AI Architect
Required Experience & Qualifications
- AI & Agentic Engineering: Deep understanding of modern AI patterns—including agentic workflows, Model Context Protocol (MCP), tool use, prompt and context engineering, and structured instruction design.
- Hands-on Agent Experience: Proven experience applying Claude Code (or comparable AI coding agent frameworks) to complex software engineering or business automation problems.
- Core Software Engineering: Solid background in building, reviewing, and maintaining production-quality software solutions using modern programming languages (e.g., Python, TypeScript).
- System Architecture & Ownership: Demonstrated ability to make and defend foundational platform decisions, design shared developer infrastructure, and govern platform-level standards.
- Evaluation of Non-Deterministic Systems: Hands-on experience testing, debugging, and improving non-deterministic LLM-driven applications.
- Business-to-Technical Translation: Ability to interface with non-technical stakeholders, extract operational knowledge, and translate it into robust technical designs.
Preferred Qualifications (Nice to Have)
- Claude Ecosystem Mastery: Direct experience authoring official Claude Code Skills, custom plugins, or Model Context Protocol (MCP) servers.
- LLM Evaluation Frameworks: Familiarity with evaluation and observability tools such as Promptfoo, LangSmith, or custom evaluation harnesses.
- Domain Knowledge: Exposure to enterprise business domains such as HR technology, compensation & benefits, payroll, or workforce analytics.
- Developer Tooling Background: Prior experience building internal developer platforms (IDP), CLI tools, or enterprise integration harnesses.
- Consulting & Public Artifacts: Background in technical consulting/professional services, or public contributions (open-source agent tooling, published skills/plugins, technical articles, or conference talks on agentic engineering).
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