Associate Partner - Tech Industry Data & AI

Introduction A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences. Your role and responsibilities Lead Data & AI engagements for semiconductor clients, driving both go-to-market (GTM) growth and large-scale delivery execution across advanced analytics, AI/GenAI/Agentic AI, MES, and modern data platforms. Act as a trusted advisor to CIO, CTO, and business executives, shaping enterprise data strategies, AI adoption roadmaps, and digital transformation programs aligned to semiconductor industry priorities (R&D, manufacturing, supply chain, finance, HR and commercial analytics). Own end-to-end delivery of complex Data & AI programs, including solution architecture, technical leadership, and cross‑functional team management across data engineering, data science, and platform implementation. Drive technical sales and solution development, translating client business challenges into scalable data platform and AI solutions, supporting proposals, value cases, and executive presentations. Architect modern data ecosystems including cloud-native data platforms, streaming data pipelines, advanced analytics environments, and governed data products that enable enterprise self‑service and AI‑driven decision making. Lead the design and implementation of enterprise data & AI architectures, including large‑scale data engineering pipelines, ML lifecycle management, real‑time/streaming analytics, and AI/GenAI/Agentic AI. Lead the end‑to‑end delivery and strategic oversight of SiView MES implementations, ensuring program quality, client satisfaction, and on‑time execution while managing cross‑functional teams and serving as the primary escalation point for program risk and governance. Establish robust data & AI governance, security, and compliance frameworks, ensuring trusted data foundations enabling AI capabilities across regulated and global semiconductor operations. Mentor and grow high‑performing technical teams, fostering innovation across Data Engineering, MLOps, Analytics, AI/GenAI/Agentic disciplines. This Job can be performed from anywhere in the US. Required technical and professional expertise 15+ years of experience in Data, Analytics, AI/GenAI/Agentic AI, and enterprise technology leadership within consulting or large‑scale technology organizations. Strong semiconductor industry experience, with understanding of data and AI use cases across wafer fabrication, manufacturing operations, supply chain, product engineering, and commercial analytics. Deep expertise in modern Data & AI platforms, including advanced analytics, complex data modeling, data product architectures, AI/GenAI/Agentic AI and enterprise self‑service analytics enablement. Hands‑on knowledge of large‑scale data engineering, including distributed data processing, real‑time streaming architectures, and ML lifecycle platforms. Experience designing cloud-native data platforms, including cloud data warehousing, query optimization, secure data sharing, and hybrid/multi‑cloud architectures. Strong familiarity with major cloud ecosystems (AWS, Microsoft Azure, Google Cloud), with relevant certifications preferred. Proven ability to combine technical depth with client‑facing leadership, driving both solution sales and delivery outcomes for strategic enterprise clients. Preferred technical and professional experience Demonstrated success delivering data and analytics solutions within the manufacturing industry. Cloud certifications and expertise across AWS, Azure, and/or Google Cloud Platform, with strong knowledge of machine learning and hybrid/multi‑cloud architectures. IBM is committed to creating a diverse environment and is proud to be an equal‑opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status. #J-18808-Ljbffr IBM Computing