About Alluxio:
Alluxio powers the data layer for modern AI and analytics. Proven in production at eight of the top ten internet companies and seven of the ten highest-valued enterprises globally, Alluxio’s open-source data-orchestration platform unifies data across storage systems, regions, and clouds — enabling memory-speed access for large-scale AI and analytics workloads.
Spun out of UC Berkeley’s AMPLab and backed by Andreessen Horowitz, Hillhouse Capital, and Seven Seas Partners, Alluxio sits at the intersection of data, distributed systems, and AI infrastructure.
Our technology is deployed at scale by Meta, Uber, TikTok, Alibaba, Microsoft, and Salesforce, orchestrating data for billions of operations per day.
The Role
We’re hiring a Technical Product Manager to define and execute Alluxio’s AI systems strategy — spanning inference, training, and emerging agentic workloads.
This role bridges the worlds of AI infrastructure and distributed data systems, guiding how Alluxio evolves to serve next-generation model architectures and large-scale data flows.
You’ll partner with engineering, research, and enterprise AI teams to build features that improve latency, throughput, and GPU efficiency for model inference and training — and design the data layer powering the shift toward autonomous, agentic AI systems.
What You'll Own
- AI Product Strategy — define the long-term vision and roadmap for Alluxio’s AI data platform, covering inference, training, and agentic workloads.
- Systems Optimization for AI — collaborate with engineering to design features that deliver high-throughput, low-latency data access (e.g., GPU-aware caching, streaming reads, tiered prefetching).
- AI Ecosystem Integration — ensure seamless integration with frameworks like PyTorch, TensorFlow, Ray, and Triton; evolve Alluxio’s APIs for AI-native workloads.
- Customer & Partner Collaboration — engage directly with enterprise AI teams to understand workload patterns, validate impact, and prioritize roadmap direction.
- Market Awareness & Foresight — stay ahead of trends in multi-model serving, retrieval-augmented generation (RAG), and agentic orchestration; translate them into actionable product plans.
What We’re Looking For
- 5–9 years of experience in product management or technical leadership within AI infrastructure, ML platforms, or distributed systems.
- Strong understanding of AI/ML workflows — from model training and deployment to inference and data-access pipelines.
- Proven track record of delivering infrastructure features that improve latency, GPU utilization, or total cost of ownership.
- Technical fluency with distributed systems, caching, and cloud orchestration (Kubernetes, AWS/GCP/Azure).
- Familiarity with AI frameworks such as PyTorch, TensorFlow, Triton, Ray, or LangChain.
- Exceptional communication and strategic thinking — ability to translate complex systems work into clear, prioritized roadmaps.
Why Join Alluxio?
- Shape how the world’s most advanced AI systems access and process data.
- Work at the intersection of distributed systems, AI acceleration, and open source.
- Collaborate with world-class engineers, researchers, and customers driving the AI frontier.
- Competitive compensation and equity package with comprehensive benefits.
- A culture built on curiosity, empathy, and deep technical rigor.
Alluxio is an equal opportunity employer and does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors.
The salary range for this full-time position in the United States is $190,000 - $240,000 depending on experience and level, subject to standard withholding and applicable taxes. All candidates will also receive equity (stock options) and access to a comprehensive benefits package. The base salary range reflects the minimum and maximum target for candidates across all US locations. The specific compensation awarded will be based on factors such as work location, skills, experience, and relevant education or training. Our Recruiting Team or Hiring Manager will provide more details about the specific salary range during the recruitment process.
