Design and build small, high-impact full-stack tools from concept to deployment
Own the full SDLC: design, development, testing, deployment, and iteration
Work within a small pod to deliver quickly with a high degree of autonomy
Rapidly prototype and validate solutions with internal stakeholders
Integrate with third-party tools, APIs, and internal systems
Make pragmatic technical decisions appropriate for fast-moving tools
Use AI tools to accelerate development, testing, and code quality
Continuously refine, replace, or retire tools based on usage and feedback
Hands-on experience using AI-assisted development tools beyond basic code generation
Ability to leverage AI across the workflow (e.g., prototyping, debugging, test generation, QA, code review, security analysis)
Experience combining AI with automation/orchestration to streamline workflows and reduce manual effort
Familiarity with modern AI-enabled development environments and practices
Infrastructure as Code (e.g., Terraform)
CI/CD and modern DevOps practices
Experience with workflow automation/orchestration tools (e.g., n8n, Zapier, Temporal, Airflow)
Experience integrating SaaS tools and APIs (Slack, Notion, Jira, etc.)
Comfort building lightweight internal UIs (dashboards, admin panels, etc.)
Experience with one or more of the following languages: Python, TypeScript, Golang, Rust
Basic understanding of data engineering principles