Senior Principal Product Manager

Siemens•California, PA

2d•$197,268 - $267,036•Hybrid

About The Position

Siemens is hiring a Senior Principal Product Manager to define strategy and architecture for a key product domain involving generative AI in the physical world. The role works across engineering, machine learning, design, research, and hardware to invent and launch novel interfaces and platforms. The product leader will operate in an ambiguous, technically complex environment, influence decisions across research and product, and help shape how people interact with AI agents in dynamic environments. The position is described as remote in the role overview, while the listing specifies a hybrid (remote/office) work mode and may be based at any Siemens location in California. The role offers an annual pay range of $197,268–$267,036, with a target incentive of 20% of base salary. Siemens states that the actual wage may vary based on budget, candidate experience, knowledge, skills, qualifications, and premium geographic location. Siemens offers a variety of health and wellness benefits; details are available through the benefits link in the posting. The position is permanent and full-time.

Requirements

Bachelor’s degree.
At least 7 years of product management experience, including at least 3 years in AI/ML, developer platforms, or deeply technical domains.
Demonstrated success launching platform-level or technically complex products.
Ability to define architecture-level tradeoffs and work across research and production teams.
Strong written and verbal communication skills, with experience influencing at the leadership level.
Hands-on experience with metrics, experimentation, and iterative development.

Nice To Haves

Background in machine learning, robotics, or multimodal systems.
Experience leading product in early-stage or zero-to-one product environments.
Familiarity with LLMs, inference systems, feedback pipelines, or agentic frameworks.
Prior experience mentoring other product managers or leading cross-functional pods.

Responsibilities

Define product vision, strategy, and roadmap for an AI-native platform, interface, or product line.
Translate open-ended problems into structured product definitions and scalable architectures.
Partner with engineering, ML, and research teams to drive cross-functional product delivery.
Own the full product lifecycle, from zero-to-one MVPs through post-launch iteration.
Identify critical data, feedback, and learning loops that enable model and user-experience improvement.
Represent product strategy to leadership and cross-functional stakeholders.