Sr. Product Manager, AI Infrastructure

Tencent•Palo Alto, CA

1d•Onsite

About The Position

Tencent is a world-leading internet and technology company that develops innovative products and services to improve the quality of life for people around the world. This Sr. Product Manager, AI Infrastructure role entails owning the full lifecycle management of AI infrastructure platforms, including large-scale clusters, distributed systems, lifecycle management toolchains, and model service gateways. The position requires developing 3-5 year strategies and annual roadmaps that align business goals with technical excellence, balancing performance, cost, usability, and reliability. Responsibilities include deeply analyzing the core pain points of internal ML teams, data scientists, and enterprise clients, translating technical requirements into clear PRDs and technical specifications, and leading products from 0 1 incubation to 1 N scaled iterations. The role also involves partnering with hardware architecture, heterogeneous systems, software engineering, algorithms, and SRE teams to drive product R&D and operations, resolving critical technical trade-offs, and establishing a core performance indicator system. Furthermore, the manager will track cutting-edge advancements in AI Infrastructure and industry trends to build differentiated competitive advantages, and collaborate with GTM and sales teams to articulate product value propositions and drive commercial success.

Requirements

Master’s degree or higher in Computer Science, Electronic Engineering, Mathematics, or a related STEM field.
Extensive experience in product management, with a focused track record in AI Infrastructure, cloud computing, distributed systems, or developer platforms.
Familiar with the end-to-end model development lifecycle; understanding of compilation optimization, high-performance inference engines, and distributed training optimization techniques.
Exceptional cross-team communication and "influence without authority"; ability to drive project execution in ambiguous, fast-paced environments.

Nice To Haves

Product design experience in compilation optimization, high-performance inference engines, and distributed training optimization techniques.
Experience in major cloud service providers or leading AI companies.
Active contributions to relevant open-source technical communities.

Responsibilities

Own the full lifecycle management of AI infrastructure platforms (including large-scale clusters, distributed systems, lifecycle management toolchains, and model service gateways); develop 3-5 year strategies and annual roadmaps that align business goals with technical excellence, balancing performance, cost, usability, and reliability.
Deeply analyze the core pain points of internal ML teams, data scientists, and enterprise clients; translate technical requirements into clear PRDs and technical specifications, leading products from 0 1 incubation to 1 N scaled iterations.
Partner with hardware architecture, heterogeneous systems, software engineering, algorithms, and SRE teams to drive product R&D and operations; resolve critical technical trade-offs during the development process.
Establish a core performance indicator system (e.g., throughput, latency, compute resource utilization, cost efficiency, and developer satisfaction); leverage data to drive continuous product optimization.
Track cutting-edge advancements in AI Infrastructure (such as compiler optimization, cloud-native architectures, and large-scale model training/inference techniques) and industry trends to build differentiated competitive advantages.
Collaborate with GTM and sales teams to articulate product value propositions, technical whitepapers, and POC solutions to drive commercial success and client acquisition.