Lead Data & AI Engineer - R&D IT

Job Description

Summary:

As a Data & AI Engineer, you will directly contribute to accelerating and optimizing NXP’s New Product Introductions by designing, implementing, and operationalizing advanced AI driven solutions. Your work will empower R&D teams with scalable AI tools, assistants and automated workflows.
Working closely with data engineers, data scientists and domain experts, you will help define the future of AI capabilities within R&D at NXP. You will build robust, production ready AI applications, including Generative AI solutions for our R&D community.


Your key responsibilities
• Stakeholder Collaboration: Work with project managers, resource managers, IT teams, and other stakeholders to gather requirements, define project scope, and ensure alignment with business objectives.
• Generative AI Solutions: Design, develop, and deploy AI products to support R&D engineers.
• Responsible AI and Reliable Data: Collaborate with data engineers and DevOps engineers to ensure high‑quality, secure, reliable, and well‑governed data availability for AI initiatives.
• Automation & DevOps: Build AI solutions with a DevOps mindset—ensure reproducibility, automation, and quality by leveraging CI/CD pipelines, version control, and modern development practices.
• Agile Delivery & Collaboration: Work as part of a Scrum team, operating within an Agile environment and participating in sprint planning, reviews, and cross‑functional collaboration to ensure rapid, iterative delivery of AI solutions.

Job Qualification:
Education & Experience:
• Education: A master’s degree in Artificial Intelligence, Data Science, Software Engineering, Computer Science, or a related field. PhD in Artificial Intelligence, Machine Learning or related discipline is a plus.
• Experience: 7+ years of experience in applied AI or AI solution development (professional or academic), preferably within a complex IT or R&D environment.
Technical Skills
• Coding: Strong proficiency in Python.
• Generative AI Development:
o Experience with foundational and open source model families (Claude, GPT, Llama, Mistral, Gemma, etc.).
o Experience with RAG frameworks and components (LangChain, LlamaIndex, semantic search, embeddings, vector stores, etc.).
o Familiarity with multimodal and agentic architectures.
• Application Deployment:
o Experience with Backend/API development (FastAPI, Flask, or equivalent).
o Understanding of containerization and orchestration (Docker).
• Automation: A strong interest in automation, cloud technologies, Infrastructure as Code (preferably using CDK), DevOps practices, and CI/CD pipelines (preferably using Gitlab).
• Cloud: Experience working with cloud-native AI deployment on AWS (or other cloud platform) is a plus.
Professional Attributes
• Strategic Problem-Solving: Comfortable owning technical challenges and designing long-term, scalable solutions.
• Customer & Stakeholder Focus: Strong communicator who can translate technical concepts into business value and collaborate effectively across data science, architecture, and wider R&D.
• Team Mindset: A natural collaborator who contributes to an open, supportive working culture
• Agile & SCRUM: Experienced working in Agile environments, actively participating in sprints, stand-ups, and iterative delivery cycles to ensure continuous improvement and timely value delivery.