GTM Systems Engineer

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What if scaling visual AI revenue didn't require scaling headcount linearly?

Our founding team pioneered Latent Diffusion and Stable Diffusion - breakthroughs that made generative AI accessible to millions. Today, our FLUX models power creative tools, design workflows, and products across industries worldwide.

Our FLUX models are best-in-class not only for their capability, but for ease of use in developing production applications. We top public benchmarks and compete at the frontier - and in most instances we're winning.

If you're relentlessly curious and driven by high agency, we want to talk.

With a team of ~50, we move fast and punch above our weight. From our labs in Freiburg - a university town in the Black Forest - and San Francisco, we're building what comes next.

We've built the foundation models that power FLUX and transformed how the world generates images—now we're figuring out how to build the commercial infrastructure that can scale as fast as our technology.

This isn't your typical RevOps role, and it's not pure engineering either. It's the technical architecture of our business itself: the systems that turn API calls into revenue, transform messy multi-jurisdictional data into clarity, and automate what currently requires 10 people to do manually.

What You'll Pioneer

You'll be building the nervous system of our revenue operations—but we're honest: much of it doesn't exist yet.

Billing infrastructure that doesn't break at scale
Our business model is deliberately complex: usage-based API pricing, enterprise licenses, self-serve Playground flows, dual US/German entities. You'll design systems that handle this without requiring an army of humans to intervene. How do we track API consumption accurately? How do we automate invoice generation across jurisdictions? How do we recognize revenue correctly when products and pricing are constantly evolving?

Enterprise GTM systems that actually talk to each other
Right now, data moves through too many hands. You'll architect integrations between CRM, billing, contracts, and finance—building the workflows that turn enterprise sales from a manual slog into something elegant. Quote-to-cash shouldn't take weeks. Contract amendments shouldn't require spreadsheets. We need systems that scale with ambition.

Analytics infrastructure that surfaces truth
We're flying fast, which means we need instruments. You'll build the data pipelines and dashboards that show us what's actually happening: consumption patterns, churn signals, expansion opportunities. Not vanity metrics—the kind of real-time visibility that changes how we make decisions.

The Questions We're Wrestling With

You won't just execute—you'll help us figure out what to build:

• How do we accurately track and bill for API usage across millions of requests while handling edge cases we haven't imagined yet?

• What's the right build-vs-buy calculus for a 50-person company scaling to 150? (Stripe? Metronome? Custom?)

• How do we create automated customer health scoring when our product is at the frontier and usage patterns are still emerging?

• How do we design financial systems for a dual US/EU structure that doesn't make our finance team want to quit?

• What does "usage-based billing" actually mean when customers use our API in ways we never anticipated?

• How do we build support automation for self-serve customers without losing the human touch that matters?

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Required Experience

Technical Skills

• 3-5+ years as a Software Engineer, Systems Engineer, or RevOps Engineer at a B2B AI or SaaS company

• Programming proficiency: Python, JavaScript/TypeScript, SQL

• CRM expertise: Hands-on experience with cloud-based CRMs such as Attio, Salesforce, or HubSpot

• Integration platforms: Experience building with Workato, Zapier, Tray.io, or similar iPaaS tools

• API development: RESTful APIs, webhooks, OAuth, authentication protocols—you understand these as contracts, not just endpoints

• Data pipelines: Proven experience building ETL/ELT workflows, data transformation, and warehouse integration

• Billing systems: Familiarity with Stripe Billing, Metronome, Lago, Chargebee, or similar usage-based billing platforms

Business & Domain Knowledge

• Experience with usage-based pricing, consumption billing, and complex contract structures

• Understanding of multi-jurisdictional business operations (US/EU structures a plus)

• Track record of making build-vs-buy decisions and living with the consequences

How You Work

• Cross-functional collaboration: You translate fluently between finance speak, sales speak, and engineering speak

• Business acumen: You connect technical solutions directly to revenue outcomes

• Problem-solving: You debug complex data flows and system integration issues independently—because you can't help yourself

• Communication: You explain technical concepts clearly to non-technical stakeholders without condescension

• Attention to detail: You ensure data accuracy and integrity because you know messy data leads to messy decisions

• Ownership mentality: You identify problems and ship solutions without waiting for permission

Preferred Experience

• Experience at a high-growth startup scaling from $1M to $100M+ ARR (ideally during the messy middle)

• Familiarity with API-first or usage-based products

• Experience with data visualization tools (Tableau, Looker, Metabase)

• Knowledge of sales tax, VAT compliance, and multi-currency billing

• Prior experience navigating dual US/EU entity structures

What Success Looks Like

Within 3 months: You've audited our GTM systems, identified the biggest automation opportunities, built your first integration, and documented where our revenue architecture breaks (because it does break—we know this).

Within 6 months: Manual billing tasks have dropped 70%. Usage-based invoicing is automated. Finance, Ops, and GTM teams have self-service dashboards they actually use. You've made real build-vs-buy recommendations on subscription management.

Within 12 months: We have real-time revenue visibility across all products and geographies. We've scaled 10x in customers without scaling ops headcount linearly. Billing errors are under 1%. You've built predictive models that tell us about churn and expansion before we need them.