AI Automation Engineer; Claude AI​/Agentic AI

TA-AI-1022-9AC

Role: AI Automation Engineer / Agentic AI Developer

Experience:

5+ years in software engineering, with hands-on experience in LLM and AI agent development

Location:

Bellevue, WA (Hybrid)
Work Authorization:

Green Card (GC) / U.S. Citizen

We are seeking a skilled AI Automation Engineer with hands-on experience designing and developing AI agents, Claude-based solutions, and enterprise workflow automation. The ideal candidate will have strong Python development skills, experience with Model Context Protocol (MCP), Claude Skills, API integrations, and production-ready AI solutions.

• Design, develop, and deploy AI agents using Anthropic Claude models and APIs.
• Build reusable Claude Skills and agent-based automation workflows.
• Develop custom MCP integrations to connect AI agents with enterprise systems.
• Implement Python-based automation, APIs, and asynchronous workflows.
• Build data-driven solutions integrating databases, external services, and enterprise platforms.
• Implement multi-agent orchestration, testing, monitoring, and AI governance.
• Collaborate with business and technical stakeholders to translate requirements into scalable AI solutions.
• Measure automation effectiveness, operational improvements, and ROI.

• Strong Python programming, REST APIs, asynchronous programming, and software engineering fundamentals.
• Hands-on development of LLM-powered applications and agentic AI workflows.
• Working knowledge of Anthropic Claude models, Claude APIs, tool use, and structured outputs.
• Experience designing Claude Skills and reusable AI automation workflows.
• Understanding of MCP architecture and secure tool integration.
• Experience integrating databases, APIs, and enterprise applications.
• Proficiency in SQL, JSON, YAML, Git, and data-processing libraries.
• Knowledge of AI evaluation, security, monitoring, and production deployment.

• Claude Code, Claude Agent SDK, and custom MCP server development.
• Multi-agent orchestration and AI agent evaluation frameworks.
• FastAPI, Pydantic, Pandas, Pytest, Docker, and CI/CD.
• Integration with Jira, Confluence, Git Hub, and Microsoft 365.
• RAG, vector databases, semantic search, and knowledge engineering.
• AWS, Azure, or Google Cloud.
• n8n, Apache Airflow, or similar automation platforms.
• Experience demonstrating measurable business benefits through automation.

Ideal CandidateA hands-on AI engineer who can independently identify business problems, analyze data dependencies, design Claude-based solutions, build reusable AI agents, integrate enterprise systems through MCP/APIs, and deliver measurable improvements in efficiency, reliability, quality, and cost.