Field Engineer

LLM usage has seen a meteoric rise in the past year, but there is still a significant gap between agentic innovation and its use in the real world. This is especially true for underserved industries like automotive and healthcare, where outdated systems persist due to barriers to entry, legacy software, and high-stakes consequences of hallucinations and failure.
Here at Toma (YC W24), we are bridging this gap by providing a customer-centric platform to deploy and monitor AI agents, even for non-technical users. We recently raised a $17M Series A from a16z and are building the future of human-AI interactions, starting in the automotive industry.

We’re assembling a team of Avengers: engineers, product managers, former founders, athletes, and leaders from Scale AI, Uber, Braze, Microsoft, Amazon, and more. We consider everyone regardless of their backgrounds or identities. Learn more about us here.

As a Field Engineer, you’ll be one of Toma’s first technical operators. You’ll live at the intersection of our customers and our technology, debugging live AI behavior, solving edge-case system issues, and building the internal infrastructure that allows us to scale support and reliability.

This is a technical and hands-on role that blends forward deployment, triage, and system design. You’ll move fluidly between talking to customers, writing prompts, investigating production issues, and automating monitoring or support processes. The systems you build will define how Toma delivers reliability and trust at scale.

• Own technical triage for live AI voice deployments, debugging agent behavior, call routing, and integrations.

• Work directly with Product and Engineering to identify and fix high-impact issues.

• Design and implement health monitoring, alerting, and observability systems across AI and voice infrastructure.

• Build internal tooling to automate repetitive support and ops workflows.

• Establish the foundation for a scalable, data-driven support motion: ticket systems, SOPs, playbooks, and knowledge bases.

• Partner closely with customers to understand pain points and translate them into durable engineering solutions.

• 2–5 years in a technical field role such as support engineering, forward deployed engineering, DevOps, or infra.

• Experience debugging distributed systems and APIs; can read logs and reproduce complex issues.

• Comfort writing light scripts (TypeScript/Python/Bash/etc.) to automate or diagnose.

• Familiarity with LLMs, vector databases, or AI systems or a hunger to learn fast.

• Strong customer instincts and communication skills. You like solving messy problems in the field.

• Experience standing up monitoring tools (e.g. Metabase, DataDog) or building dashboards.

• Bonus: experience in automotive, SaaS, or customer-facing AI products.

• Competitive salary with meaningful equity

• Free health, dental, and vision insurance

• Free in-office lunch and dinners

• Unlimited PTO