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# Senior / Principal AI Engineer for Business Intelligence

- **Company:** TSMC - Taiwan Semiconductor Manufacturing Company Limited
- **Location:** California, MO, United States
- **Experience:** Expert
- **Salary:** $123,240.0 - $180,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Automation of Tests, Cloud Computing, Programming Tools, Distributed Systems, Python (Programming Language), Machine Learning, Open Source Technology, Productivity Software, Azure Machine Learning, Software Engineering, Systems Architecture, User-Centered Design, Reinforcement Learning, Flexi (Photoshop Plugin), Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Google Vertex AI, Model Validation, Generative AI, Cyber Threat Analysis, Backend, Agentic-AI, AI Platforms, Kubernetes, Information Technology, Machine Learning Operations, Data Pipelines, Docker
- **Published:** October 20, 2026
- **Apply:** https://www.juju.com/job/23_13DE78D03470E0669F654C5F31297EC9

## About the Role

Experience: At least 7+ years of professional experience in software engineering, machine learning engineering, or related fields in high-performance environments. 5+ years of hands-on experience in professional software and/or machine learning engineering. 2+ years of experience in a technical leadership role, 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 Retrieval-Augmented Generation, 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. MLOps & Cloud: Experience with at least one major cloud AI platform (GCP Vertex AI, AWS SageMaker, Azure ML) and containerized workflows (Docker, Kubernetes).

Leadership & Communication: 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 engineering teams and senior management.

Education: B.S. or higher in Computer Science, Engineering, Mathematics, or related 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. Broad knowledge of mathematical modeling beyond ML, such as combinatorial optimization or operations research.

## Description

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 blends applied research with end-to-end product development, placing you at the forefront of leveraging advanced AI for a competitive edge. You will operate with the agility of an internal startup, building foundational systems from the ground up and tackling challenges across advanced analytics, multimodal AI agents, time-series forecasting, and reinforcement learning for manufacturing optimization. This is a role for a builder and a researcher who thrives on zero-to-one product journeys, rapid iteration, technical leadership, and delivering tangible business impact. The hybrid work schedule currently requires 4 days in the office. 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 hands-on implementation of advanced AI systems using 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 underlying MLOps infrastructure, including model serving, automated testing, and observability, to ensure 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 foundational frameworks to
accelerate deployment. Collaborate and Mentor: Partner with Product, Design, and business stakeholders to ensure solutions are technically sound and commercially impactful. Mentor junior engineers and foster experimentation, responsible AI, and first-principles thinking. Communicate Vision: Craft and deliver executive-level narratives, demos, and visualizations that clearly communicate technical strategy, roadmaps, trade-offs, and business impact.