Research Lead

About Us

Mosaic AI is the only enterprise AI platform built for technical support in highly configurable, multi-product companies. We unify the customer, product, and support context scattered across a company’s systems, then act on it across the case lifecycle: automating what we can, escalating to a human expert when it matters. Built on 100+ deep integrations, the platform runs products already live in production, including Self-Service, Knowledge, Triage, Assist, Intelligence, Alerting, and QA, all sharing one foundation so they ship fast and improve as the platform grows.

That shared foundation makes this an exciting, unusual place to build. Each product we launch would have been an entire company in the pre-AI era; for us, it’s a focused product on common infrastructure, so each deployment builds on the last. Our no-code Agent Builder lets teams design and deploy agents with governance and traceability, while our Customer Context Model routes recurring issues and account risk to the teams that can fix them. Every deployment lowers our customers’ cost to serve. We’re hiring engineers and product leaders who want to build systems that get more capable the more they run.

About The Role

Mosaic builds the AI platform that technical support teams run on. Our agents, retrieval, and reasoning sit at the core of how customer-facing teams answer questions, resolve cases, and surface insights. The depth and reliability of that AI is the product.

You’ll start with an active research roadmap,, from self-improving evaluation infrastructure to agentic RAG to multimodality. You’ll work with a small team of researchers who are already in place. We’re looking for a hands-on researcher who will do much of this work directly, lead the team day to day, and grow into a bigger leadership role as the team expands. Expect most of your week to go to research and building.

What You’ll Do

• Work hands-on across the AI/ML core of the Mosaic platform (retrieval, agents, model routing, and evals) and own the research that improves it.
• Shape the research agenda with the VP of Product and engineering, including what we investigate, how we measure it, and what goes into the product.
• Lead a small research team day to day, set goals with each researcher, and help hire as the team grows.
• Work inside the product team and with engineering to turn research into features customers use.
• Define the quality bar for our AI outputs and make it measurable.
  
  

• MSc or PhD in Machine Learning, NLP, Computer Science, or a closely related field. This is a hard requirement.
• 6+ years of hands-on industry experience building production AI/ML systems.
• Real production experience with AI agents: designed, built, evaluated, and improved them. Not just experimented.
• Prior experience managing researchers or ML engineers.
• Independent research mindset: a point of view on what to bet on next, and the judgment to defend it.
• Track record of shipping research into product, not only papers or prototypes.
• Comfortable partnering deeply with engineering and product.
• You still enjoy writing code and running experiments yourself, and you want that to stay a big part of your job.
  
  

• Experience with enterprise B2B SaaS or applied research in industry (not only academic).
• Public contributions (papers, talks, open-source, technical writing) that show the way you think.
• Experience with RAG systems, evaluation infrastructure, or multi-agent orchestration at scale.