About the Role
You'll design and implement the AI integration layer across the software stack and operational tech stack. You'll establish Claude Code as the primary development paradigm, creating standards, templates, and guardrails for AI-assisted engineering. You'll build custom MCP servers, tool integrations, and agentic workflows that extend AI capabilities to non-technical teams. You'll create self-service AI interfaces enabling GTM and executive teams to request code changes, documentation updates, and operational automations without engineering tickets. You'll develop internal AI assistants with deep context on company systems, processes, and institutional knowledge. You'll establish governance, security, and review frameworks for AI-generated contributions, and measure and optimize AI adoption across the organization.
Requirements
- Deep hands-on experience with LLM APIs, prompt engineering, and agentic frameworks (Claude, OpenAI, LangChain, etc.)
- Strong software engineering fundamentals—you'll be writing production code, not just prompts
- Experience building internal tools, developer platforms, or automation systems
- Understanding of code review, CI/CD, and secure software development practices
- Ability to translate technical capabilities into organizational workflows that non-engineers can adopt
- Comfort operating in an early-stage environment with ambiguity and rapid iteration
- Background in fintech, payments, or blockchain infrastructure (nice to have)
- Prior work enabling "low-code" or "no-code" development for business teams (nice to have)
Responsibilities
- Design and implement the AI integration layer across Coinbax's software stack and operational tech stack
- Establish Claude Code as the primary development paradigm, creating standards, templates, and guardrails for AI-assisted engineering
- Build custom MCP servers, tool integrations, and agentic workflows that extend AI capabilities to non-technical teams
- Create self-service AI interfaces that enable GTM and executive teams to request and receive code changes, documentation updates, and operational automations without engineering tickets
- Develop internal AI assistants with deep context on Coinbax systems, processes, and institutional knowledge
- Establish governance, security, and review frameworks for AI-generated contributions
- Measure and optimize AI adoption, tracking metrics like ticket deflection, PR velocity, and cross-functional autonomy