AI Backend Engineer

We are seeking an AI Backend Engineer to own core backend and infrastructure systems powering Zig's orchestration layer. This is a high-ownership role where you will design primitives, define state models, and ship to production rapidly. You will collaborate closely with customers to understand real-world workflows, edge cases, and failure modes. Daily collaboration with founders, frontend engineers, product teams, and directly with customers is essential to ensure our solutions function effectively in production environments.

Responsibilities:

• Design and build stateless backend services using Python and FastAPI.
• Define durable workflow state models driven by real customer workflows.
• Integrate AI agents into reliable execution pipelines.
• Build event-driven asynchronous systems, including queues, schedulers, and background jobs.
• Own prompt engineering and production LLM integration.
• Design clean APIs for consumption by frontend systems and agents.
• Engage directly with customers to understand workflow failures, practically debug production issues, and iterate quickly based on feedback.
• Ensure systems are observable, debuggable, and resilient.
• Operate backend and AI infrastructure end-to-end.

Requirements:

• Strong backend experience, preferably 5+ years.
• Deep proficiency in Python and backend systems.
• Experience modeling durable, explicit states for asynchronous workflows.
• Practical experience with LLMs and prompt engineering in production environments.
• Comfort engaging directly with customers and reasoning about real-world workflows.
• Ability to transform ambiguous problems into clean system designs.
• Startup mindset: embracing fast iteration, comfort with ambiguity, and high ownership.
• Nice to have: Experience with workflow engines (Temporal, Prefect, n8n, LangGraph, Agno), event sourcing, open-source LLMs, or B2B SaaS/sales-tech.