AI Engineer (Full-Stack)

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• 4+ years of professional software engineering experience with a strong full-stack background
• Claude Code fluency: daily use in production as a core engineering tool
• Experience building and shipping full-stack AI systems in production including automations, AI agents, or LLM-integrated workflows
• Strong system design fundamentals including APIs, databases, and distributed systems
• Product-oriented mindset with strong ownership and ability to execute without heavy oversight
• Full availability during US business hours

Preferred but not strictly required:

• Experience with TypeScript, Python, or similar backend technologies
• Experience with modern frontend frameworks
• Exposure to cloud infrastructure such as AWS or GCP
• Experience with embeddings, vector databases, or retrieval systems

Nice to Have:

• Experience building AI copilots, autonomous agents, or AI-assisted developer tooling
• Familiarity with workflow automation platforms such as n8n, Make, or similar
• Experience with Replit for collaborative or cloud-based development workflows
• Exposure to DevOps or infrastructure-as-code practices
• Experience building internal automation tools that reduce manual overhead at scale

Claude Code and AI-Assisted Development:

• Use Claude Code as the primary development tool for writing, refactoring, debugging, and shipping production code
• Leverage Claude Code to accelerate full-stack development without sacrificing quality or maintainability
• Build editor utilities, automation scripts, and internal tooling using Claude Code workflows
• Continuously push the limits of what Claude Code enables across the stack

Full-Stack AI System Development:

• Design and build full-stack AI systems including automations, intelligent workflows, AI agents, and LLM-integrated products
• Integrate AI services, LLMs, and automation layers into both backend and frontend systems
• Build guardrails, monitoring, and fallback mechanisms that keep AI systems reliable in production
• Optimize prompt architecture, model usage, and system performance across live environments

Backend and API Architecture:

• Design and build scalable backend services, APIs, and data models that power AI features
• Architect clean service layers connecting AI components with application logic
• Ensure performance, security, and long-term maintainability across the full stack

Frontend and Product Integration:

• Develop and maintain frontend features and user-facing interfaces connected to AI systems
• Collaborate with product and design to translate requirements into robust, shippable systems
• Own features from initial architecture through deployment and iteration

Engineering Standards and Scalability:

• Write clean, well-tested, maintainable code that holds up at scale
• Contribute to CI/CD pipelines, observability, and deployment workflows
• Identify bottlenecks and propose automation or architectural improvements proactively

• Full availability during US business hours is required
• Only candidates who submit a Loom video will be moved to the next step of the hiring process