Software Engineer - AI Infrastructure (MCP / Agentic AI)

About Us

Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.

Role Overview

We are looking for a highly skilled Software Engineer to join an advanced AI Infrastructure team working at the forefront of the Model Context Protocol (MCP) ecosystem.

In this role, you will build the critical layer that connects cutting-edge AI models with enterprise-grade data systems. You'll work on enabling agentic coding assistants (e.g., Gemini CLI, Claude Code) to interact seamlessly with complex database environments, contributing directly to next-generation AI tooling and infrastructure.

This is a hands-on engineering role combining backend development, AI integration, and systems design in a fast-evolving space.

Commitments Required: 8 hours per day with an overlap of 4 hours with PST.

Employment type: Contractor assignment (no medical/paid leave)

Duration of contract: 6 months+

Location: LATAM, Eastern Europe

Interview: technical interview

Start Date: 1st week of June 2026

Responsibilities

• Design and implement MCP tools for managed MCP servers and open-source MCP Toolbox for Databases
• Enhance functionality and test coverage for tools used by agentic coding assistants and IDE-integrated AI agents
• Maintain and improve the MCP Toolbox for Databases codebase, focusing on scalability, reliability, and clean architecture
• Expand and maintain robust test suites for asynchronous AI tools and CLI-based systems
• Translate technical concepts and blog content into usable code samples and clear developer documentation
• Build and maintain high-fidelity data applications using QueryData to support internal experimentation and product development
  
  

• 5+ years of experience working with LLMs or AI systems that integrate external tools or data sources (e.g., MCP, tool-calling, agents)
• Strong proficiency in SQL, including writing and optimizing complex queries
• Hands-on experience with at least one relational or NoSQL database (e.g., PostgreSQL, MySQL, BigQuery, Spanner, MongoDB)
• Experience developing or maintaining backend systems, APIs, or developer tools
• Experience working with asynchronous systems or CLI-based applications
• Proven experience in writing, maintaining, and expanding automated test suites
• Experience refactoring codebases for scalability, maintainability, and performance
• Solid understanding of how AI agents manage context, tools, and data interactions
• Experience working with or contributing to shared or production-grade codebases (internal or open-source)
• Ability to write clear technical documentation and developer-facing content