Senior Applied AI Engineer

Role overview

This Senior Applied AI Engineer role centers on building and refining the core coding agents that power a fast, browser-based app builder used by a large monthly audience. You will work directly with product, design, engineering, and data teammates to address hard agent problems: evaluation harnesses, context compression, context retention across large codebases, multi-turn workflows, and everything from minor UI tweaks to major architectural decisions. This is not an API integration seat—you will shape how models generate and reason about full-stack applications alongside experienced engineers in a space where the patterns are still emerging.

Responsibilities

- Build and ship state-of-the-art coding agents, including long-running workflows, context compression, agent loops, and model routing. - Own agent capabilities end-to-end: planning, tool use, code generation and editing, and maintaining context across large codebases and multi-turn sessions. - Integrate and evaluate multiple LLM providers, benchmarking quality, cost, and latency, selecting the right model per task, and adopting new model features. - Design safe, reliable tool-use and workflow orchestration with structured actions, guardrails, and production observability. - Partner closely with product, design, engineering, and data teams to deliver robust AI features and mentor peers. - Build and maintain evaluation harnesses and datasets, analyzing failure modes and user feedback to continuously improve quality.

Requirements

- Track record of shipping LLM agents to production environments used by thousands of users. - Deep prompt-engineering skills, with the ability to craft, refine, and optimize prompts for varied tasks and models. - Solid software engineering fundamentals and experience building production-ready systems. - Comfort working autonomously, owning tasks end-to-end, managing complexity, and driving projects to completion. - Strong analytical and problem-solving abilities, including debugging nuanced agent behaviors in ambiguous situations. - Data-driven mindset with experience collecting, curating, and analyzing data to inform agent improvements. - Strong verbal and written English communication skills for cross-functional collaboration.

Nice to have

- Machine learning background, including familiarity with model evaluation metrics. - Experience contributing to or maintaining open-source AI or ML projects. - Experience implementing ideas from AI or ML research papers.

Benefits and work setup

- Fully remote team distributed globally, deeply collaborative, and passionate about the future of software development. - No college degree required. - Open to candidates outside the United States. - Encouragement to apply even if you do not meet every qualification listed.