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About the Role
As a GTM AI Engineer at Applied Compute, you will build the software, agents, and data infrastructure powering our go-to-market engine. Your systems will identify promising accounts, reach the right people, and transform business information into actionable insights. This is a software engineering role focused on internal GTM systems, involving design, coding, deployment, and improvement of team tools. You will own projects from problem definition to production, ensuring their architecture, reliability, and business impact. Collaboration with the GTM team is key to understanding workflows, prioritizing development, and enhancing systems as the company grows.
Responsibilities
- Build agents and applications for GTM workflows.
- Develop systems for account research, prospect discovery, outreach personalization, inbound qualification, and pipeline reporting.
- Build the data foundation by connecting CRM, communication tools, meeting transcripts, and external data sources.
- Ensure account and contact information is accurate, current, and accessible.
- Turn recurring work into reusable software by identifying and automating manual bottlenecks.
- Develop evaluations, review workflows, and feedback loops to improve LLM accuracy and agent behavior.
- Own production quality through code review, automated testing, monitoring, documentation, and reliable deployments.
- Debug failures and improve systems as usage grows.
- Instrument workflows to measure their impact on pipeline, conversion, and time saved.
- Use results to guide experiments and engineering priorities.
Requirements
- Prior professional experience as a software engineer or machine learning engineer, building and maintaining production systems on an engineering team.
- Strong programming skills in Python or TypeScript.
- Experience working with APIs, databases, and integrations.
- Hands-on experience building with LLMs, including tool use, agent workflows, and evaluations.
- Comfort working with SQL and messy data, including reconciling information across multiple sources.
- Strong engineering judgment to ship quickly while keeping systems understandable, testable, and maintainable.
- Ownership and product sense to turn ambiguous business problems into useful tools, work directly with users, and improve them based on evidence.
Skills
- Python
- TypeScript
- APIs
- Databases
- Integrations
- LLMs
- Tool use
- Agent workflows
- Evaluations
- SQL
- Data reconciliation
Location
- San Francisco
Work Type
- Onsite
- Full-time
Experience Level
- Professional experience
Salary/Compensations
- $160,000–$240,000
Benefits
- Meaningful equity
- Comprehensive benefits package
- Competitive compensation
- 100% employer-paid health insurance coverage for you and your family
- Unlimited PTO
- Paid parental leave
- Daily lunches and dinners
- Transportation and relocation support
- 5% 401k match
About the Company
- Applied Compute builds Specific Intelligence for the enterprise, providing continual learning infrastructure for companies to build agent workforces trained on proprietary data and institutional expertise.
- 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.
- We are product-led, research-enabled, and forward-deployed.
- We are a team of engineers, researchers, and operators, many of whom are former founders.
- Team members have experience building 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 backed by partners like Kleiner Perkins, Benchmark, Sequoia, Lux, and Greenoaks.
- We are 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.
Equal Opportunity
- 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.