Role purpose
Lead AI Engineer responsible for taking AI and Generative AI solution designs from architecture into working, production-ready software. The role leads technical implementation, guides developers, makes day-to-day engineering decisions, ensures code quality, and drives development from backlog refinement through deployment, monitoring, and support handover.

The role requires strong hands-on engineering skills, practical experience with Generative AI, RAG, agentic workflows, AI-assisted business applications, cloud-native development, APIs, integrations, CI/CD, testing, observability, and production operations. Computer Vision experience is a strong plus.

The Lead AI Engineer works closely with the AI Solution Architect, product owners, business stakeholders, developers, data engineers, cloud/security teams, and operations teams to ensure solutions are implemented correctly, maintainably, securely, and in line with agreed engineering standards.

What you will be doing

Lead implementation of AI, GenAI, ML, automation, and AI-powered applications.
Translate solution designs and requirements into development plans and working software.
Drive engineering delivery aligned with the target architecture.
Guide development teams on coding, integrations, testing, and operational readiness.
Build GenAI and agentic solutions using RAG, embeddings, vector search, prompt engineering, tool calling, and workflow orchestration.
Implement AI safety, quality controls, testing, and evaluation frameworks.
Design and develop APIs, backend services, integrations, cloud-native components, and supporting front-end functionality.
Lead code quality, reviews, CI/CD, documentation, and engineering best practices.
Support deployments, monitoring, troubleshooting, performance optimization, and operational handover.
Develop secure integrations with enterprise systems, data platforms, and business applications.
Build cloud-native AI solutions, preferably on Azure AI services and platform components.
Use AI-assisted development tools responsibly, ensuring human validation of outputs.
Mentor engineers, coordinate technical delivery, and communicate progress, risks, and decisions to stakeholders.

What will make you successful?

Bachelor’s or Master’s degree in Computer Science, AI, Data Science, Engineering, or a related field (or equivalent experience).
7+ years of experience in software engineering, AI, cloud, data engineering, or related technical domains, including 3+ years in a technical leadership role.
Strong programming frontend and backend development skills, preferably in Python, with experience building APIs and scalable applications.
Hands-on experience with Generative AI technologies, including LLMs, RAG, prompt engineering, vector search, and AI-powered workflows.
Experience developing and deploying cloud-native solutions, preferably on Microsoft Azure and Azure AI services.
Solid understanding of software engineering best practices, including testing, CI/CD, Git, observability, security, and production support.
Knowledge of MLOps/LLMOps, data engineering fundamentals, and secure application integration.
Proven ability to deliver secure, scalable, production-ready solutions in Agile, cross-functional environments.
Strong analytical, communication, collaboration, and mentoring skills.
Passion for innovation and emerging AI technologies.
Fluent English.

What we offer you

Working at the world’s only fully integrated aluminum and leading renewable energy company
Diverse, global teams
Flexible work environment/home office
We provide you the freedom to be creative and to learn from experts
Possibility to grow with the company, gain new certificates
Attractive benefit package