Product Engineer

About the Job

As a key growth accelerator, A11 partners with Europe’s most ambitious startups and scaleups, corporates and SMBs to connect them with top-tier talent ready to make an impact. 

We're looking for an ownership-driven Senior Product Engineer (Full Stack) for the engineering team at one of our Ecosystem Companies. You won't just ship tickets: you own business problems end to end, from the first conversation to production, working with Product on what to build and delivering across data, services, AI agents, and UI.

Join the A11 Ecosystem – a next-generation supply chain platform redefining how one of the world's largest industries sources, distributes, and finances materials. Engineered to unlock the full potential of global trade, it harnesses agentic AI and workflow automation to provide seamless, high-efficiency access to premium materials at scale. Since its commercial rollout, the platform has fueled exponential growth, optimizing procurement for thousands of businesses while setting new benchmarks for speed, transparency, and efficiency. Its competitive edge lies in full digitization and AI-driven supply chain management automation, eliminating inefficiencies and creating a direct, intelligent bridge between suppliers and buyers. With a team of 80+ FTEs across Europe (Berlin HQ), China, and India, the company is rapidly scaling toward profitability, driving triple-digit million GMV, and setting new industry standards in autonomous, AI-powered supply chain orchestration.

In this role, you’ll:

Own business problems end to end

• Take a problem from first conversation through production and ongoing operation, for example making supplier pricing reliable from ingestion to the final quote
• Work with Product to decide what to build and why
• Measure whether shipped work performs, including monitoring and evaluating LLM-driven workflows in production

Build the platform and AI agents

• Build backend services for pricing, inventory, orders, and integrations with suppliers, customers, and logistics partners
• Build AI agents, their tools, and APIs, with safeguards such as idempotency, validation, audit trails, and human review
• Turn messy external data (price lists, datasheets, stock feeds) into reliable data for the wider business
• Design interfaces where commercial teams can review agent proposals, correct errors, and approve decisions quickly

Raise the engineering bar

• Make and document technical decisions and their trade-offs
• Mentor other engineers through reviews, pairing, and feedback