Applied AI Engineer

About this role

## About Pareto

Humanity is in a virtuous cycle: human insight improves AI, and better AI expands what people can do. Sustaining it depends on the one input that can't be automated: [expert human judgment](https://pareto.ai/blog/debating-persuasive-llms-truthful-answers).

At Pareto, we build the platform that turns that judgment into the [data](https://pareto.ai/blog/community-driven-knowledge-resource-ai), [evals](https://pareto.ai/blog/introducing-attunebench), and RL environments [frontier models](https://pareto.ai/blog/llm-metacognition-shared-and-shallow) learn from. We work with leading frontier labs like Anthropic and GDM, and we give skilled people everywhere a way to shape the future of AI and share in what it creates.

This RL environment and human-data infrastructure is already in production. Our job now is to scale it.

About This Role

Applied AI Engineers at Pareto build the internal systems that let the company scale. The work is unglamorous in the best way: data pipelines, training workflows, HITL infrastructure. Your job is to get ahead of the complexity before it slows things down. Design the agentic workflows and automation pipelines that let Pareto operate faster and break less.

You work directly with research, data, and product teams. You'll scope hard problems, decide what's worth building, and own what ships. The work feeds into training pipelines at Anthropic, GDM, and other frontier labs.

What You'll Do

• Design and build pipelines that generate synthetic tasks and eval environments for model training. Factory floor of AI development, not the models themselves.
• Architect HITL workflows. Decide what gets automated vs. what needs human review, how state survives handoffs, and what breaks first under load.
• Lead system design discussions. Write one-page scoping docs that surface hidden risks before development starts.
• Assess whether a technical idea is worth building. Get early signal, align stakeholders, then decide fast.
• W...