Software Engineer

Our AI tech client is looking for a Software Engineer.

We are looking for a highly skilled Software Engineer to join our AI Infrastructure team. In this role, you will be at the forefront of the Model Context Protocol (MCP) movement, building the connective tissue between advanced AI models and enterprise-grade data. You will be responsible for developing, refactoring, and maintaining the tools that allow agentic coding assistants to interact seamlessly with complex database environments.

What does day-to-day life look like?

• MCP Tool Development: Implement a variety of MCP tools for both managed MCP servers and the open-source MCP Toolbox for Databases.
• Agentic Integration: Expand test coverage and functionality for tools and skills utilized by leading agentic coding assistants (e.g., Gemini CLI, Claude Code, and other IDE-integrated agents).
• Code Maintenance & Refactoring: Take ownership of the MCP Toolbox for Databases codebase, focusing on refactoring legacy components and maintaining high-quality test suites.
• Technical Documentation: Bridge the gap between engineering and community adoption by converting technical blog posts into functional toolbox sample code and comprehensive documentation.
• R&D Support: Build and maintain a realistic, high-fidelity data application using QueryData. Use this environment as a primary testbed to support ongoing Product R&D, with a specific focus on advancing the Context Engineering Agent.

Requirements

• AI Protocols: Deep understanding of the Model Context Protocol (MCP) and its application in connecting LLMs to external data sources.
• Database Expertise: Strong proficiency in SQL and experience working with a variety of database engines (e.g., PostgreSQL, MySQL, BigQuery, Spanner, or NoSQL solutions).
• Software Testing: Proven experience in expanding test coverage for complex, asynchronous AI tools and CLI-based assistants.
• Agentic AI: Familiarity with "Agentic" workflows, including how AI models use tools, manage context, and navigate file systems/databases.
• Engineering Best Practices: Strong background in refactoring code for scalability and maintaining open-source repositories.

Nice to have

• Experience with Context Engineering (optimizing token utility and state management for LLM inference).
• Active contributor to open-source projects or developer advocacy experience.
• Familiarity with Cloud Identity and Access Management (IAM) and observability frameworks (OpenTelemetry).

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