Senior / Principal AI Engineer for Business Intelligence (7063)

Overview Of Role As a Sr./Principal AI Engineer within TSMC's Artificial Intelligence for Business Intelligence Innovation (AI4BII) Center, you will join an exciting global team dedicated to generating crucial business intelligence insights that shape TSMC's strategic decisions and global operations. This role uniquely blends applied research with end-to-end product development, placing you at the forefront of our mission to leverage advanced AI for a competitive edge. Operating with the agility of an internal startup, you will have the autonomy to build foundational systems from the ground up. You will tackle complex challenges spanning from advanced analytics and multimodal AI agents to time‑series forecasting and reinforcement learning for manufacturing optimization. This role is for a builder and researcher who has built a product from zero to one and thrives on rapid iteration, technical leadership, and seeing their work create tangible business impact. Our hybrid work schedule currently requires four days in the office, ensuring a dynamic and collaborative work environment. Responsibilities Lead System Architecture: Own the end‑to‑end design and development of new AI‑native products and platforms, from initial concept and data pipelines to scalable, production‑grade services. Build with Frontier AI: Drive the hands‑on implementation of advanced AI systems leveraging frontier LLM models, including the design of robust Retrieval‑Augmented Generation (RAG) pipelines and multi‑agent workflows. Prototype and Validate: Lead rapid validation sprints to build proof‑of‑concepts, create evaluation harnesses to measure accuracy, latency, and cost, and partner with product teams to harden prototypes for production release. Engineer for Scale: Architect and implement the underlying MLOps infrastructure, including model serving, automated testing, and observability, to ensure our AI services meet enterprise‑grade SLAs. Drive Innovation: Research and validate novel AI use cases (e.g., threat‑hunting copilots, developer productivity tools, automated workflow optimization) and build the foundational frameworks to accelerate their deployment. Collaborate and Mentor: Partner closely with Product, Design, and business stakeholders to ensure solutions are technically sound and commercially impactful. Mentor junior engineers and foster a culture of experimentation, responsible AI, and first‑principles thinking. Communicate Vision: Craft and deliver compelling executive‑level narratives, demos, and visualizations that clearly communicate technical strategy, roadmaps, trade‑offs, and business impact. Minimum Qualifications Experience: At least 10+ years of professional experience in software engineering, machine learning engineering, or related fields in high‑performance environments. 7+ years of hands‑on experience in professional software and/or machine learning engineering. 3+ years of experience in a technical leadership role, specifically focusing on architecting and building scalable systems powered by Generative AI or Large Language Models (LLMs). Technical Expertise: Generative AI & LLMs: Deep, hands‑on expertise in the modern AI stack, including RAG, fine‑tuning, agentic frameworks, prompt engineering, vector databases, and model evaluation techniques. Backend & Systems Design: Strong fundamentals in backend engineering and distributed systems. Mastery of Python is required. MLOps & Cloud: Hands‑on experience with at least one major cloud AI platform (GCP Vertex AI, AWS SageMaker, Azure ML) and containerized workflows (Docker, Kubernetes). Leadership & Communication: Demonstrated ability to translate ambiguous business problems into clear technical blueprints and phased execution plans. Exceptional communication and presentation skills, with experience conveying complex technical concepts to both engineering teams and senior management audiences. Education: B.S. or higher in Computer Science, Engineering, Mathematics, or a related technical field. An M.S. or Ph.D. is a plus. Preferred Qualifications Experience deploying AI into developer tooling (IDE plug‑ins, CI/CD pipelines). Active contributions to open‑source AI/ML projects or publications in top‑tier academic conferences. A broad knowledge of mathematical modeling beyond ML, such as combinatorial optimization or operations research. Diversity statement TSMC Technology, Inc. is committed to employing a diverse workforce and provides Equal Employment Opportunity for all individuals regardless of race, color, religion, gender, age, national origin, marital status, sexual orientation, gender identity, status as a protected veteran, genetic information, or any other characteristic protected by applicable law. TSMC is an equal opportunity employer prizing diversity and inclusion. We are committed to treating all employees and applicants for employment with respect and dignity. If you require reasonable accommodation due to a disability during the application or the recruiting process, please feel free to notify us at View email address on click.appcast.io. TSMC confirms to all applicants its commitment to meet TSMC’s obligations under applicable employment law. Reasonable accommodations will be determined on a case‑by‑case basis. Pay Transparency / Benefits Statement At TSMC, your base pay is only part of your overall total compensation package. At the time of this posting, this role typically pays a base salary between $123,240 and $200,000 per year. The range displayed reflects the minimum and maximum target for new hires. Actual pay may be more or less than the posted range. Factors that influence pay include the individual's skills, qualifications, education, experience and the position level and location. TSMC’s total compensation package consists of market competitive pay, allowances, bonuses, and comprehensive benefits. We also offer extensive development opportunities and programs. #J-18808-Ljbffr TSMC