Senior Principal AI Architect

Product Engineering develops and establishes many of the processes used throughout product development, qualification, and manufacturing. As product complexity, engineering data, and production volumes continue to grow, these processes must evolve into connected, traceable, and AI-ready systems. The Senior Principal AI Architect establishes technical direction and drives adoption of AI/ML and automation across OMG. The role works across engineering functions and with AI/ML experts throughout Nokia to develop shared methods, reusable solutions, governance frameworks, and practical capabilities that improve engineering effectiveness throughout the product lifecycle. Success is measured by organizational adoption, development of engineering capability, delivery of scalable solutions, measurable improvement in engineering practice, and influence of AI/ML methods across Nokia engineering organizations. Master's degree or higher in Electrical Engineering, Computer Science, Data Science, Physics, Photonics, Applied Mathematics, or a related field, or equivalent relevant experience. Demonstrated organizational and technical leadership in AI/ML, analytics, software, or automation for engineering, product development, test, or manufacturing. Strong technical depth in programming, data analysis, and tool development using Python or similar technologies, with the ability to guide teams and review solution approaches. Experience with modern AI/ML methods and architectures, including agents, skills, RAG, knowledge systems, engineering data systems, traceability, or decision-support tools. Experience with optical transceiver products, photonics, DSP, semiconductor technologies, Product Engineering, or manufacturing and test systems is highly desirable. Demonstrated experience defining organization-level technology strategy, roadmaps, and architecture direction across multiple engineering organizations. Demonstrated success establishing enterprise-scale technical standards, governance frameworks, or architecture methods. Experience leading large cross-functional transformation initiatives involving engineering, operations, IT, manufacturing, or external partners. Experience influencing technology investment decisions, platform strategy, build-versus-buy evaluations, and partner selection. Experience building technical communities, competency-development programs, workforce plans, or AI/ML enablement programs. Ability to communicate AI/ML strategy, opportunities, risks, and investment recommendations to senior and executive leadership. Recognized technical authority in AI/ML, engineering automation, knowledge systems, or digital engineering transformation. Experience evaluating technical talent, forming teams, and working with internal and external delivery partners. Experience leading cloud-based AI/ML, data, or engineering platform initiatives. Experience defining project scope, priorities, deliverables, risks, and stakeholder alignment across organizational boundaries.