Director, AI Engineering
United States · Remote · Permanent
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What the market looks like
We've tracked 1,200+ senior-level AI engineering postings across the US in the last six months, with hiring concentrated in California, New York, and Texas. Professional services, technology, and financial services firms are actively building out their AI engineering teams. Senior-level candidates in this space typically land in the $240k–$410k salary range. The strongest directors bring hands-on fluency with modern ML systems and infrastructure, genuine experience scaling teams through rapid AI adoption, and the judgment to balance engineering rigor with business velocity.
Job responsibilities
Lead the design, development, and deployment of AI/ML systems and products that drive measurable business value
Own the technical strategy for AI engineering initiatives, including architecture decisions, tooling, and infrastructure investments
Build and mentor an engineering team; set hiring bar, develop talent, and foster a culture of technical excellence and accountability
Partner with product, data science, and business stakeholders to translate requirements into robust, scalable systems
Drive best practices around model evaluation, testing, monitoring, and production reliability for AI workloads
Identify and remove technical blockers; iterate on processes and tooling to unblock the broader AI engineering organization
Represent engineering voice in AI strategy conversations; communicate trade-offs and technical constraints clearly to non-technical leaders
Candidate requirements
8+ years of software engineering experience, with at least 3 years directly building or shipping ML/AI systems in production
Proven track record managing and scaling an engineering team; experience hiring, developing, and retaining strong technologists
Deep hands-on fluency with modern ML tooling, frameworks, and infrastructure (e.g., PyTorch, TensorFlow, cloud ML platforms, MLOps practices)
Strong foundation in software engineering fundamentals: system design, testing, deployment, and operational excellence
Track record translating business problems into sound technical strategy and delivering measurable outcomes
Clear communicator able to explain technical concepts and constraints to cross-functional partners and executives