Technical Project Manager Data Assets and AI

About AMD

At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.

The Role

We are seeking a highly organized and technically savy Project Manager to manage projects across our Data Assets team (data engineers and semantic model developers) and Data Science team (ML and LLM initiatives). This role bridges technical depth with strong program management discipline—ensuring projects are delivered on time, within scope, and aligned to business priorities. You will manage complex data and AI initiatives, coordinate cross-functional teams, and maintain clear communication with stakeholders to drive measurable impact.

The Person

The ideal candidate is passionate about data and AI technologies and thrives in a very fast-paced environment. You have a good understanding of data pipelines, semantic modeling, machine learning, and generative AI concepts, combined with exceptional project management skills. You are proactive, detail-oriented, and skilled at pushing teams toward timely delivery while fostering collaboration and managing stakeholder expectations effectively.

Key Responsibilities

Project Delivery & Governance

• Own end-to-end planning and execution for data engineering, semantic modeling, and ML/LLM projects.
• Define project scope, timelines, and deliverables; manage risks, dependencies, and change requests.
• Run Agile ceremonies, maintain backlogs, and track progress using metrics like velocity and burn-down charts.

Technical Coordination

• Collaborate with data engineers on managing projects related to data pipelines and semantic models.
• Partner with data scientists to manage ML/LLM project lifecycles, including experimentation, deployment, and monitoring.
• Ensure adherence to best practices in DataOps, MLOps, Release Management and Documentations.

Stakeholder Management

• Communicate project status, risks, and decisions clearly to technical and business stakeholders.
• Align priorities across teams and manage expectations to avoid delivery surprises.

Operational Excellence

• Implement dashboards and reports for project health and delivery KPIs.
• Drive continuous improvement in processes, tools, and team collaboration.

Qualifications

• Experience managing technical projects, preferably in data and AI domains.
• Proven track record of delivering complex projects involving data pipelines, semantic models, and ML/AI solutions.
• Technical Knowledge: Familiarity with data engineering tools (e.g., Airflow, Snowflake) and semantic modeling (Power BI Tabular, dbt Semantic Layer).
• Understanding of machine learning workflows, MLOps practices, and LLM concepts.
• Project Management Skills: Strong command of Agile methodologies and tools (Jira, Azure DevOps).
• Excellent communication, stakeholder management, and conflict resolution skills.

Education

Bachelor’s degree in related field.

Key skills/competency

• Project Management
• Data Engineering
• Semantic Modeling
• Machine Learning
• Generative AI
• Agile Methodologies
• Data Science
• MLOps
• DataOps
• Stakeholder Management