R&D Transformation Lead

This role owns the two biggest levers for how the R&D organisation evolves: who it works with externally and how it builds capability internally — including the adoption of AI-driven ways of working. The Vendor, Org & AI Transformation Specialist ensures subcontractor quality does not become a delivery liability, that the organisation is structured and skilled for what is ahead, and that AI tools are embedded into engineering workflows in a disciplined, measurable way. Manage weekly and monthly R&D operating cadence, including program reviews, S OW standards, Deliverable Acceptance Checklists (DAC — SW and HW categories), and Payment Gate Schedules . Conduct technical audits and deliverable reviews for subcontractor engagements across SW, HW, and systems categories. Track vendor performance KPIs; manage underperformance with structured Corrective Action Plans (CAPs) Oversee the R&D governance calendar, ensuring timely and data-driven discussions occur. Identify, pilot, and scale AI tools (Copilot, generative AI assistants, automated test generation, AI-assisted code review) within R&D teams Triage escalations by identifying blockers early and coordinating resolution efforts with engineering teams. Facilitate day-to-day Agile execution, including Sprint Planning, SCRUM, and retrospectives. Define and monitor delivery KPIs, identifying bottlenecks and implementing process improvements. Drive quality metrics monitoring and ensure adherence to engineering quality gates throughout the product lifecycle. Conduct root cause analysis on quality issues and foster communities of practice around engineering excellence. Must-Have: Engineering or Masters in engineering with 10–14 years in R&D, engineering program management, or technical operations Direct experience in managing hardware/embedded subcontractor engagements DAC, BOM/AVL, DER, ECR/ECO in a hardware-software context Demonstrated experience driving AI or Gen AI tool adoption in an engineering organization — structured rollout with measurable outcomes, not just awareness. Comfortable working across engineering, HR, IT, and procurement stakeholders Proficient in org and people processes — headcount planning, competency frameworks, onboarding design Nice-To-Have: Familiarity with Nokia or comparable OEM engineering processes Experience with Microsoft Copilot, GitHub Copilot, or equivalent GenAI tools in an engineering context Background in organizational design or HR business partnering. Exposure to Nokia BBD or Fixed Networks program structures