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AI Forward-Deployed Manager

TSMC•Published 1 days ago•First seen 1 days ago
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Established in 1987 and headquartered in Taiwan, TSMC pioneered the pure-play foundry business model with an exclusive focus on manufacturing its customers’ products. As of 2024, TSMC serves more than 500 customers and manufactures over 11,000 products for high-performance computing, smartphones, the Internet of Things (IoT), automotive, and digital consumer electronics. It is the world’s largest provider of logic ICs, with an annual capacity of over 17 million 12-inch equivalent wafers in 2025. TSMC operates fabs in Taiwan as well as manufacturing subsidiaries in Washington State, Japan and China, and the Company began construction on a specialty technology fab in Dresden, Germany, in 2024. In Arizona, TSMC is building three fabs, with the first starting 4nm production in 2025, the second by 2028, and the third by the end of the decade.

Role Overview: As an AI Forward-Deployed Technical Manager, you will lead the delivery of cutting-edge AI and machine learning solutions for Advanced Semiconductor R&D Modules. You will own the relationship with internal engineering stakeholders from a technical delivery standpoint, translating complex semiconductor domain challenges into AI/ML roadmaps. You will manage a team of Forward-Deployed Engineers and Data Scientists to design, build, and deploy production-grade AI systems (including LLMs, RAG pipelines, and predictive models), ensuring measurable business impact, operational efficiency, and adherence to AI safety and data governance standards.

Job Responsibilities

1. AI Delivery & Project Management: Lead the end-to-end lifecycle of enterprise AI deployments—from initial scoping and proof-of-concept (PoC) to full production deployment and scaling.

2. Team Leadership: Manage, mentor, and unblock a multidisciplinary team of AI/ML engineers, forward-deployed engineers, and data scientists embedded within engineering teams.

3. AI Solution Scoping: Translate complex domain problems into concrete data science and engineering requirements. Define KPIs for AI model accuracy and engineering impact.

4. Cross-Functional Collaboration: Bridge the gap between central IT/AI platforms and domain-specific R&D teams. Advocate for user needs to influence the core AI product roadmap.

5. AI Governance & Security: Ensure deployed AI models adhere to enterprise IP security, data privacy, and strict compliance standards.

Job Qualifications

Technical Literacy (AI & Engineering): 

1. Generative AI & LLMs: Strong understanding of Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), vector databases, and fine-tuning techniques.

2. Classical ML & Data Science: Solid grasp of supervised/unsupervised learning, deep learning, NLP, computer vision, and data pipelines.

3. AI Infrastructure & MLOps: Familiarity with the AI lifecycle stack (e.g., LangChain, LlamaIndex, MLflow, Kubeflow) and experience deploying models in enterprise-grade private/hybrid cloud or on-premise environments.

4. Data Architecture: Solid understanding of data engineering principles, data warehousing, and secure data governance.

Leadership & Soft Skills:

1. Technical Product Management: Ability to define MVP scope, manage backlogs, and run agile sprints for AI deployments.

2. Executive Communication: Exceptional ability to translate complex AI concepts to non-technical engineering and executive stakeholders.

3. Stakeholder Management: Proven track record of managing diverse stakeholders, scope alignment, and driving consensus under ambiguity.

Education & Experience:

1. Education: Master’s or PhD in Computer Science, Data Science, AI/ML, or a related quantitative engineering field.

2. Experience:

(1) 6+ years of total experience in technology consulting, AI product management, or technical program management.

(2) 3+ years of experience leading the delivery of AI/ML or Big Data solutions.

(3) Proven track record in managing or mentoring engineering/data science teams.

TSMC Core Values

At TSMC, we invite talented individuals who share our vision and values to contribute to our continued success. Our core values are the foundation of our culture, guiding every decision and action. We seek applicants who deeply resonate with these principles and embody them in their work:
  • Integrity: Tell the truth. We do not brag. We do not make commitments lightly. Once we make a commitment, we devote ourselves completely to meeting that commitment.
  • Commitment: Employees are dedicated to the company, view the company’s success as their own and work diligently to make their best contributions. As commitment is mutual, the Company strives to serve the best interests of its employees. 
  • Innovation: Innovation is the wellspring of the Company's growth. It means more than new ideas; it means putting ideas into practice. 
  • Customer Trust: We strive to build deep and enduring relationships with our customers, who trust and rely on us to be part of their success over the long term.
(For more details on TSMC’s Core Values, please visit：https://www.tsmc.com/english/aboutTSMC/values)Fostering a global inclusive workplace reflects TSMC’s core values and business philosophy and is essential for our future success. Our commitment to global inclusive workplace allows us to create an environment where every employee, regardless of gender, age, disability, religion, race, ethnicity, nationality, political affiliation, or sexual orientation, can bring their unique perspective and experiences to work, enabling us to drive profitability, increase productivity, and unleash innovation. We strive to create a workplace that is equitable and accessible to all employees. We are committed to fostering an inclusive culture where every employee feels valued and empowered to contribute to our mission and provide excellent service to our global customers.

For more information, please refer to 2025 TSMC Global Inclusive Workplace Progress: