS designing backend systems for LLMs and building frontend applications when needed
• Deep LLM experience: You understand agent patterns workflows MCP RAG prompt engineering. Youve worked with frameworks like LangChain LlamaIndex or built your own orchestration layers.
• Entrepreneurial mindset: You can take a vague problem (make compliance checking automatic) design the full solution and ship it to production without needing your hand held
• A love of simple well-tested code that is easy to extend and hard to breakespecially important when working with non-deterministic AI systems
• Excellent communication skills: Youll be working directly with operators product teams and leadership to understand needs and explain technical tradeoffs
• A bias for action: When you see an opportunity to eliminate toil or catch errors you build it
• Non-optional: an aptitude for learning quickly in a space where best practices are being written in real-time

Nice to Have:

• Experience with security especially around API gateways and auth systems
• Experience with workflow orchestration tools (Temporal Airflow etc.)
• Familiarity with the logistics or supply chain domain