Forward Deployed Research Engineer

Applied Compute•San Francisco, CA

1d•Onsite

About The Position

Applied Compute builds Specific Intelligence for enterprises, unlocking the knowledge inside a company to train custom models and deploy an in-house agent workforce. Today’s state-of-the-art AI isn’t one-size-fits-all—it’s a tailored system that continuously learns from a company’s processes, data, expertise, and goals. The same way companies compete today by having the best human workforce, the companies building for the future will compete by having the best agent workforce supporting their human bosses. We call this Specific Intelligence and we’re already building them today. We are a small, talent-dense team of engineers, researchers, and operators who have built some of the most influential AI systems in the world, including reinforcement learning infrastructure at OpenAI and data foundations at Scale AI, with additional experience from Together, Two Sigma, and Watershed. We’re backed with $80M from Benchmark, Sequoia, Lux, Hanabi, Neo, Elad Gil, Victor Lazarte, Omri Casspi, and others. We work in-person in San Francisco. The Role As a founding Forward Deployed Research Engineer, you’ll design, deliver, and scale production-grade AI agents and systems that sit at the core of some of the world's largest enterprises. These agents are already running in production across industries like finance, healthcare, and commerce. You'll own the process from pilot through deployment and continuous iteration, creating best practices as you go. You’ll partner directly with leaders at the world’s largest enterprises as well as cutting-edge startups, embedding AI agents into their workflows to transform how they operate at scale. Your work will also develop our core platform, surfacing unmet needs, prototyping new features, and collaborating with research and product to push the boundaries of adaptive intelligence.

Requirements

Experience building and scaling end-to-end production systems
Experience building RL environments and evals for language models
Strong technical problem-solving skills, especially in fast-changing, ambiguous environments
Comfort balancing speed of iteration with rigor, reliability, and craft
Customer obsession and ability to quickly anticipate customer needs

Nice To Haves

Experience building or deploying AI/LLM-powered systems in production
Familiarity with evaluation frameworks and agent tooling
Previous experience as a founder or early engineer in a zero-to-one environment
Strong full stack skills
Demonstrated technical creativity through published projects, OSS contributions, or side projects

Responsibilities

Ship production-grade AI agents that are essential for customers
Partner with enterprise leaders to understand their hardest problems and embed AI agents across their workflows
Shape the evolution of our platform through direct customer engagements, surfacing unmet needs and prototyping new tools and features
Collaborate with product, platform, and research teams to define architectures, eval frameworks, and generative agent development practices