Requirements

5+ years of experience building and shipping production software systems
Strong backend engineering fundamentals (APIs, distributed systems, data modeling, reliability)
Experience building full stack systems, with comfort working across backend and occasional frontend surfaces
Hands-on experience working with AI/ML systems, LLMs, or inference pipelines in production
Ability to prototype rapidly while maintaining a clear path to production-grade architecture
Strong systems thinking — able to reason about orchestration, failure modes, and observability
Comfort operating in ambiguous, 0→1 environments with high ownership

Nice to haves

Experience building or operating agent-based systems or autonomous workflows
Familiarity with prompt engineering, evaluation frameworks, or model performance tuning
Experience integrating with internal enterprise systems (CRM, support tools, analytics platforms, etc.)
Background in building developer platforms or internal tooling
Experience designing guardrails, sandboxing, or safety layers for AI systems

Build and ship AI-powered agent systems that automate internal workflows and decision paths
Design and implement inference pipelines that reason over user interactions across internal systems
Prototype quickly to validate agent behaviors, then productionize what proves valuable
Architect backend services that integrate with multiple internal APIs and data sources
Define patterns for safe, observable, and controllable agent execution
Collaborate cross-functionally to identify high-leverage automation opportunities
Improve system speed, reliability, and signal quality as usage scales
Contribute to foundational design decisions for a 0→1 agent platform