AI Expert
Pubblicato il 24-10-2026 - Nokia in Vimercate
Job Description
Are you passionate about the intersection of Artificial Intelligence, Machine Learning, and robust software development practices? Do you have a foundational understanding of DevOps principles and a keen interest in applying them to AI solutions? We are looking for an Associate DevOps Engineer to join our team and contribute to developing, deploying, and maintaining AI-powered tools that streamline and enhance the daily workflows of our R&D; engineers across hardware, software, architecture, and test functions.
In this role, you will work closely with experienced engineers, learning to bridge the gap between AI development and operational excellence. You will help ensure our R&D; teams can leverage AI tools safely, effectively, and efficiently, gaining valuable hands‑on experience in a supportive environment.
How You Will Contribute And What You Will Learn
Support AI Solution Development & Integration:
- Assist in the development and integration of AI-driven tools and platforms (e.g., internal LLM chatbots, specialized applications) into existing R&D; workflows and systems.
- Collaborate with AI experts and R&D; engineers to understand their needs and contribute to building effective AI solutions.
- Learn about and contribute to use cases such as initial code drafting, test scaffolding, refactoring, documentation generation, test plan generation, script generation, log analysis, debugging, and design option exploration.
Contribute to DevOps Pipelines for AI:
- Support the building, maintenance, and optimization of CI/CD pipelines for AI models and applications, focusing on automated testing, deployment, and continuous integration.
- Gain hands‑on experience with tools like GitLab, Artifactory, Argo CD, and SonarQube for efficient and secure software delivery.
- Learn and apply DevSecOps practices to embed security throughout the AI solution lifecycle.
Assist with Infrastructure & Cloud Management:
- Help manage and provision cloud infrastructure (e.g., Azure, NESC, AWS) using Infrastructure as Code (IaC) principles with tools like Terraform and Kubernetes.
- Support the configuration and access for approved AI tools and environments, adhering to corporate policies and security baselines.
- Assist in the deployment and lifecycle management of containerized AI applications.
Monitor, Log & Optimize Performance:
- Contribute to implementing monitoring and logging solutions (e.g., Prometheus, Grafana, ELK stack) for AI tools and their underlying infrastructure.
- Learn to identify and help resolve performance bottlenecks, ensuring the reliability of AI services.
- Participate in the continuous improvement of AI-assisted R&D; processes by analyzing metrics and feedback.
Develop AI/ML Understanding & Application:
- Apply academic knowledge or project experience in machine learning fundamentals, algorithms (e.g., Linear Regression, Neural Networks, Deep Learning), and data science techniques.
- Develop skills in prompt engineering to maximize the effectiveness of large language models for R&D; tasks.
- Understand basic data preprocessing, feature selection, model evaluation, and deployment strategies in cloud and local environments.
Collaborate & Communicate:
- Work effectively within R&D; teams, learning from architects, product owners, and the PSE AI Council to align AI initiatives with business objectives and technical standards.
- Provide support to R&D; engineers on the effective and safe use of AI tools.
- Learn about and report suspected policy violations or data leakage related to AI usage through established channels.
Key Skills And Experience
- Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or a related technical field (or graduating soon).
- Academic projects, internships, or demonstrable personal projects showcasing an understanding of DevOps principles and practices.
- Foundational knowledge of AI/ML concepts, including basic model development or application.
- Familiarity with at least one scripting language (e.g., Python, Bash) and an eagerness to learn relevant AI/ML libraries.
- Basic understanding of cloud platforms (e.g., Azure, AWS, OpenStack) and containerization (e.g., Docker, Kubernetes).
- Awareness of IaC concepts (e.g., Terraform, Ansible).
- Basic understanding of monitoring and logging tools (e.g., Prometheus, Grafana, ELK).
- Interest in secure coding practices and DevSecOps principles.
- Strong problem-solving aptitude, analytical skills, and clear communication.
- Eagerness to learn and adapt in an agile, fast-paced R&D; environment.
About Us
Advancing connectivity