Leads end-to-end backend feature development using Python, FastAPI, PostgreSQL, and GCP in an AI-native environment. Requires 2-6 years experience, deep Claude Code proficiency, and strong systems architecture skills for scalable systems.
30k – 60k/yr
Remote2+ YOEBackend Engineering
About the role
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
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