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 who is both broad and deep someone who can hold the whole backend in their head and make good decisions across it, while also bringing a genuine spike that makes us meaningfully better in an area we're not yet strong in. That spike is the differentiator. Great engineering fundamentals get you to the interview. The thing you're unusually good at is what gets you the role.

This role sits at the intersection of two things that are rarely mastered together: building robust, production-grade Python services and designing durable, observable workflow systems with tools like Temporal. But more than the specific technologies, we're looking for someone with the ownership instinct and the range to become the de facto owner of our entire backend, its architecture, its reliability, and its evolution.

You will be a senior individual contributor working directly with the founders. The person in this role won't be handed a roadmap, they'll help define it and build the team around it.

What You Will 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.

Nice To Have:

• AI/ML infrastructure: Feature pipelines, embedding stores, evaluation datasets, async inference patterns. We're building in this direction and want someone who's already been there.
• SAP/ERP integration experience: We work in the enterprise supply chain space. If you've built integrations with SAP or other ERP systems understood their data models, their APIs, their quirks that's rare and valuable.
• Supply chain domain knowledge: You don't need to have worked in logistics, but if you have, you'll ramp faster and ask better questions.
• Data infrastructure depth: ClickHouse for analytics, dbt for modeling, pipeline observability. We want someone who isn't allergic to the data layer.
• PostgreSQL ownership: If you can own Postgres as a production system query plans, schema design, vacuuming, performance tuning that's a genuine differentiator. We want this covered; the question is whether it's your spike or something you're solid at.

Why Join Us

We're a small team building something genuinely complex a platform where backend reliability and correctness have direct consequences for how the product works and how the business runs. You won't be one engineer among many maintaining a system someone else designed. You'll own the backend: its architecture, its quality, and its direction with the autonomy to do it right and the trust to make real calls.

If you're a strong generalist who also has something they're genuinely exceptional at, and you want a role where both of those things matter, this is it.