Senior AI Engineer

Job Description

Senior AI Engineer at Hermetic

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Remote · Full-time

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About Hermetic

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Restaurants and event venues lose bookings every day to slow replies. A guest asks about a rehearsal dinner on a Tuesday night, and by the time someone answers on Thursday, they’ve booked somewhere else.

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Hermetic fixes that with Mia, an AI assistant that picks up inquiries within seconds, answers questions about rooms, menus, and availability, follows up when a guest goes quiet, and hands the conversation to a coordinator at exactly the right moment.

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The Role

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You’ll own Mia’s conversations end to end: the agent that writes each reply, the models that decide whether a reply can go out on its own or should wait for a human, and the measurement that tells us whether a change actually made Mia better. The work sits across LLM systems, applied ML, and production engineering.

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What You’ll Work On

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• The conversation agent: Mia’s replies, routing, tool calls for availability and pricing, handoff detection, and guardrails that keep things accurate and on-brand.
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• Autonomy: Improve the models and per-location thresholds that predict which replies need an edit, so more can go out safely on their own.
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• Evaluation that drives decisions: Build offline eval sets from real conversations, regression tests for prompts and graph changes, and online metrics tied to what customers care about: edit rate, handoff rate, response time, and bookings.
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• Voice: Help take Voice Mia from early adopters to every customer, with per-customer rollout flags, safe call transfer, and instant rollback when something sounds off.
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• Running it for real: Tracing and cost tracking on every LLM call, prompt versioning, latency budgets, and being the calm person in the room when a model provider has a bad day.
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• Raising the bar: Write the design docs others build from, review code thoughtfully, and help engineers new to LLM systems get good at them fast.
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What You Bring

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• 6+ years building production software, including 2+ years shipping LLM-powered features that real users depend on
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• Strong Python, and comfort reading and changing TypeScript
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• Real experience with agent frameworks or tool-using LLM workflows, and opinions about where they break
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• Experience building evaluation for a model or LLM system and using it to make actual ship or don’t-ship calls
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• Practical ML skills: you can train, calibrate, and threshold a classifier, and explain the precision-versus-coverage trade-off to someone who isn’t an ML person
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• Solid production instincts around async queues, idempotency, retries, observability, and cost
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• Clear writing: your design docs and PR descriptions make it easy for others to act
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Nice to Have

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• Voice AI or real-time conversational systems
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• Experience in hospitality, events, booking, or conversational commerce
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• Human-in-the-loop systems, or learning from human edits
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• Hands-on time with SageMaker, Langfuse, or LangSmith
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Our Stack

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• Services: Python, TypeScript, React
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• Data: PostgreSQL, Redis, SQS
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• Infrastructure: AWS, Grafana, PostHog (analytics and feature flags)
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• Integrations: Twilio, plus the CRMs and booking systems our venues use, such as Salesforce and Tripleseat
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How We Work

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• We’re a small team with a lot of ownership, and you’ll ship to production every week.
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• AI coding tools are part of how we build. We expect you to use them well, and to know when not to trust them.
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