Senior Director Generative Ai Engineering
Equinix
Generative AI leadership at Equinix calls for hands-on engineering across production systems, machine learning, and enterprise customer workflows. Locations include Redwood City, Dallas, and Toronto.The Senior Director AI leads design, engineering, and deployment across Sales, Marketing, and Customer Success. This technical leadership role builds production-grade systems driving pipeline growth, deal acceleration, retention, and operational efficiency. It connects AI engineering, enterprise architecture, and go-to-market strategy.Key Responsibilities:
Design generative AI solutions within CRM and customer workflowsBuild LLM copilots, agentic workflows, RAG pipelines, and predictive modelsOwn data, development, evaluation, deployment, and monitoring lifecyclesGuide PyTorch, TensorFlow, and Hugging Face implementation pipelinesEstablish CI/CD, experimentation, evaluation, and observability practicesRequirements:
12–15+ years in AI/ML, data science, or distributed systems8+ years leading ML or AI engineering teamsEnterprise-scale production AI delivery experienceGenerative AI, LLM, prompt engineering, and finetuning expertiseCloud, modern data stack, and distributed systems experienceLead Equinix AI engineering with generative AI, machine learning, enterprise architecture, and measurable revenue outcomes.
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Design generative AI solutions within CRM and customer workflowsBuild LLM copilots, agentic workflows, RAG pipelines, and predictive modelsOwn data, development, evaluation, deployment, and monitoring lifecyclesGuide PyTorch, TensorFlow, and Hugging Face implementation pipelinesEstablish CI/CD, experimentation, evaluation, and observability practicesRequirements:
12–15+ years in AI/ML, data science, or distributed systems8+ years leading ML or AI engineering teamsEnterprise-scale production AI delivery experienceGenerative AI, LLM, prompt engineering, and finetuning expertiseCloud, modern data stack, and distributed systems experienceLead Equinix AI engineering with generative AI, machine learning, enterprise architecture, and measurable revenue outcomes.
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