Enterprise AI Architect – Claude Code & Agentic Engineering

Our requirements

• Strong hands-on experience with Claude Code in real-world software-development or business-workflow scenarios.
• Proven practical experience creating Claude Code Skills or comparable reusable capabilities for AI coding agents.
• Strong understanding of modern AI engineering and agentic AI patterns, including: agentic workflows, AI agent orchestration, tool use, prompt engineering, context engineering, structured instruction design, reusable AI capabilities.
• Strong professional software engineering background with the ability to design, implement, review, test and maintain production-quality solutions.
• Experience translating business requirements and domain knowledge into technical designs, structured workflows and executable AI instructions.
• Practical experience evaluating, troubleshooting and improving non-deterministic AI/LLM-based solutions.
• Strong understanding of software architecture and the ability to make decisions affecting an entire AI platform or capability.
• Experience defining engineering standards, reusable components and architectural patterns.
• Ability to establish clear quality criteria for AI Skills and determine what should be accepted, redesigned or rejected during technical review.
• Ability to distinguish between functionality that belongs within an individual skill and functionality that should be implemented as shared infrastructure.
• Strong technical leadership skills, including experience reviewing other engineers' solutions, providing technical direction and resolving blockers.

Optional

• Hands-on experience with Claude Code plugins and/or MCP servers.
• Experience with LLM evaluation and testing frameworks such as Promptfoo, LangSmith or custom evaluation harnesses.
• Experience working in consulting, professional services or client-facing technology environments.
• Experience building internal developer tooling or establishing a new technical platform/capability from the ground up.
• Public technical artefacts, such as: open-source AI/agent tooling, published Claude Code Skills or plugins, MCP servers, conference presentations, technical articles or blog posts focused on agentic engineering.

Your responsibilities

• Work directly with business stakeholders and domain experts to understand business objectives, processes, constraints, requirements and expected outcomes.
• Analyse business requirements, process documentation, examples, templates, operational knowledge and other reference materials.
• Identify business workflows and use cases that can be automated, enhanced or standardized using Claude Code Skills and AI agents.
• Design, implement, test and maintain reusable Claude Code Skills and related AI capabilities.
• Create structured skill instructions, supporting scripts, reference materials, validation logic and reusable workflow components.
• Translate complex, ambiguous or highly contextual business processes into clear, structured and executable instructions for AI agents.
• Design AI workflows that are reliable, maintainable, reusable and suitable for enterprise-scale adoption.
• Evaluate AI skill behaviour using realistic business scenarios, test cases, acceptance criteria and repeatable evaluation frameworks.
• Analyse non-deterministic AI behaviour and continuously improve the accuracy, reliability, consistency and usability of AI-generated outputs.
• Establish standards and guidelines defining what constitutes a well-designed and production-ready AI Skill.
• Determine which capabilities should be implemented as individual skills and which should become shared infrastructure or reusable platform components.
• Define technical standards for skill development, testing, evaluation, versioning, release management and backward compatibility.
• Provide technical leadership to other engineers through architecture reviews, code and solution reviews, technical direction and problem-solving.
• Unblock engineers and support the team in resolving complex technical and architectural challenges.
• Make and justify platform-level technical decisions related to agent harnesses, integration architecture, reusable components and build-versus-adopt strategies.
• Own the overall technical shape of the AI capability and platform rather than focusing solely on individual skills.
• Establish and continuously improve the development lifecycle for AI capabilities, including design, implementation, evaluation, release and maintenance.

About the project

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