Forward Deployed Engineer

The role

As a forward deployed engineer, you'll work directly with customers to deploy and integrate our platform, building the infrastructure and tooling that turns research into production systems. You'll own customer engagements end-to-end. This includes architecting environments, building large-scale data pipelines, creating evaluation frameworks for model training, and ensuring our platform delivers value at scale.

What you'll do

• Deploy and integrate our platform within customer environments end-to-end

• Build environment simulations, data capture pipelines, and tooling for model training and evaluation

• Create applications and tooling to accelerate customer engagements

• Mock out and orchestrate customer-specific environments for model training and deployment

• Work with applied researchers to ensure training environments and data flows are production-ready

• Surface engineering requirements from customer engagements and contribute them back to the core platform

What we're looking for

• Strong software engineering fundamentals with the ability to build polished, functional applications quickly

• Experience building full-stack applications, data analysis tooling, or developer-facing products

• Ability to use large scale data and LLMs to solve valuable business problems

• Strong problem-solving skills in ambiguous, fast-changing environments with high autonomy

Strong candidates also have

• Background working with LLMs or ML systems in production

• Previous experience as a founder or early engineer at a zero-to-one company

• Demonstrated engineering creativity through side projects, open source contributions, or shipped products

About us

Applied Compute builds Specific Intelligence for the enterprise. We provide the continual learning infrastructure for companies to build agent workforces trained on proprietary data and institutional expertise. Our researchers and platform embed directly within customer environments to build custom evals, train models, and deploy agents that get better with use.

• Why we’re excited: We get to work at a rare intersection. Our product team builds the platform powering a new generation of digital coworkers. Our research team pushes the frontier of post-training and reinforcement learning. Our applied AI team sits side-by-side with customers as they ship agents into production. This combination of strong product, deep research, and boots on the ground is what we believe it takes to bring AI to the enterprise. We are product-led, research-enabled, and forward-deployed.

• Who we are: We’re a team of engineers, researchers, and operators. Many of us are former founders. We've built RL infrastructure at OpenAI, data foundations at Scale AI, and systems at Together, Two Sigma, Watershed, and others. We work with F50 customers and are fortunate to be backed by partners like Kleiner Perkins, Benchmark, Sequoia, Lux, and Greenoaks.

• Who Thrives Here: We're looking for people who are excited about applying novel research and complex systems to real-world problems. Our team genuinely enjoys working with customers: listening, empathizing, and understanding how work actually gets done in their organizations. Former founders, people who've built a lot of side projects, or anyone who's shown they can own something end-to-end, tend to do well here.

Benefits & Logistics

This role is based in San Francisco. We work from our office in the Mission. We offer:

• Competitive compensation and equity

• Generous health benefits

• Unlimited PTO

• Paid parental leave

• Daily lunches and dinners

• Transportation and relocation support

• Retirement plans

We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the process with you. We encourage you to apply even if you do not believe you meet every single qualification. As set forth in Applied Compute’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.