Senior Low-Code AI Agent Architect

NTT DATA Europe & Latam

Valencia

On-site

EUR 70,000 - 90,000

Full time

3 days ago

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Job summary

NTT DATA is seeking a senior Low Code AI Developer to join the team onsite in Valencia for a UN Agency project. The consultant assumes responsibility for developing AI Agents that directly add value to UN´s vision and deliver against the organisations mandate.

Design and deploy AI agents using Microsoft Copilot Studio, Azure OpenAI Studio, and Azure AI Foundry, integrate AI into business workflows, and ensure ethical AI with agile methods and telemetry tools to optimize performance and impact.

Qualifications

Master's degree in computer science or related field with two years of relevant professional experience, or;
University degree in the above fields with four year of relevant professional experience.
Hands-on experience developing and deploying AI agents using low-code/no-code tools such as Microsoft Copilot Studio, Power Apps, and Azure AI Studio, with a focus on real-world business use cases.
Proven experience integrating AI capabilities into business workflows using the Microsoft Power Platform and Azure AI services.
Strong practical knowledge of Microsoft Azure, particularly services supporting AI development, orchestration, data access (e.g., Azure AI Foundry, Azure Functions, Logic Apps, Azure Data Lake).
Demonstrated ability to troubleshoot and maintain low-code AI solutions, including multi-agent systems or coordinated agents in enterprise environments.

Responsibilities

Design and Deploy Low-Code AI Agents: Build tailored AI agents using Microsoft Copilot Studio, Azure OpenAI Studio, and Azure AI Foundry to address specific business challenges especially lightweight, high-value use cases where rapid automation can drive immediate impact.
Maximise Use of Microsoft AI Capabilities: Stay at the forefront of Microsoft's evolving AI feature set, proactively integrating new capabilities into existing solutions and workflows to enhance usability, productivity, and automation potential.
Develop and Maintain a Scalable Multi-Agent Architecture: Lead the creation and upkeep of low-code, multi-agent frameworks that support internal reuse, integration, and coordinated agent behaviour across the organisation.
Embed AI in Business Workflows: Collaborate with business process owners and solution architects to seamlessly integrate AI agents into existing workflows, ensuring ease of use, measurable value, and alignment with operational goals.
Ensure Compliance and Responsible AI Practices: Develop and deploy AI agents in line with the organization's standards on data protection, security, and ethical AI, promoting trust and accountability in every solution delivered.
Iterate and Optimise Agents Based on Feedback: Use agile methods, user testing, and telemetry tools such as Azure Monitor to iteratively refine agents for performance, reliability, and user satisfaction.
Translate Operational Needs into Agent Concepts: Work across teams to identify problems and opportunities that can be addressed through intelligent agents, translating these into practical, scalable solutions that meet real-world needs.