About the role
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.
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