Senior Principal Data and AI Engineer- R&D IT

What You'll Do

• 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. • 10+ 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.
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