Remote AI Tooling Engineer: Build Internal AI Platform

Jobgether; Italia; Remote; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Fully remote work

Global team collaboration

Hands-on AI tooling with cutting-edge技

Job summary

Jobgether is seeking an AI Tooling Engineer in Italy to develop and scale an internal agentic platform that unifies company knowledge, data, and tools in a secure environment. You will own the full lifecycle from user needs to deployment, monitoring, and continuous improvement, using Python, LangGraph, LLM APIs, and MCP.

The role involves building AI agents and integrations, optimizing performance and costs, and ensuring robust access controls within a globally distributed team.

Responsibilities

• Help develop and maintain an internal AI platform combining agent development, systems integration, production engineering, and optimization to deliver practical tools.
• Collaborate with the Principal Engineer to design, develop, and deploy new platform capabilities from design to production release.
• Integrate internal systems and SaaS apps by connecting APIs and data sources with shared data models and access controls.
• Build AI agents and supporting tools, including MCP servers enabling agents to interact with internal systems and retrieve context.
• Design and improve retrieval workflows, tool calling, embeddings, prompts, and context management for accurate AI responses.
• Establish AI quality standards through evaluation datasets, benchmarks, regression testing, tracing, and observability.
• Monitor cost per answer and token usage; optimize models, prompts, and workflows for efficiency and reliability.
• Troubleshoot production issues, act on user feedback, and continuously improve the platform.
• Turn proofs of concept into secure, scalable cloud applications with proper infrastructure and identity management.

Job description

Jobgether is seeking an AI Tooling Engineer in Italy to develop and scale an internal agentic platform that unifies company knowledge, data, and tools in a secure environment. You will own the full lifecycle from user needs to deployment, monitoring, and continuous improvement, using Python, LangGraph, LLM APIs, and MCP.

The role involves building AI agents and integrations, optimizing performance and costs, and ensuring robust access controls within a globally distributed team.