Founding AI Engineer

About the Company

This seed-stage startup, backed by Lightspeed Venture Partners, is developing an agentic service desk platform for managed service providers (MSPs) - a $500 billion global industry delivering IT services to small and midsized businesses. The company's AI agents assist technicians by investigating tickets, navigating the systems MSPs rely on daily, and executing approved actions on their behalf.

The organization is focused on building agents capable of reasoning through unfamiliar problems, adhering to policies, managing long-running workflows, and operating reliably across real customer environments. As a seed-stage company, the successful candidate will collaborate directly with the founders and play a pivotal role in shaping the product, technical foundation, and engineering culture from the ground up.

The Role

The Founding AI Engineer will be responsible for building the agents at the core of the company's platform, guiding them from early experimentation to reliable production systems. The role demands versatility - one week might involve enhancing an agent's ability to investigate an unfamiliar IT issue, the next could focus on designing evaluations that reveal failure points, and the following might center on developing the tools and infrastructure needed for safe operation across customer systems.

This individual will work directly with customers, contribute to product decisions, write production code, and operate what they ship. They will also help define how AI is applied across the MSP industry: determining which tasks agents should own, where human oversight remains essential, how decisions are explained, and what constitutes an excellent technician experience. The standards for AI-native service delivery are still being established, and this role offers a meaningful opportunity to shape them. This will remain a hands-on building position.

Key Responsibilities

1. Build and refine AI agents that investigate IT issues, maintain context, utilize tools across customer systems, follow policies, request approvals, and recover when unexpected situations arise.
2. Design evaluation systems that measure agent quality, expose failure modes, and convert production traces and customer feedback into actionable improvements.
3. Experiment with models, prompts, retrieval approaches, tool design, and agent architectures, then translate the most promising ideas into dependable production systems.
4. Develop integrations and backend infrastructure that enable agents to operate securely, reliably, and observably across long-running customer workflows.
5. Collaborate directly with customers to understand their challenges, deliver end-to-end product improvements, and help establish engineering practices and culture as the company scales.

Ideal Candidate Profile

1. Has built and shipped production software using modern AI models, ideally including agents or other tool-using systems.
2. Is an AI-native software engineer who experiments quickly with new models and techniques and turns promising prototypes into reliable production systems.
3. Knows how to evaluate nondeterministic systems, investigate failures, and balance speed with quality, safety, and customer trust.
4. Takes ownership, uses AI deeply in their work, possesses strong product instincts, and works comfortably with customers to transform ambiguous problems into working products.