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.

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.

• 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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