Senior Applied AI Research Engineer (Agentic Systems)

Job Overview And Responsibility

Most agentic AI work optimizes against benchmarks that don't push back. Here, the agent's hypotheses get tested at the bench — its reasoning is answerable to real experimental results, not a leaderboard. We have a working system orchestrating 300+ tools; what we need is someone to keep it at the frontier. You'll read the latest in agentic research, decide what's real, and ship it into a system where "better" means a better experiment runs next week. If you want your work on autonomous agents to be grounded in reality instead of demos, this is the rare seat where it is. - Own the research-to-production loop for our agent: survey emerging agentic techniques, run structured experiments against them, and ship what proves out. - Continuously upgrade core agent capabilities — planning, tool selection and reasoning, memory, multi-agent coordination — measured against real benchmarks, not demos. - Build and own the evaluation harness that tells us whether a change is actually an improvement. This is the backbone of the role. - Diagnose where the agent fails at the frontier of its current capability and design the fixes. - Set technical direction for agentic best practices internally; review, mentor, and raise the quality bar for the existing engineers. - Translate latest research into pragmatic engineering decisions under real reliability and cost constraints.