Назад
4 дня назад

Head of AI Enablement

Тип работы
fulltime
Грейд
head
Английский
b2
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Описание вакансии

TL;DR
Head of AI Enablement (LLM/Agentic Automation): Designing and implementing an AI integration layer across software and operational technology stacks with an accent on Claude Code standards, MCP servers, agentic workflows, and internal AI assistants. Focus on establishing governance and security frameworks, enabling self-service AI interfaces, and measuring adoption through ticket deflection, pull request velocity, and cross-functional autonomy.

Head of AI Enablement

Company

Coinbax

Conditions

3 days agoHead Ai Jobs by Coinbax

Skills

Agentic Framework Ai Automation Blockchain Ci/Cd Claude Code Review Developer-Platform Fintech Governance Langchain Llm Mcp Openai Payments Prompt Engineering Security Software Engineering

About the Role

You design and implement an AI integration layer across software and operational technology stacks. You establish Claude Code standards, templates, and guardrails; build MCP servers, tool integrations, and agentic workflows; create self-service AI interfaces for code changes, documentation updates, and operational automations; develop internal AI assistants; establish governance and security frameworks; and measure AI adoption through metrics such as ticket deflection, pull request velocity, and cross-functional autonomy.

Requirements

  • Deep hands-on experience with LLM APIs, prompt engineering, and agentic frameworks such as Claude, OpenAI, and LangChain
  • Strong software engineering fundamentals
  • 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 for non-engineers
  • Comfort operating in an early-stage environment with ambiguity and rapid iteration
  • Background in fintech, payments, or blockchain infrastructure
  • Prior work enabling low-code or no-code development for business teams

Responsibilities

  • Design and implement the AI integration layer across software and operational technology stacks
  • Establish Claude Code as the primary development paradigm with standards, templates, and guardrails
  • Build custom MCP servers, tool integrations, and agentic workflows
  • Create self-service AI interfaces for code changes, documentation updates, and operational automations
  • Develop internal AI assistants with context on systems, processes, and institutional knowledge
  • Establish governance, security, and review frameworks for AI-generated contributions
  • Measure and optimize AI adoption using ticket deflection, pull request velocity, and cross-functional autonomy metrics

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