AI Platform Engineer

Job summary

Build and scale an enterprise AI platform that enables development teams to run agentic workflows across the software delivery lifecycle, from specification and implementation through deployment and post-deployment operations. Develop production-grade agents, coding harnesses, tools, and MCP servers; establish machine-checked lifecycle gates and reusable, secure adoption patterns in partnership with DevOps, security, and platform teams. The role uses Python and/or TypeScript, LangChain, LangGraph, and coding assistants such as Claude Code.

Qualifications

• Strong software development background in Python and/or TypeScript or JavaScript.
• Ability to build, deploy, and operate production-grade services.
• Hands-on experience building agent-based AI solutions with LangChain, LangGraph, or comparable frameworks.
• Practical experience with MCP servers and custom skills, tools, and integrations for AI coding environments.
• Experience using coding assistants such as Claude Code in real-world engineering work.
• Experience developing reusable tools and automation for software development workflows.
• Understanding of AI agent architecture, tool calling, orchestration, and workflow automation.
• Experience integrating AI capabilities into DevOps and software delivery processes.
• Ability to collaborate across platform, security, and development teams.

Responsibilities

• Design and build AI agents across the software delivery lifecycle, from specification through post-deployment operations.
• Develop agents using coding harnesses, custom skills, tools, and MCP servers.
• Select platforms, frameworks, and technologies for specific use cases and enterprise requirements.
• Implement spec-driven development workflows and machine-checked lifecycle gates such as Spec Ready and PR Ready.
• Evaluate frontier AI models, coding harnesses, agent platforms, frameworks, and architectural patterns.
• Build reusable AI capabilities and maintain shared enterprise skill and tool catalogs.
• Partner with DevOps, security, and platform teams to deploy agents, skills, and tools safely into production.
• Demonstrate platform capabilities and provide technical guidance and troubleshooting to development teams.
• Establish scalable, secure, and reliable patterns for enterprise AI agent adoption.

Skills

Work schedule

Relocation