Engineering Manager (Azure, AI)

TL;DR

Engineering Manager (Azure, AI): Leading and building a Cloud Inference team to scale and optimize Claude for Azure developers and enterprise companies with an accent on API design, load balancing, and inference capacity. Focus on ensuring LLMs meet rigorous performance, safety, and security standards and enhancing core infrastructure for deploying inference technology globally.

Location: Hybrid (San Francisco, Seattle). Must be in one of our offices at least 25% of the time.

Salary: $405,000–$485,000 USD (Annual)

Company

hirify.global is a public benefit corporation focused on creating reliable, interpretable, and steerable AI systems.

What you will do

• Set technical strategy and oversee development of Claude on Azure across all layers of the technical stack.
• Collaborate across teams and companies to understand product, infrastructure, operations, and capacity needs.
• Work closely with cross-functional stakeholders to align on goals and drive outcomes.
• Create clarity for the team and stakeholders in an ambiguous and evolving AI environment.
• Take an inclusive approach to hiring and coaching top technical talent.
• Design and run processes (e.g., postmortem review, incident response, on-call rotations) for effective team operations.

Requirements

• 10+ years of experience in high-scale, high-reliability software development, particularly infrastructure or capacity management.
• 5+ years of engineering management experience.
• Experience recruiting, scaling, and retaining engineering talent in a high-growth environment.
• Experience scaling products, resources, and operations to accommodate rapid growth.
• Deep interest in the transformative effects of advanced AI systems and commitment to their safe development.
• Excellent written and verbal communication skills.
• Willing and able to travel frequently between Seattle and the SF Bay Area.

Nice to have

• Experience with machine learning infrastructure like GPUs, TPUs, or Trainium, as well as supporting networking infrastructure like NCCL.
• Experience as a Product Manager.
• Experience with deployment and capacity management automation.
• Security and privacy best practice expertise.

Culture & Benefits

• Mission to create reliable, interpretable, and steerable AI systems.
• Work as a single cohesive team on a few large-scale research efforts.
• Value impact, collaboration, and an empirical science approach to AI research.
• Competitive compensation and benefits, with optional equity donation matching.
• Generous vacation and parental leave, and flexible working hours.
• Hybrid policy: expected to be in one of our offices at least 25% of the time.
• Visa sponsorship is available.