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Equinix
Equinix
5,001 – 10,000 Employees
H1B Visa SponsorConsultingLogisticsManufacturing
Equinix provides digital infrastructure that helps organizations connect people, platforms, and services across global ecosystems. Its offerings include data centers, colocation, interconnection, ecosystem discovery, and digital services designed to support secure, high-performance connectivity for multicloud environments. By combining low-latency networks, high bandwidth, automation, and infrastructure designed with sustainability in mind, Equinix supports digital transformation for companies in sectors including financial services, telecommunications, manufacturing, and commercial markets.
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Senior Director of AI

Lead the development of production generative AI and machine learning systems for Equinix’s digital infrastructure business. Apply AI to sales and customer success, with goals that include pipeline growth, stronger retention, and improved deal velocity.

USUnited StatesCACaliforniaTXTexas
$182,000 – $403,000 / year
HybridFull-timeSeniorEnglish RequiredArtificial Intelligence
AWSAzureDistributed SystemsGoogle Cloud PlatformPyTorchTensorflow

Description

  • Lead development and deployment of generative AI and machine learning across Sales, Marketing, and Customer Success.
  • Integrate AI and ML solutions into CRM platforms and customer workflows.
  • Build LLM copilots, agent workflows, retrieval-augmented generation pipelines, and predictive models.
  • Manage the end-to-end lifecycle, from data sourcing and model development to evaluation, deployment, and monitoring.
  • Architect and guide model training and fine-tuning pipelines.
  • Develop real-time and batch inference systems, embedding pipelines, and vector database integrations.
  • Set standards for CI/CD, experimentation, model evaluation, and observability.
  • Design and deploy agents for multi-step reasoning, tool use, and workflow orchestration.
  • Create reusable approaches for prompt management, tool integration, policy enforcement, and agent lifecycle management.
  • Work with Sales and go-to-market leaders to incorporate AI into deal strategy and customer engagements.
  • Advance pipeline growth, deal velocity, account expansion, conversion, productivity, and customer retention.
  • Coordinate with Engineering, Data, Product, Sales, and Customer Success teams.
  • Turn business needs into scalable technical architectures and align the supporting systems, data, and workflows.
  • Lead and develop teams of ML engineers, ML scientists, and AI architects.
  • Set expectations for engineering quality, execution, technical depth, scalable development, and enterprise AI delivery.

Requirements

  • Bring 12–15 or more years of experience in AI/ML, data science, or distributed systems engineering.
  • Have 8 or more years of experience leading ML or AI engineering teams in platform or infrastructure environments.
  • Demonstrate a track record of delivering production AI systems at enterprise scale.
  • Have partnered with Sales, Marketing, or Customer Success teams to achieve business outcomes.
  • Bring deep practical experience with generative AI, including LLMs, prompt engineering, and fine-tuning.
  • Have strong experience with retrieval-augmented generation architectures and agentic AI systems.
  • Be proficient with ML frameworks such as PyTorch or TensorFlow.
  • Have experience with AWS, GCP, or Azure and modern data stacks.
  • Understand distributed systems, CI/CD, experimentation frameworks, and observability.
  • Have experience with Salesforce or enterprise CRM systems.
  • Have built internal AI platforms or developer tools.
  • Bring a background in SaaS or enterprise software.
  • Hold an advanced degree in Computer Science, Machine Learning, or a related field.
  • Have 15 or more years of experience.
  • A bachelor's degree is preferred.

Benefits

  • Employee Assistance Program.
  • Health, life, disability, and voluntary insurance plans.
  • Retirement plan contributions.
  • Paid time off.
  • Paid holidays.
  • Healthcare coverage supplementing the provincial healthcare system in Canada.
  • Defined Contribution Pension Plan (DCPP).
  • Group Retirement Savings Plan (RRSP).
  • Tax-Free Savings Plan (TSFA).
  • Vacation and personal time in Canada.
  • Eligibility for a bonus.
  • Potential equity offering, depending on the position.

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