About the Role
Are you looking at the AI revolution and trying to figure out how it can be used to make money? Are you playing with the latest tools like OpenClaw and trying to figure out how this is going to revolutionize the business world? Are you a high-potential person, but locked out of an entry job, and want to get your foot in the door at a fast-growing company with exposure to founder levels and the highest executives to show off your brilliance?
The AI Builder designs and builds internal software utilizing AI that simplifies, automates, and scales workflows across the organization. This role partners directly with all departments, including business, operations, data, and product to optimize workflows and rapidly create MVPs.
About You
The ideal candidate is a pragmatic builder - comfortable working close to the business, rapidly prototyping solutions, and turning them into reliable tools used by real teams. You are someone who is:
- Creative, technical, gritty, hungry
- Experienced in software engineering
- Experienced in turning messy workflows into clean systems
- Clear communicator with non-technical stakeholders
- High ownership, pragmatic, execution-focused
Core Responsibilities
Full-Lifecycle Engineering
- Own the end-to-end lifecycle of internal tools, from initial design and rapid prototyping to launch, iteration, and transition to steady-state ownership.
- Design and build scalable, AI-enabled systems and services that automate repetitive tasks and optimize complex workflows.
- Modernize technical debt by converting ad-hoc scripts and notebook-driven processes into robust, maintainable production software.
- Harden and validate solutions in development environments to ensure they meet rigorous standards for reliability, security, and scalability.
Strategic Collaboration
- Embed with internal teams to identify friction points and translate business requirements into technical designs that reduce operational risk.
- Partner with Product, Data, and Engineering to ensure all internal solutions align with the broader company roadmap and architectural standards.
- Manage stakeholders by setting clear expectations, communicating progress, and facilitating feedback loops to drive continuous improvement.
Enablement & Operational Excellence
- Drive adoption through the creation of lightweight training materials and hands-on enablement for new system implementations.
- Standardize documentation including system architectures, operational playbooks, and handoff plans to ensure long-term stability and ease of use.
Required Skills
Technical Engineering & AI Mastery
- AI-Augmented Development: Proven expertise using AI-native IDEs (e.g., Cursor, Windsurf, Claude Code) and LLMs to accelerate development and automate complex workflows.
- Modern Tooling: Deep familiarity with RESTful APIs, Git, CI/CD pipelines, and Agile methodologies.
- Bridge Builder: Ability to translate exploratory work from JupyterLab or ad-hoc scripts into maintainable, production-ready software.
Data & Systems Architecture
- Data Foundations: Solid understanding of SQL/NoSQL databases, data modeling, and structured data management.
- Systems Thinking: Ability to design for cloud environments while maintaining a strong foundation in software engineering principles.
- Applied AI: Skill in evaluating where AI provides genuine leverage versus where traditional software solutions are more appropriate.
Problem Solving & Execution
- Strategic Pragmatism: A "progress over perfection" mindset, with the ability to identify patterns, evaluate trade-offs, and prioritize high-impact solutions.
- Ambiguity Management: Comfortable navigating messy, real-world business processes and technical challenges in a fast-paced environment.
- Analytical Debugging: Strong troubleshooting skills with the ability to reason through complex system failures.
Communication & Collaboration
- Cross-Functional Fluency: Exceptional communication skills, with the ability to explain technical concepts to non-technical stakeholders clearly.
- Collaborative Spirit: Experience working in fast-moving teams where iterative feedback and flexibility are key to success.
Nice-to-Haves
- Degree in Computer Science, Engineering, or equivalent practical experience
- Experience building internal platforms or operational tooling
- Experience in Node.js, with a track record of building internal tools, services, and robust automations.
- Experience in Python and SQL; comfortable building tools, services and automations
- Familiarity with workflow orchestration, job scheduling, or data pipelines
- Exposure to containerization (Docker) and cloud-native tooling
- Prior experience working directly with operations or business teams