The Hub | Senior Software Engineer

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Senior Software Engineer

Salary Competitive

Equity To be negotiated

The Role

We're looking for a Senior Backend Engineer to build the data foundation that powers our AI agents. You'll architect and maintain the systems that ingest, process, and unify customer data from multiple sources, handling millions of records while ensuring our intelligent agents have clean, reliable data to work with.

This is an on-site/hybrid position in Copenhagen with competitive salary and early-stage equity.

What You'll Build

Data foundation for AI agents: Build the complete data infrastructure that powers our intelligence system. This includes ETL pipelines that ingest from multiple data sources , intelligent deduplication logic that creates canonical records from millions of data points, and schemas in Postgres and BigQuery optimized for agent operations and fast querying.
AI agent infrastructure: Build the systems that agents run on. This includes orchestration logic, job queues for async processing, state management for agent workflows, and the data layer agents consume (endpoints, data formatting, access patterns).
Application backend and APIs: Design and build backend services and REST APIs that power our customer intelligence platform. Enable users to interact with agent insights, create spaces for different intelligence views, and access the data our agents surface.
Observability and debugging: Implement logging, monitoring, and debugging tools for both application services and agent operations. Make it possible to trace agent decisions, identify bottlenecks, and troubleshoot issues in production.
Cloud infrastructure: Deploy and manage services on Google Cloud Platform using Cloud Run. Handle infrastructure decisions, monitoring, and optimization as we grow

What We're Looking For

Data foundation for AI agents: Build the complete data infrastructure that powers our intelligence system. This includes ETL pipelines that ingest from multiple data sources , intelligent deduplication logic that creates canonical records from millions of data points, and schemas in Postgres and BigQuery optimized for agent operations and fast querying.
Backend experience: Strong Python skills and experience building production systems. You know how to handle data at scale, design clean APIs, and deal with messy real-world data sources.
Data infrastructure: Experience with Postgres, BigQuery, and cloud platforms (GCP preferred). You understand data modeling, schema design, and how to optimize for both writes and reads.
ETL expertise: You've built systems that extract, transform, and load data from various sources. You know how to handle edge cases, deduplication, and data quality issues.
System design: Experience building infrastructure for asynchronous workloads, job queues, and state management. Bonus if you've worked with AI/ML systems or agent architectures.
Production mindset: You write code that's maintainable and reliable. You think about monitoring, error handling, observability, and what happens when things break.
Generalist approach: You're comfortable working across the backend stack, whether that's data pipelines, REST APIs, cloud infrastructure, or agent orchestration systems.

Mindset We Value

Owner mentality: you take responsibility for your work's impact
Bias for action: you move fast, ship, and learn from real usage
No ego: you're proud of scrappy solutions that get results
Market obsessed: you care about solving customer problems, not politics or titles
Organized and focused: you bring structure to chaos and keep momentum

Technology

Backend: Python, REST APIs, Async processing, Job queues, State management
Data Infrastructure: PostgreSQL, BigQuery, ETL pipelines, Data modeling, Schema design
Cloud & DevOps: Google Cloud Platform (Cloud Run), Monitoring, Logging, Observability tools
AI Infrastructure: Agent orchestration systems, Data layer for AI agents, Workflow management

About the interview

Intro chat with a founder (CTO)
Paid take-home assignment based on a real design problem
2–3 day paid work trial (in-office in Copenhagen) to collaborate with the team and assess culture fit ‍

Compensation

Competitive salary and early-stage equity

‍ ‍

Please note: ‍We are currently only considering candidates who reside in Denmark due to the on-site/hybrid nature of this role.

For more information or questions please contact us at career@usepropane.ai

Perks and benefits

This job comes with several perks and benefits

Near public transit

Equity package

Paid holiday

Remote work allowed

Social gatherings

Central office

See all 8 benefits

Working at
Propane

See company profile

We've all been in that meeting. The one where everyone has a different take on what to build next. Someone quotes a customer call from last month. Someone else pulls up a support ticket. A third person has a Notion doc nobody else has read. Nothing connects. The decision gets made on gut feel — and you leave the room slightly unsure you got it right. Dennis lived that as a CPO for years. The context never made it to the room. Customer evidence scattered across six tools. Feedback from a €500 account carrying the same weight as a €50k one. Insights from last quarter's research buried before anyone shipped anything. He built Propane because that problem felt embarrassingly solvable — and nobody had solved it. The idea is simple: PMs deserve the same AI-native environment that engineers got with Cursor. A workspace where customer signals, company context, and agents that actually know your product work together — so you spend your time deciding, not searching. Propane connects your stack and builds from there. Signals from real customers, weighted by revenue. A shared surface to reason, write specs, and align the team. Agents that remember what your customers told you last quarter and help you act on it. We're a small team in Vesterbro, Copenhagen — a few minutes from the central station. Flat, direct, and low on process. Everyone owns something real. We hire makers — people who'd rather figure something out than wait to be told how, and who find genuine satisfaction in shipping something that didn't exist last week. Previous founders tend to feel at home here pretty quickly. Pre-seed, backed by people who've built and scaled companies like Lovable, ElevenLabs, Pleo, GameAnalytics, and Neurons. Early days — which means what you build now shapes what this becomes. If you want to shape what it means to be a PM in the age of AI — and you'd rather have real ownership over that than a comfortable title at a bigger company — we'd love to hear from you.