AI Engineer

UNIT4 NV; Lisboa; Hybrid; EUR 90,000 - 130,000; Full time

Job summary

UNIT4 NV is seeking an AI Engineer to design, build, and operate production-grade AI and Generative AI solutions across the company. This hands-on role focuses on LLM applications, AI agents, RAG pipelines, and integrations with our enterprise platforms, especially in the Microsoft Azure and Copilot ecosystems.

You will translate architecture and business requirements into scalable systems, implement governance and security controls, and contribute to responsible AI practices across teams.

Qualifications

• Experience building production-grade AI/GenAI solutions.
• Experience turning business requirements into scalable AI systems.
• Knowledge of Azure-based AI platforms and enterprise integrations.

Responsibilities

• Design and implement AI-driven solutions that automate business processes, reduce manual effort, and improve service delivery across the organization.
• Build production-grade GenAI applications — LLM-powered features, AI agents, copilots, and orchestration layers — translating architectural patterns into working code.
• Contribute to PoCs and pilots, rapidly prototyping new capabilities and bringing them to a production-ready state when validated.
• Develop and integrate AI agents and multi-agent systems using established orchestration frameworks.
• Build APIs and microservices that expose AI capabilities to internal teams and products, following architecture and security standards.
• Integrate AI solutions with enterprise platforms via APIs, events, and connectors.
• Ensure designs support scale, reliability, and change management — versioning, backward compatibility, and clear contracts.
• Contribute to responsible AI practices and internal policy development by translating principles into engineering standards, reusable patterns, and reference implementations.
• Implement governance and security controls in code, including: data classification and PII handling, prompt injection defences and content filtering, audit logging and traceability, and RBAC/least-privilege access patterns.

Skills

Azure AI

GenAI apps

LLM apps

API design

Multi-agent systems

Security RBAC

Tools

Azure

Copilot

APIs

Microservices

RBAC

Job description

We're looking for an AI Engineer to design, build, and operate production-grade AI and Generative AI solutions across the company. This is a hands-on engineering role: you'll turn architecture and business requirements into working, scalable systems - including LLM applications, AI agents, RAG pipelines, and integrations with our enterprise platforms. The role has a strong emphasis on Microsoft Azure and the Microsoft Copilot ecosystem, which are our primary enterprise platforms.

Key Responsibilities

• Design and implement AI-driven solutions that automate business processes, reduce manual effort, and improve service delivery across the organization.
• Build production-grade GenAI applications — LLM-powered features, AI agents, copilots, and orchestration layers — translating architectural patterns into working code.
• Contribute to PoCs and pilots, rapidly prototyping new capabilities and bringing them to a production-ready state when validated.
• Develop and integrate AI agents and multi-agent systems using established orchestration frameworks.
• Build APIs and microservices that expose AI capabilities to internal teams and products, following architecture and security standards.
• Integrate AI solutions with enterprise platforms (e.g., CRM, ERP, ITSM, data warehouse, identity, observability stack) via APIs, events, and connectors.
• Ensure designs support scale, reliability, and change management — versioning, backward compatibility, and clear contracts.
• Contribute to responsible AI practices and internal policy development by translating principles into engineering standards, reusable patterns, and reference implementations.
• Implement governance and security controls in code, including: data classification and PII handling, prompt injection defences and content filtering, audit logging and traceability, and RBAC/least-privilege access patterns.