What You'll Do
- Own and lead product features end-to-end: research, design, implement, test, and ship
- Lead and shape engineering architecture - set standards for code quality, testing, and development practices across the stack
- Mentor and guide other engineers in adopting AI-native workflows, establishing best practices and patterns
- Talk directly to customers and translate vague requirements into polished user experiences
- Design scalable backend systems (Python, FastAPI, PostgreSQL, GCP)
- Write clean, maintainable, and testable code with minimal oversight
- Drive architectural decisions and engineering processes that maximize AI-assisted development velocity
- Ship fast and learn fast - high urgency environment
You're a Fit If
Engineering Foundations:
- 2–6 years of professional full-stack experience at a product-first company or FAANG-level environment (Senior SDE ownership expected)
- Comfortable building features across the entire backend stack
- Care deeply about product, design, and user experience—not just code
- Have owned something meaningful end-to-end (a product module, infrastructure refactor, major feature launch)
- Can set standards for engineering quality and architectural decisions in an AI-native environment
- Resourceful and thrive in ambiguous environments—you figure things out independently
- Have strong product intuition and can push back on requirements when needed to improve outcomes
AI-Native Development:
- AI coding experience is your most important and necessary skill - you have deep understanding of modern coding tools, specifically Claude Code, and are proficient with its various modes (Interactive, Plan, Headless, Agent Teams, Delegate)
- You're "AI-pilled" when it comes to problem-solving - you tackle any new problem, skill, or architectural challenge by leveraging AI tools and an AI-driven workflow. This is your default approach, not an experiment
- Strong systems thinking and architectural awareness - you direct AI to build while you architect, review, and verify. You know when AI output is correct and when it needs correction
- Can demonstrate recent AI-native work - you've shipped meaningful projects in the last 90 days where AI coding tools were your primary development environment
Technical Skills We Value
AI and Agentic Development:
- Claude Code proficiency: understanding of modes, context engineering (CLAUDE.md), custom commands, MCP integrations, and subagent coordination
- AI-driven development workflows and effective prompt engineering
- Ability to decompose complex engineering work into tasks suitable for AI assistance
- Strong judgment for when to leverage AI vs. when to code directly
- Experience verifying and reviewing AI-generated code for correctness, security, and maintainability
Backend:
- Python, FastAPI, PostgreSQL
- System design and scalable architecture
- GCP/cloud infrastructure
- API design (REST/GraphQL)
General:
- Code reviews, documentation, and establishing conventions
- Product analytics tools (Amplitude, Mixpanel) for data-driven development
Bonus Points If
- Experience building autonomous agents with the Claude Agent SDK or similar agentic frameworks—you understand multi-agent orchestration, MCP integrations, and production agent deployment
- Experience with AI image/video generation or manipulation - familiarity with tools like Midjourney, Runway, Stable Diffusion, Sora, or integrating generation APIs into product workflows
- You've built responsive, delightful UIs (React, TypeScript, Tailwind, shadcn/ui)
- You've worked at an early-stage startup or been a first/early engineering hire
- You've built internal tooling, dashboards, or systems that scaled to thousands of users
- You've led technical initiatives or mentored junior engineers
- You've built or maintained design systems
- You're curious about AI, e-commerce, or automation—we work in that space
- You've shipped side projects or contributed to open-source
- You've worked directly with designers and can contribute to design discussions