AI Platform Engineer - 1815
Location: San Francisco, CA (Onsite)
Job Type: Full-Time
Compensation: $200,000 – $300,000 Base Salary + Equity
About the Role
We're looking for experienced AI Platform Engineers to build and scale the infrastructure that powers an AI-first engineering organization. This is one of the highest-impact roles on the team, focused on improving developer productivity, strengthening platform reliability, and enabling rapid product innovation.
You'll own the systems that support deployment, security, observability, AI-assisted development, and cloud infrastructure. Your work will directly increase engineering velocity while helping the company scale enterprise-ready products.
This role is ideal for someone who thrives in startup environments, enjoys solving complex infrastructure challenges, and has a passion for building scalable internal platforms.
What You'll Do
- Design, build, and maintain scalable platform infrastructure supporting engineering teams.
- Improve CI/CD pipelines, deployment workflows, testing frameworks, and developer environments.
- Build AI-powered internal tools that increase engineering productivity and accelerate software delivery.
- Strengthen platform security, compliance, monitoring, and operational readiness.
- Evaluate and implement modern infrastructure, storage, and compute technologies.
- Design reliable cloud infrastructure with a focus on scalability, performance, and cost optimization.
- Support production environments, troubleshoot incidents, and implement long-term reliability improvements.
- Enable both technical and non-technical teams to safely build, test, and deploy software.
- Partner closely with engineering leadership to evolve the company's AI-first development platform.
Required Qualifications
- 5+ years of Platform Engineering or Infrastructure Engineering experience.
- Experience building and maintaining production infrastructure within a B2B SaaS environment.
- Startup experience, ideally at a post-Series A company.
- Proven experience supporting production systems through rapid growth and scaling.
- Strong understanding of deployment automation, reliability engineering, monitoring, and infrastructure operations.
- Bachelor's degree required.
Technical Qualifications
Candidates should have experience with many of the following technologies:
Cloud & Infrastructure
- Kubernetes
- Docker / Containerization
- AWS, GCP, or Azure
- Cloud networking
- Infrastructure monitoring
- Reliability engineering
- Rollbacks and deployment strategies
- Database migrations
Development & Automation
- TypeScript
- Python
- CI/CD pipelines
- Modern developer tooling
- Remote development environments
- AI-assisted software development tools
AI Engineering
- AI-first development workflows
- AI coding assistants
- Developer productivity tooling
- Internal AI automation
Nice to Have
- ETL pipelines
- Cloudflare
- SOC 2 environments
- Web application infrastructure
- Chrome extension development
- Martech or data platform experience
Preferred Qualifications
- Previous Founder or Founding Engineer experience.
- Experience helping scale startups from Series A through Series B.
- Background with modern B2B SaaS infrastructure or horizontal software platforms.
- Experience building enterprise-grade infrastructure that supports rapid product development.
- Degree from a highly regarded university is a plus.
What We're Looking For
The ideal candidate is highly technical, self-sufficient, and passionate about building infrastructure that empowers other engineers.
Successful candidates will demonstrate:
- Strong ownership mentality.
- Startup mindset with a bias toward execution.
- Excellent engineering judgment across security, scalability, reliability, and speed.
- Deep curiosity about AI-assisted software development.
- Ability to work independently while collaborating across multiple teams.
- Passion for improving engineering productivity through automation and platform tooling.
- Attention to detail and commitment to operational excellence.
Candidates Unlikely to Be a Fit
The following backgrounds generally do not align with this opportunity:
- Engineers whose experience is exclusively within large enterprise or FAANG organizations.
- Candidates who prefer architecture or leadership roles without remaining hands-on.
- Engineers who are unwilling to manage infrastructure, production systems, or operational responsibilities.
- Professionals lacking startup experience or exposure to rapidly scaling engineering environments.
- Candidates who are not detail-oriented or comfortable working across multiple technical domains.