Domain Architect - AI/ML
Nokia
In this role, you will lead the design, operationalization, and scaling of intelligent systems—from LLM-powered solutions to autonomous AI agents—driving innovation across multiple industries.
This position is ideal for a visionary architect with a passion for pushing AI boundaries and transforming cutting-edge research into production-ready systems. You will play a strategic leadership role, working closely with global teams to deliver advanced AI solutions that meet enterprise demands for scalability, security, and performance.
Nokia is a global leader in connectivity for the AI era. With expertise across fixed, mobile and transport networks, powered by the innovation of Nokia Bell Labs, we’re advancing connectivity to secure a brighter world.
Our recruitment process
We act inclusively and respect the uniqueness of people. Our employment decisions are made regardless of race, color, national or ethnic origin, religion, gender, sexual orientation, gender identity or expression, age, marital status, disability, protected veteran status or other characteristics protected by law. We are committed to a culture of inclusion built upon our core value of respect.
If you’re interested in this role but don’t meet every listed requirement, we still encourage you to apply. Unique backgrounds, perspectives, and experiences enrich our teams, and you may be just the right candidate for this or another opportunity.
The length of the recruitment process may vary depending on the specific role's requirements. We strive to ensure a smooth and inclusive experience for all candidates. Discover more about the recruitment process at Nokia.
- Flexible working arrangements and additional flex benefits to support work–life balance
- A minimum of 90 days of Maternity and Paternity Leave, with the option to return to work within a year following the birth or adoption of a child (based on eligibility)
- Medical and life insurance plan, plus paid sick leave for added security
- Meal allowance to support daily needs
- Car allowance based on eligibility
- Well-being programs to support your mental and physical health
- Opportunities to engage with Nokia Employee Resource Groups (NERGs), as well as access to mentors, coaches, and Employee Growth Solutions
- A learning culture that promotes continuous personal and professional growth – for your role and beyond
We are seeking a highly skilled AI/ML Engineer to design, deploy, and operationalize advanced AI/ML solutions with a focus on MLOps, Generative AI (GenAI), LLM Ops, and Agentic AI integration. This role requires deep expertise in ML engineering practices, cloud-native deployment, and hands-on experience with modern AI platforms. The engineer will be responsible for building scalable ML pipelines, LLM-based applications, and intelligent agent frameworks to accelerate delivery for telecom, enterprise, and next-generation autonomous network solutions.
If you have:
- Bachelor’s/Master’s in Computer Science, Data Engineering, AI/ML, or related field
- 10+ years of AI/ML engineering experience, including 5+ years in MLOps
- Proven experience with LLM platforms and GenAI ecosystems (e.g., OpenAI, Anthropic)
- Strong proficiency in Python, PyTorch, TensorFlow, and SQL
It would be nice if you also had:
- Experience with Ab-initio data management platform
- Familiarity with telecom data products and autonomous networks use cases
- Knowledge of vector databases and retrieval-augmented generation (RAG)
- Contributions to open-source AI/ML or GenAI frameworks
#LI-Hybrid
- Lead the design and scaling of advanced AI solutions, focusing on LLM-powered systems and autonomous agents.
- Build and optimize end-to-end ML pipelines, implementing MLOps best practices for model deployment and monitoring.
- Develop and operationalize generative AI solutions, including fine-tuning, prompt engineering, and RAG pipelines.
- Integrate autonomous decision-making frameworks with existing AI/ML systems for enhanced workflow orchestration.
- Collaborate with cross-functional global teams to translate AI/ML use cases into production-ready systems.
- Manage cloud-native AI/ML infrastructure, ensuring functionality across multi-cloud/hybrid environments.
- Ensure observability and governance for AI systems, focusing on compliance, fairness, and model drift.
- Support PoCs, customer pilots, and production rollouts while creating accelerators for faster time-to-market.