Senior Software Engineer, AI

Tono, Inc.

New York (NY)

Hybrid

USD 180,000 - 275,000

Full time

12 days ago

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Benefits offered by this job

Unlimited PTO
Medical, dental, and vision coverage
Direct access to founders
Hybrid NYC office

Job summary

Tono is building autonomous specialty medicine clinics, starting with dermatology. You will own and ship AI agents that handle clinical notes, intake triage, care coordination, and admin tasks, working in a TS monorepo with engineering and care teams.

You’ll also build shared infrastructure for high reliability, tracing, and evaluation. We seek 5+ years of TS experience, hands-on LLM agent work, eval design, and a drive to deliver in a regulated healthcare setting.

Qualifications

  • 5+ years of software engineering experience with strong TypeScript across frontend and backend.
  • Hands‑on experience building and shipping LLM‑powered agents in production.
  • Experience designing evals and tying quality metrics to outcomes.
  • Practical sense of making LLMs reliable with structured outputs and fallbacks.
  • Experience with data-labeling techniques and feedback loops.
  • Solid PostgreSQL fundamentals and schema design.
  • Comfort shipping iteratively with feature flags and instrumentation.
  • Ability to break down ambiguous problems and deliver.

Responsibilities

  • Own the agents that run Tono's clinic end to end and ship AI features.
  • Design evals and labeled datasets from clinician feedback to prevent regressions.
  • Build self‑improving loops where corrections flow back into prompts and tuning.
  • Add guardrails, human‑in‑the‑loop review, and safe fallbacks for reliability.
  • Debug agents with traces, logs, and replay to diagnose issues.

Skills

TypeScript
LLM agents
Eval design
Reliable LLMs
Data labeling
PostgreSQL
Feature flags

Tools

Mastra
LangGraph
Inngest
LoRA
Fine-tuning

Job description

About Tono

Specialty care is hard to access and even harder to run. Patients often wait months, and clinics rely on fragmented tools and manual workflows.

Tono builds software and operations together to make specialty care faster to access and easier to deliver, starting with dermatology.

We’re building a fully autonomous specialty medicine clinic: continuous, real-time care for patients anywhere.

What makes us different is how we build. We run two clinics of our own, a national telehealth practice and an in‑person clinic in DUMBO, Brooklyn. Our engineers work side by side with our doctors and care coordinators to build (mostly) every piece of the software from scratch. The long-term goal is for specialty clinics across the country to run on our autonomous EHR, freeing them from the administrative burden that slows care down.

Today we see patients in 33 states, covering more than 80% of the US population.

You will work closely with the co-founders and a team of engineers and physicians (backgrounds include Amazon, Apple, and leading academic medical centers). We are backed by Village Global (backed by Mark Zuckerberg, Jeff Bezos, Michael Dell, chaired by Reid Hoffman), HOF Capital, and Oncology Ventures.

What You'll Do

Own the agents that run Tono's clinic end to end. You'll design, build and ship AI agents that handle real clinical and operational work, such as drafting clinical notes, triaging intake, coordinating care, and automating the admin work that slows doctors down. You'll work in our TypeScript monorepo (Cloudflare DO, tRPC, Prisma, Postgres, Inngest) alongside the engineers, physicians and care coordinators who use what you build.

You'll also build the foundation other engineers build on: shared agent infrastructure, tool and memory abstractions, durable workflows, tracing, and the evaluation harnesses that tell us whether an agent is actually getting better. On any given week you might be:

  • Building an agent that turns a patient visit into a structured clinical note a doctor trusts

  • Designing evals and labeled datasets from real clinician feedback, then using them to catch regressions before they ship

  • Building self-improving loops where physician corrections flow back into prompts, retrieval and fine‑tuning

  • Adding guardrails, human-in-the-loop review and safe fallbacks so an agent fails gracefully

  • Debugging why an agent did something unexpected, using traces, logs and replay

We build AI that has to be reliable in production. That means structured outputs, evaluation loops, monitoring and clear escalation to a human when it matters.

How We Work
  • We ship quickly, with discipline: small PRs, clear ownership, and tight feedback loops.

  • Small team, broad scope. Engineers regularly work across frontend, backend, data, and infrastructure.

  • We ship with confidence in a regulated environment: feature flags, careful reviews, and safe migrations (including backfills). We use AI all the time but we do not vibe code our way into debt. Patients and doctors deserve better.

  • We invest in maintainability. Dependency upgrades, performance work, and removing dead code are part of the roadmap.

  • Observability is built-in. Logs, metrics, alerting, and error monitoring are part of the job.

  • We value builders. Curiosity, good taste, and a willingness to pick up whatever the system needs goes a long way.

Stack

Frontend: Next.js, TanStack Start, React

Backend: Fastify, tRPC, Prisma, PostgreSQL

Durable Workflows: Inngest

AI: Mastra, Flue, OpenAI, Anthropic, Vertex

Infra: Cloudflare, Turborepo, Doppler, AWS, GCP

Observability: Posthog

Data: Motherduck/DuckDB, dbt, dlt, Prefect, BigQuery

What We're Looking For
  • 5+ years of software engineering experience, with strong TypeScript across frontend and backend

  • Hands‑on experience building and shipping LLM‑powered agents in production, not just prototypes

  • Experience designing evals: test sets, LLM‑as‑judge, regression suites, and tying quality metrics to real outcomes

  • A practical sense of making LLMs reliable: structured outputs, retries and fallbacks, tool‑calling design, and monitoring

  • Experience with data‑labeling techniques and feedback loops that improve an agent over time

  • Solid relational database fundamentals (Postgres, schema design, migrations)

  • Comfort shipping iteratively with feature flags, instrumentation and tight feedback loops

  • The ability to take an ambiguous problem, break it down, and drive it to done

  • Care about code quality and take pride in your craft

  • Nice to have: experience with agent frameworks such as Mastra or LangGraph, durable workflow tools such as Inngest, LoRA or fine‑tuning, and startups, healthcare, regulated industries or multi-tenant systems

Compensation & Benefits

Salary: 180k - 275k commensurate with experience

Equity: Meaningful equity in a high-growth, venture-backed company

Medical: Medical, dental, and vision coverage

Growth: Direct access to founders and an agile team where your impact is highly visible. We do weekly demos with leadership

PTO: Unlimited PTO to recharge when you need it

Location

New York City preferred. We are hybrid and currently spend a few days per week in our DUMBO, Brooklyn office. We will consider fully remote for the right candidate.

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