IT Architect Data and AI

Job Description:

Are you a seasoned Data & AI expert who thrives in solving complex challenges and turning cutting‑edge innovations into real, enterprise‑ready solutions? Within NXP’s global IT organization, you will shape the future of NXP’s R&D data and AI ecosystem—developing architectures, platforms and next‑generation capabilities that empower thousands of engineers, analysts, and business users worldwide.
NXP is rapidly scaling advanced analytics, AI/ML, and data-driven decision making across R&D. As our Data & AI Architect, you will define and realize the architectural vision that underpins these capabilities. You will explore opportunities beyond the paved road, drive innovation, and guide global teams in delivering secure, scalable, and future‑proof data and AI solutions.
This role is ideal for a highly experienced architect ready for their next step—combining deep hands‑on expertise with strategic thinking, leadership, and enterprise collaboration.

Role and responsibilities
Strategic Architecture Leadership
• Define the end-to-end Data & AI architecture vision and roadmap, aligned with NXP’s enterprise IT and business strategy.
• Drive the development of AI‑ready data platforms, data governance frameworks, and cloud‑native architectures supporting analytics and AI/ML use cases.
• Identify emerging technologies and market trends (e.g., LLMs, MLOps, real‑time pipelines, knowledge graphs, vector databases) and assess their applicability within NXP.
• Lead the evaluation and adoption strategy for generative AI capabilities including large language models, multimodal models, and retrieval augmented generation to accelerate business workflows and product innovation.
• Define enterprise standards for GenAI model selection, fine‑tuning, hosting (cloud and on‑prem), and lifecycle management aligned with NXP risk and compliance posture.
• Assess cost, latency, and data residency tradeoffs for managed GenAI services versus self‑hosted open models.

Design & Implementation
• Design scalable, secure, and maintainable enterprise data architectures incorporating AI/ML capabilities, cloud solutions (Azure/AWS/GCP), and modern data engineering practices.
• Lead the conceptualization and design of AI system architectures, working closely with data scientists, ML engineers, and solution teams to ensure production‑grade performance.
• Design and enable real-time and batch data processing pipelines, feature stores, and ML deployment workflows.
• Architect GenAI solutions such as RAG pipelines, prompt engineering frameworks, embedding generation and vector search, and multimodal inference flows to support conversational agents, code generation, document understanding, and knowledge augmentation.
Governance, Quality & Security
• Establish and promote enterprise data governance, metadata management, lineage tracking, automated compliance, and responsible AI standards.
• Ensure all data and AI platforms adhere to architectural, privacy, security, and regulatory requirements.
Innovation & Exploration
• Lead Proofs of Concept (PoCs) to evaluate new tools, platforms, and architectural patterns for data and AI.
• Promote sustainable, ethical, and explainable AI practices across the organization.
Collaboration & Stakeholder Engagement
• Act as a trusted advisor to global business and technology stakeholders, understanding needs and translating them into actionable architectures and implementation roadmaps.
• Collaborate with R&D, Operations, Digital Transformation, Cybersecurity, and Cloud teams to ensure cohesive development and deployment of enterprise AI solutions.


Delivery & Technical Leadership
• Guide technical decision‑making for data and AI platforms, fostering modern engineering practices (MLOps, DataOps, DevOps).
• Provide architectural oversight for multiple parallel implementation workstreams, ensuring quality, scalability, and alignment with enterprise standards.
• Serve as a mentor and thought leader to engineers, architects, and data professionals across NXP.

Education and experience

• Master’s or Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, or related technical field.
• 12+ years of professional experience in data architecture, AI/ML platforms, advanced analytics, or related technical roles.
• Demonstrated experience designing enterprise-scale data architectures, cloud-native solutions, and AI/ML systems.
• Hands-on background working with big data technologies (Spark, Hadoop), real‑time streaming (Kafka, Flink), AI/ML frameworks, and cloud platforms.
• Experience implementing MLOps and AI governance capabilities in enterprise environments.
• Experience in high-tech, semiconductor, automotive, or large-scale R&D environments is a strong plus.

Skills
Core Architectural Skills
• Expertise in enterprise data architecture, including modeling, integration, governance, and security.
• Strong understanding of AI/ML platform design, pipelines, lifecycle management, and infrastructure.
• Ability to evaluate and integrate emerging AI technologies responsibly.

Analytical & Strategic Abilities
• Strategic thinker with the ability to define long‑term vision for data and AI capabilities.
• Strong analytical and problem‑solving abilities, comfortable navigating complex architectural decisions.
Technical & Delivery Skills
• Deep knowledge of cloud-native architectures, distributed computing, and scalable pipelines.
• Ability to assess architectural options, review engineering designs, and guide teams through implementation.
• Strong experience with modern data management, MLOps, and DevOps tooling.
Communication & Collaboration
• Excellent communication skills for explaining complex technical concepts to both technical and business audiences.
• Proven ability to influence stakeholders and collaborate across global, matrixed teams.
Personal Attributes
• Curious, enthusiastic, and continuously scanning for new opportunities to innovate.
• Highly organized, proactive, and adaptable within fast‑paced environments.
• Team-oriented, collaborative mindset with a passion for driving transformation.
• Fluent in English, both written and verbal.