Support Systems Engineer (AI/LLM SaaS) at Toma

Location: San Francisco, Bay Area
Team: Customer Success | Reports to Head of Customer Operations

About Toma

At Toma, we’re building something unorthodox — a fully AI-driven voice platform reshaping how 18,000 car dealerships operate. Our proprietary voice AI handles inbound calls, sets appointments, and unlocks agentic workflows that reduce frontline workload.

We’re a 20-person team (ex-Scale AI, Uber, pro Valorant player, robotics champ, motocross racer...) obsessed with getting dealers real results. We’ve landed dozens of rooftops via word-of-mouth, and we’re just getting started.

The Role

We’re looking for a Support Systems Engineer to help us scale fast — without breaking.

You’ll be the first technical hire on the support side, working directly with Ops, Engineering, and Product to debug complex issues, build internal health monitoring systems, and lay the foundation for a scalable support layer.

This is not a traditional ticket-based support role. It’s part forward deploy, part triage lead, part system builder. You’ll get deep in the weeds, own high-impact technical problems, and play a foundational role in how support functions at Toma as we scale.

What You’ll Do

Technical Debugging & Triage

• Manage a support queue & build systems to improve support metrics.

• Investigate LLM-related issues, agent behavior, voice system bugs, and integration failures

• Reproduce edge cases and partner with Engineering to drive root-cause fixes

• Triage and document inbound issues for the product and AI teams

Build Health Monitoring & Tooling

• Design and implement health monitoring for AI behavior, call routing, scheduler integrations, and more

• Create dashboards, logs, and alerting systems to reduce support lag

• Write light internal scripts and tools to automate repetitive ops or support tasks

Build Support Processes

• Be the connective tissue between Engineering, Ops, and Product

• Own and improve the way support is delivered and scaled: ticket systems, SOPs, playbooks

• Build an internal knowledge base for common issues and config workflows

Act as a Strategic Operator

• Flag product risks and recurring friction points for Engineering

• Help prioritize bugs and UX friction based on support trends

• Recommend product improvements based on what you’re seeing in the trenches

You Might Be a Fit If You...

• Have 2–5 years in a technical support, infra, dev ops, or forward deploy role, ideally at a startup

• Love solving messy technical problems in live customer environments

• Can read logs, reproduce bugs, and work directly with engineers on triage

• Have experience with AI systems (LLMs, agents, vector databases) or are excited to learn fast

• Can write basic scripts (Python, JS, Bash, SQL, etc.) to unblock yourself or automate tasks

• Thrive in ambiguity and want to build support systems from scratch — not inherit them

Nice to Have

• Experience with tools like Postman, Airflow, Segment, LogRocket, or voice AI platforms

• Background in automotive, SaaS, or customer-facing AI products

• Startup experience where you’ve been “the one who gets called when it breaks”

Why This Role Matters

We’re growing fast, and every new customer means more complexity. The systems you build — and the fires you put out — will directly shape our ability to scale, retain, and grow revenue across hundreds of rooftops.

You won’t just answer tickets. You’ll own the support systems that reduce customer effort & pain.

What Success Looks Like

• You become the go-to point of contact for escalations and AI troubleshooting

• You reduce our average support resolution time through better tools, monitoring, and triage

• You help launch a proactive support function — not just reactive firefighting

• You elevate how Toma learns from customer pain, product bugs, and systemic issues

Compensation & Perks

• Competitive salary and early-stage equity

• Health, dental, vision

• Daily food stipend

• Health & wellness stipend

• Educational stipend

• High-impact seat on a low-ego, high-output team