AI engineer for agent systems

Toughbyte Ltd; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Требуется опытный инженер верхнего уровня для построения и поддержки продакшн-систем в Toughbyte Ltd. Вы будете работать над агенти-ными системами, генеративными медиа и инфраструктурой, устойчивой к сбоям, с акцентом на качество кода, документацию и постмортемы.

Ищем специалиста, который быстро пишет план, разворачивает рядом стоящие решения и умеет держать стандарты на уровне лучших практик для продакшена. Желателен опыт с LLM-агентами и производственными окружениями.

Qualifications

• Сеньор- или staff-уровень инженерии, жауапственный за продакшн-системы.
• Опыт работы с Python и TypeScript/React в реальном продакшене.
• Опыт разработки распределённых и высокоп throughput систем.
• Работа с LLMs в продакшене, наличие реальных релизов.
• Умение писать чёткие планы и качественный код.

Responsibilities

• Разрабатывать агентные системы и автономные планировщики.
• Обеспечивать надёжность и масштабируемость инфраструктуры.
• Развивать производственные пайплайны для генеративных медиа.
• Документировать планы, аудит и постmortems.

Skills

Python

TypeScript/React

Distributed systems

LLMs in production

Code quality

Tools

Claude Code

Cursor

Codex

Job description

Описание:

Building the entertainment studio of the future. Looking for AI filmmakers, data analyst, product manager, producers. Join us!

Задачи:

Agent systems. Fleets of agents that plan, create, critique, and repair autonomously, and stay reliable when nothing about them is deterministic. Generative media at scale. Getting consistent, high-quality output from frontier models, hour after hour. Behavioural intelligence. Understanding what drives attention and desire, and turning real-world response into better decisions about what to make next. Distributed infrastructure. Systems that scale with demand and survive the failures of everything they depend on. Consumer product. The owned platform, where audiences engage and convert.

Требования:

A senior or staff-level engineer, or a founder or early engineer who has carried a production system on your back. You are still deeply hands-on. Strong in Python and comfortable in TypeScript/React. Someone who has built distributed or high-throughput systems and debugged them in production. Already building with LLMs beyond the demo stage, in production, with real evaluation. A heavy, opinionated user of AI coding agents who already ships multiples of what you shipped two years ago. Fast, but with a very high quality bar. You can tell a real fix from a patch that hides the symptom. A clear writer. Our plans, audits, and postmortems are written documents.

Будет плюсом:

• Generative media, video pipelines, or film/TV experience
• Growth engineering, ad tech, or experimentation systems
• Consumer apps at scale
• Eval design for LLM systems
• Having founded something, or having been one of the first engineers somewhere

Условия:

Extreme ownership. You own an area from design to production to the 2 a.m. incident. Nobody hands you specs. You find the problem, write the plan, ship it, and measure it. Agent-native engineering. Most code here is written by humans directing coding agents (Claude Code, Cursor, Codex). The skill that matters is judgment: writing a precise plan, running agents in parallel, reviewing their output hard, and keeping the codebase small and clean. Our standard is that simple, correct code beats clever code. Production is the lab. We learn from real-world results, not demos. Outcomes are the metric. We judge work by measurable results, not by how impressive it looks.