Director, AI Engineering
$269,000–$403,000 year
On-siteRedwood City, California, United States
Job Summary
Lead and scale a global Machine Learning Engineering organization by building production-grade AI/ML systems for next-generation generative and predictive capabilities. Define the vision for ML platform architecture, MLOps, and GenAI enablement while establishing best practices for model governance, security, and responsible AI standards. Own end-to-end delivery of ML pipelines and services, partnering with Data Science and Product to translate experimentation into scalable, enterprise-ready deployment. Drive the development of GenAI capabilities including LLMs, RAG, and automation workflows to unlock smarter decisions and sustained competitive advantage.
Required Qualifications
- 12+ years in software engineering, data engineering, or ML engineering
- 5+ years leading large, distributed engineering teams (including managers of managers)
- Proven track record of delivering ML/AI systems at scale in production environments
- Deep knowledge of machine learning systems, MLOps, and cloud-native architectures
- Experience with ML frameworks (e.g., TensorFlow, PyTorch) and data platforms
- Strong understanding of GenAI/LLMs, prompt engineering, and retrieval-augmented systems
- Familiarity with distributed systems, APIs, and microservices architecture
- Strong ability to translate business strategy into technical execution
- Experience driving large-scale transformation initiatives
- Excellent communication and stakeholder management skills
Desired Qualifications
- Experience building enterprise AI platforms or internal AI products
- Background in both predictive ML and generative AI use cases
- Experience in global delivery models (e.g., US + India engineering hubs)
- Master's or PhD in Computer Science, Engineering, or related field
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