Principal Product Manager (AI)

TL;DR

Principal Product Manager (AI): Own the AI product strategy for Azure hirify.global Files (ANF), translating an evolving AI landscape into differentiated platform capabilities and joint roadmap bets with Microsoft. Focus on multi-year AI vision and requirements for training/inference, RAG, agentic workflows, and enterprise data governance—balancing hyperscaler co-development constraints with enterprise storage differentiation.

Location: United States (San Jose, California; Morrisville, North Carolina)

Salary: $228,000 - $345,000

Company

hirify.global delivers intelligent data infrastructure, including unified storage and integrated data services across major cloud platforms.

What you will do

• Own end-to-end AI strategy and multi-year roadmap for ANF, including problem selection, success metrics, phased delivery, and competitive positioning.
• Define AI-centric product requirements for training/inference data planes, high-throughput low-latency checkpointing, and bursty I/O.
• Drive product definition for RAG and enterprise search (datasets, versioning, clones, refresh patterns) and for agentic workflows and orchestration (durable shared state, tool/data access patterns).
• Shape capabilities for large multimodal and enterprise datasets with governance, access control, and lifecycle management.
• Partner with Microsoft across Azure AI/Foundry, Azure Machine Learning, AKS/container platforms, GPU infrastructure, and Azure storage/networking dependencies.
• Lead cross-functional execution with engineering, product marketing, sales, customer success, and professional services; validate with strategic customers and design partners.

Requirements

• 10+ years of product management experience in cloud infrastructure, enterprise storage, AI/ML infrastructure, or data platforms.
• Strong enterprise storage knowledge (NFS/SMB semantics, snapshots/clones, replication, backup integration, capacity/performance tiers, and large-scale filesystem behavior under parallel workloads).
• Hands-on familiarity with modern AI stacks: LLMs, RAG architectures, embeddings/vector retrieval patterns, training vs. inference I/O profiles, orchestration, and enterprise AI data pipelines.
• Proven ability to influence engineering and partner roadmaps without direct authority; hyperscaler first-party or deeply partnered service experience is a plus.
• Excellent written and verbal communication skills for customers, executives, and engineers.

Nice to have

• Direct experience with Microsoft Azure AI services, GPU estates on Azure, and/or Azure Kubernetes Service + ML platform integrations.
• Familiarity with Databricks, Iceberg/Delta-class open table patterns, Kubernetes storage patterns, NVIDIA AI software stacks, and enterprise MLOps release cadences.
• Background in regulated industries and enterprise security/governance requirements for AI data.

Culture & Benefits

• Hybrid working environment with some in-office and/or in-person expectations shared during recruitment.
• Comprehensive benefits package including health insurance, life insurance, retirement/pension plans, paid time off, and performance-based incentives (regional variations apply).
• Emphasis on ownership, initiative, and impact; flexibility to balance professional ambition and personal life.
• Opportunities to collaborate with cross-functional teams and validate roadmap bets with customers and partners.

Hiring process

• Application review is conducted through the company website.
• Some stages may use AI tools to support candidate evaluation, with final decisions made by humans.