Director, AI Architecture
San Francisco, CA · Hybrid · Permanent
Heads up: this posting is for future opportunities rather than one specific open role. If you apply, we'll add you to our candidate network and may reach out when relevant roles come up.
Axial Search is a specialist executive search firm built for one kind of hire: leaders who help organizations navigate AI transformation. Apply today to express your interest in roles like this one.
Visit our website to learn more about our process and explore free tools for your job search, including our live job market dashboard with salary, skills and hiring trend data from thousands of AI transformation roles.
What the market looks like
We've tracked 500+ senior-level AI architecture postings across the United States in the last six months, with the strongest concentration in San Francisco, New York, and Texas. These roles span technology, professional services, financial services, healthcare, and manufacturing — each sector bringing distinct infrastructure and governance complexity. Compensation for this cohort typically ranges from $250K to $410K annually. The strongest candidates in this space combine deep hands-on experience designing and shipping ML systems at scale with the ability to set technical direction, influence cross-functional teams, and articulate architecture trade-offs to both engineers and business stakeholders.
Job responsibilities
Design, own, and evolve the organization's AI and machine learning architecture, including infrastructure, data pipelines, model deployment patterns, and integration frameworks
Lead technical strategy and roadmap planning for AI initiatives, balancing innovation with maintainability and operational risk
Partner with engineering, data science, and product teams to translate business requirements into scalable, performant system design
Drive architectural standards, best practices, and governance frameworks that scale AI/ML across the organization
Evaluate and recommend tools, frameworks, and platforms — cloud infrastructure, model serving, monitoring, orchestration — based on organizational needs and constraints
Mentor and guide engineering teams on architecture decisions, code review for AI systems, and production readiness
Communicate architecture decisions and trade-offs to senior leadership, explaining technical depth in business terms
Candidate requirements
10+ years building and shipping software systems, with 5+ years focused on machine learning infrastructure, AI systems, or data-intensive architecture
Demonstrated experience designing end-to-end ML pipelines, model serving infrastructure, and real-world deployment patterns at scale
Strong fluency in cloud platforms (AWS, GCP, or Azure), containerization, orchestration, and modern data stack tools
Proven ability to lead technical strategy, influence cross-functional teams, and communicate complex architecture concepts to non-technical audiences
Track record of making sound trade-off decisions between performance, cost, maintainability, and time-to-market