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Salary
$145k – $281k per year (Estimated)
Location
In office (New York)
Seniority
Senior
Employment
Full-Time
Overview
Company
Impact
Profile match
Mutiny personalises websites and landing pages for each visiting account using machine learning on firmographic and behavioural signals. Founded in 2018 in San Francisco, it lets marketers run experiments without engineering support. Enterprise software companies use it to lift conversion on high-value accounts.

What we're building

Mutiny is the self-improving AI infrastructure for GTM teams to execute faster and close more revenue. Our ambition is to do for revenue velocity what Cursor and Claude Code did for engineering velocity. With Mutiny, everyone in sales and marketing gets a bench of GTM athletes that handle any work across their revenue motion and learn from what's actually moved their deals.

In April we re-launched the product as an agent-first platform. Anthropic showcased us as a leader in AI GTM. MRR is growing more than 70% month-over-month, with customers like Uber, Rippling, and Snowflake. We're backed by Sequoia, YC, and Insight, and we're building a generational company.

The opportunity

Most engineers spend their career making predictable systems faster. You'll spend yours making non-deterministic ones trustworthy. As a senior engineer on our AI product team, you'll architect the Campaign Builder and Agent experiences marketers and sellers open every day to go from idea to personalized assets in minutes. You'll partner directly with product, design, and the founders to define what an agent-first GTM platform should feel like, and your calls on architecture, evals, and guardrails compound across thousands of customer accounts. This role is in person in New York City, five days a week, and we ship weekly.

What you'll own

  • The core agent surfaces. Architect and ship the Campaign Builder and Agent experiences end-to-end. Frontend, backend, prompts, evals, the whole stack.

  • Reliability on top of LLMs. Make non-deterministic models feel deterministic at the surface. Build the retries, fallbacks, and orchestration so the customer never sees the failure mode.

  • Evals and guardrails. Define how we measure quality, catch regressions, and keep brand and tone consistent across thousands of customer accounts.

  • Speed and feel. AI products live or die by latency and the loop between intent and output. You'll obsess over both, and use coding agents and agent networks to ship faster than felt possible last year.

  • Product definition. You're not waiting for a spec. You sit with product and design, prototype the hardest interactions yourself, and decide what ships.

  • The next ten engineers. What you ship defines how we build. Code review, hiring, and the architectural calls that shape the next year.

Who you are

  • Full-stack by instinct. You're autonomous from prompt to backend to UI. You'd rather own a feature end-to-end than hand off pieces and hope.

  • AI-native. You've shipped on top of LLMs in production. RAG, evals, agent frameworks, coding agents. You know which abstractions hold up at scale and which were research-paper hype.

  • Sharp at the fundamentals. You're strong in a backend language (Python, TypeScript, Kotlin, Ruby, pick your weapon) and you write code that still reads well a year later.

  • A clear communicator. You explain nuanced technical decisions in writing and in real time. Your design docs make the room smarter.

  • Builds in ambiguity. Specs are sketches at Mutiny. You'd rather prototype the hard interaction yourself than wait for clarity.

  • Raises the bar. You make the engineers around you better. Sharp in code review, generous with junior engineers, direct when something is wrong.

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