AI Engineer (Open)
Job Description Summary: The AI Engineer is responsible for designing, building and deploying AI-powered solutions that support Nadara's AI transformation and operational efficiency goals. Working within the Digital and IT team, the role bridges applied AI research and production delivery—translating business needs into working automation and intelligence capabilities. The engineer will act as a technical lead on AI initiatives, owning the full lifecycle from discovery to deployment, and will champion responsible AI practices across the organisation.
Key responsibilities and Authorities
- Design and build AI solutions using Microsoft Copilot Studio, including custom copilots, conversational agents and embedded AI experiences integrated with enterprise workflows, data sources and APIs.
- Develop and maintain Power Automate flows to automate business processes, connecting AI capabilities with operational systems, workflows and data pipelines.
- Build and operationalise AI models and pipelines on Azure AI Foundry, leveraging services such as Azure OpenAI, Azure AI Search, Prompt Flow and model fine-tuning capabilities.
- Integrate AI solutions with Nadara's data platforms, including Snowflake, utilising Snowflake Cortex AI features (e.g., Cortex Analyst, ML Functions, LLM inference) where applicable.
- Collaborate with data engineers, domain experts and business stakeholders to define AI use cases, evaluate feasibility and translate requirements into technical specifications.
- Monitor and maintain deployed AI solutions, ensuring reliability, performance, security and compliance with internal governance standards.
- Evaluate emerging AI tools, frameworks and vendor offerings, providing evidence-based recommendations to the Innovation and R&D manager.
Technical and cross Competences (Optional)
- Hands‑on experience with Microsoft Copilot Studio: building custom copilots, configuring topics, actions and connectors, and publishing agents to Microsoft 365 and Teams environments.
- Proficiency in Power Automate, including cloud flows, integration with Microsoft Dataverse, SharePoint, Azure, and third‑party APIs.
- Working knowledge of Azure AI Foundry services: Azure OpenAI Service (GPT‑4o, embeddings), Azure AI Search (vector + hybrid retrieval), Prompt Flow for LLMOps, and responsible AI tooling.
- Experience with Python, SQL and/or .NET for scripting, API integration and AI solution development; familiarity with frameworks such as LangChain or Semantic Kernel is an advantage.
- Understanding of data engineering fundamentals and experience working with cloud data platforms; experience with Snowflake and its Cortex AI capabilities (Cortex Analyst, ML Functions, LLM functions) is a plus.
- Knowledge of MLOps and LLMOps practices: version control (Git), CI/CD pipelines, model monitoring, prompt versioning and deployment best practices on Azure.
- Fluency in English (spoken and written); additional European languages are a plus.
- Structured and organised, able to plan and track development tasks, milestones and dependencies.
- Proactive, inquisitive and solution‑oriented, with a strong drive to experiment, learn and iterate.
- Clear communicator, able to present technical concepts to both expert and non‑expert audiences.
- Collaborative mindset, working effectively with colleagues from engineering, operations, analytics, data and external partners.
- Strong sense of ownership and accountability for quality, timelines and knowledge transfer.
- Comfortable working in environments with uncertainty and evolving requirements, applying pragmatic judgement to balance innovation with delivery.
Education and Qualifications
Bachelor’s degree in a relevant field is required (e.g., Engineering, Science, STEM). Master’s degree is highly desirable, especially with a specialization in data, ML, genAI or a related field.
2+ years of professional experience in genAI and 4+ years’ experience in general Power Automate, data science, ML landscape.
Relevant certifications are a plus, such as Microsoft Certified: Azure AI Engineer Associate, Power Platform Developer Associate, or Snowflake SnowPro Core.
Portfolio of delivered AI projects or proof‑of‑concept work (e.g., GitHub repositories, internal case studies) demonstrating practical experience is highly valued.
Travel Requirements
The position is available in all locations where Nadara has offices and employees, ensuring representation across regions. A hybrid work model is in place, combining in‑office and remote work. Occasional travel may be required.
Location and Working Hours
Location: Lisbon. Time Type: Full time. Worker Subtype: Regular. A hybrid work model is in place; occasional travel may be required.