Engineering Manager

Altana is the network for trusted trade. Our AI-powered product network empowers governments and businesses to build a more resilient and secure global economy while keeping trade flowing.

The Opportunity at Altana

The Engineering organization is responsible for building the product that brings this vision to life. We are creating a platform fundamentally driven by AI, which scales to a massive trove of data, and a diverse customer base; it is a complex system that will stretch engineering in many directions.

The best teams here ship work customers come to rely on, and that takes a particular kind of engineering practice. It means starting inside the customer's workflow rather than at the ticket. It means treating every release as a hypothesis you can prove or disprove. It means reaching for AI as a primary building block, not a feature you bolt on at the end. And it means owning a product end‑to‑end, from the first conversation through the telemetry six months later.

As an Engineering Manager at Altana, that's the work, and you'll build and lead the team doing it. You'll embed with product and design, turn hypotheses about where the real pain is into shipped, adopted products, and own the hiring, growth, and performance of the engineers on your team. Your success is measured the same way the team's is: by the value it delivers to customers, how quickly and steadily it ships, and how well its systems hold up as output grows.

You Will

• Build the team and help each person grow. Own performance management end to end, and use each engineer's career goals to shape what they work on.

• Stay close to customers, and bring your team with you. Get on customer calls, review session recordings, and know the top friction points in your area at any moment. Make sure your engineers see customer problems firsthand too.

• Hold the bar on solving the right problem. Partner with product and design to define the problem before choosing a solution, and push back on work that isn't grounded in customer evidence.

• Keep your hands in the work. Contribute meaningful code, know your domain's architecture and tech debt, and set the standard for quality. The balance will shift toward management as the team grows.

• Build AI-native, and verify it. Treat LLMs, agents, evals, and retrieval as standard building blocks. Hold a clear standard for how AI-assisted code is checked before it reaches customers.

• Make commitments the team keeps. Run a planning process that produces realistic plans, flag risks early, and deliver cycle after cycle.

• Make the team faster over time. Use shared engineering metrics to find bottlenecks and remove them. Know where the team's time goes, and pay down operational debt before it slows you down.