Senior Backend Engineer

About GeneralMind
GeneralMind builds AI Systems of Action for complex enterprise workflows. We deploy AI employees that automate messy operational handovers across supply chains - processing orders, validating invoices, coordinating suppliers, and handling exceptions directly on top of enterprise systems like SAP, Oracle, JDE, and Dynamics.
Our platform combines AI agents, operational context graphs, and real transaction data to achieve Autopilot-grade automation in real operational environments.
We work closely with leading global companies across manufacturing, retail, and logistics to deploy AI into mission-critical workflows.
About the role
We are looking for a Senior Backend Engineer to help own and evolve the core backend architecture of the company.
You will work directly with the founders on systems that orchestrate real operational workflows across emails, documents, humans, databases, and ERP systems. The work sits at the intersection of backend engineering, workflow orchestration, AI infrastructure, and reliability engineering.
This is not a feature-factory role. We want someone who can hold large parts of the system in their head, make strong architectural decisions, and raise the quality bar for the team.
What You'll Do
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.
What we are looking for
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.

Work arrangement
No