GeneralMind is a Berlin-based AI startup building an autonomous AI-powered supply chain automation platform. Backed by Lakestar, Leo Capital, and leading angels with $12M raised in January 2026, we're eliminating manual, inbox-driven workflows in enterprise supply-chain operations - automating Sales Order processing, Purchase Order lifecycle management, Accounts Payable, and Accounts Receivable. We integrate with SAP, Oracle, Microsoft Dynamics, and Salesforce, serving companies like a $16B food retailer and an $8.2B resources company.
Tasks
Backend Ownership
- Own the backend end-to-end: service architecture, API design, reliability posture, and long-term technical direction.
- Be the person who knows how everything fits together - and who other engineers come to when they're not sure where something belongs.
- Set the bar on code quality, service boundaries, and shared abstractions across the engineering team.
- Make foundational decisions with conviction, document the reasoning, and evolve them as the system grows.
Python Services & Production Systems
- Design for failure: retries, timeouts, graceful degradation, and recovery paths built in from the start.
- Write code that is easy to operate - observable, testable, and straightforward to debug at 2am.
- Understand the runtime, not just the framework. Know when the problem is the code, the config, or the infrastructure.
Workflow Engineering & Temporal
- Design and build durable workflows using Temporal - long-running processes, async coordination, saga patterns.
- Own workflow observability: know when a workflow is stuck, degraded, or silently wrong before a customer notices.
- Think carefully about idempotency, failure modes, and replay semantics — not just the happy path.
- Evolve workflows without breaking running instances; manage versioning with intention.
Reliability & Systems Thinking
- Detect regressions before they become incidents; build the tooling to catch them early.
- Own the operational posture of the services you build: alerting, runbooks, on-call readiness.
- Identify structural debt before it compounds; propose refactors that are thoughtful, not just correct.
Requirements
- Experience: 6+ years building and operating backend systems in Python, with clear ownership of production services - not just feature delivery.
- Python depth: Non-negotiable. You make deliberate choices about async vs. sync, framework selection, and performance tradeoffs. You know the language well enough to have opinions.
- Temporal or equivalent: You've used Temporal (or a comparable workflow engine) in production. You understand durable execution, not just task queues.
- Reliability instinct: Idempotency, retries, and observability are part of how you design, not afterthoughts.
- End-to-end ownership: You're comfortable being the person who holds the full backend picture. You identify what's broken or missing before you're asked, and you don't leave the system worse than you found it.
- A real spike: We're a strong team with broad coverage. What we're hiring for is someone who brings a 10x improvement in an area we're currently underinvested in. That might be workflow systems, data infrastructure, AI-native backend patterns, or deep domain expertise. We don't know exactly what shape it takes - but you should know what yours is, and be able to articulate why it matters.