We are looking for a hands-on Senior AI Engineer to lead the technical design and delivery of enterprise AI agents and MCP-based integrations.

The team will develop Model Context Protocol (MCP) services for local business applications and build AI agents that consume both these local MCPs and MCP services provided by a global platform team.

The Senior AI Engineer will own solution design, support use-case discovery, provide technical leadership to the engineering team, and participate directly in implementation.

Required skills

- Strong hands-on Python engineering experience.
- Experience building LLM-based applications, AI agents or agentic workflows.
- Strong knowledge of REST APIs and enterprise integrations.
- Strong Microsoft Azure experience.
- Experience with authentication/authorization such as OAuth 2.0 and Microsoft Entra ID.
- Understanding of tool/function calling and agent-to-system integration patterns.
- SQL, JSON, Git and CI/CD.
- Ability to design production-grade solutions and provide technical leadership.
- Strong English communication skills.

Strong advantage

- Hands-on Model Context Protocol (MCP) experience.
- Azure AI Foundry / Azure OpenAI.
- Copilot Studio.
- Power Automate.
- Agent orchestration frameworks such as Semantic Kernel, LangGraph or similar.




- Azure Functions / API Management / Logic Apps.
- Experience with enterprise AI governance, evaluation and observability.

Responsibilities:

- Lead technical discovery and translate business use cases into AI/agentic solution designs.
- Design the architecture of AI agents and their interaction with local and general MCP services.
- Design and develop MCP services exposing capabilities of local applications to AI agents.
- Build enterprise AI agents and agentic workflows.
- Integrate agents with multiple MCP servers, APIs and enterprise systems.
- Define agent instructions, reasoning flows, tool-selection logic, approval workflows and human-in-the-loop guardrails.
- Define reusable patterns and engineering standards for MCP and agent development.
- Lead and support other AI engineers during implementation.
- Ensure compliance with enterprise security, architecture and AI governance requirements.
- Define and monitor agent quality and performance metrics, including task completion, tool failures, hallucinations, latency and cost.
- Collaborate with global AI/platform teams to ensure interoperability between local and global MCP capabilities.

📌 Senior AI Engineer / Technical Lead (Agentic AI & MCP) (España)
🏢 Intellias
📍 España