Senior Principal AI Architect

NOKIA; Dallas (TX); On-site; USD 180,000 - 260,000; Full time

Job summary

Nokia seeks a Senior Principal AI Architect to establish technical direction and drive AI/ML and automation across OMG. The role collaborates with engineering functions to develop reusable solutions, governance frameworks, and practical capabilities that improve engineering effectiveness throughout the product lifecycle.

You will guide teams in AI/ML methods, partner across departments to align methods and platforms, and define the OMG AI/ML roadmap in line with Nokia strategy.

Qualifications

• Strong leadership in AI/ML, analytics, software, or automation.
• Experience guiding cross-functional teams in engineering settings.
• Proven ability to develop reusable AI/ML solutions and governance.
• Excellent communication with senior leadership.
• Experience with cloud-based AI/ML platforms is preferred.

Responsibilities

• Lead AI/ML strategy, architecture, and adoption across OMG.
• Build reusable patterns for scalable, traceable AI/ML systems.
• Partner with Development, Product, Test, Manufacturing, IT and Nokia AI/ML communities to align methods.
• Define and maintain OMG AI/ML roadmap and investments.
• Mentor engineers and establish competency frameworks.

Skills

AI/ML leadership

Python programming

Analytics

Automation

Cloud platforms

Stakeholder communication

Education

Master's degree or higher in Electrical Engineering, Computer Science, Data Science, Physics, Photonics, Applied Mathematics, or related field

Tools

Python

TensorFlow/PyTorch

Data analysis tools

Job description

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.

• Lead OMG AI/ML and automation strategy, architecture, technical direction, priorities, and adoption across PIC, ASIC, TROSA, and Pluggable technologies.
• Build AI/ML capability across OMG through technical guidance, mentoring, reusable examples, and coordinated learning opportunities.
• Establish common methods, governance, knowledge systems, and reusable architecture patterns for scalable, traceable, and responsible use of AI/ML.
• Transform engineering data, workflows, knowledge, and traceability into AI-ready systems spanning development, qualification, manufacturing, reliability, and field performance.
• Guide engineers in the selection, development, validation, and use of AI/ML methods and reusable solutions, including agents, skills, RAG, analytics, and automation.
• Partner across Development, Product Engineering, Test, Reliability, Quality, Manufacturing, Operations, IT, and Nokia AI/ML communities to align methods, platforms, architecture, and best practices.
• Define and maintain the OMG AI/ML technology roadmap and align it with Nokia AI strategy, architecture direction, and long-term business objectives.
• Represent OMG in Nokia-wide AI, data, automation, and architecture forums, driving alignment and reuse across organizations.
• Establish AI/ML governance, architecture standards, and engineering practices that can be adopted across multiple Nokia engineering organizations.
• Lead evaluation and selection of AI platforms, cloud technologies, external partners, implementation approaches, and strategic technology investments supporting OMG objectives
• Develop OMG AI/ML competency frameworks, workforce development plans, training strategies, and technical communities.
• Serve as a senior technical advisor to OMG leadership on AI/ML opportunities, risks, priorities, and investments.
• Provide strategic leadership for cloud platform initiatives, including project team staffing, contributor selection, priorities, deliverables, risks, and decisions.

• 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.