Director, AI Engineering
United States · Remote · Permanent
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What the market looks like
We've tracked over 500 senior-level AI architecture postings across the US in the last six months, with the strongest hiring concentrated in California, Texas, and New York. Compensation for directors in this function typically lands between $250K and $420K annually. Organizations posting for this seniority are looking for leaders who can translate business strategy into concrete AI systems, lead cross-functional teams through technical complexity, and own architectural decisions that shape product roadmap. The best candidates bring a mix of deep technical fluency in AI/ML systems design, proven experience scaling engineering teams, and the ability to communicate architectural trade-offs to both technical and non-technical stakeholders.
Job responsibilities
Own the design and evolution of AI architecture across one or more product lines, balancing performance, scalability, and cost
Lead and mentor a team of AI/ML engineers, architects, and senior individual contributors, setting technical direction and raising bar on execution
Partner with product, data science, and platform teams to translate business requirements into architectural requirements and validate feasibility
Drive adoption of best practices around model deployment, monitoring, versioning, and governance across engineering organization
Evaluate and integrate new AI/ML tools, frameworks, and infrastructure; make build-vs-buy decisions on core capabilities
Lead technical design reviews on high-stakes AI initiatives; own risk assessment and mitigation for novel approaches
Communicate technical strategy and progress to executive stakeholders; translate architectural decisions into business impact
Candidate requirements
8+ years of hands-on experience building and shipping AI/ML systems, with at least 3 years in an architecture or technical leadership role
Deep technical fluency in machine learning systems design, including training pipelines, inference infrastructure, model serving, and monitoring
Demonstrated experience leading engineering teams (5+ people) through complex technical challenges and shipping at scale
Strong track record making architectural decisions under uncertainty and communicating trade-offs across technical and non-technical audiences
Experience with cloud infrastructure (AWS, GCP, or Azure) and modern data/ML stack tools in production environments
Comfort operating as a bridge between technical execution and business strategy; ability to map business problems to technical solutions