Director of AI Solutions, Equinix

• 12–15+ years of experience in AI/ML, data science, or distributed systems engineering
• 8+ years leading ML or AI engineering teams in platform or infrastructure environments
• Proven track record delivering production-grade AI systems at enterprise scale
• Experience partnering with Sales, Marketing, or Customer Success organizations to drive business outcomes
• Deep hands-on experience with generative AI including LLMs, prompt engineering, and fine-tuning
• Strong experience with retrieval-augmented generation architectures and agentic AI systems
• Proficiency with ML frameworks such as PyTorch or TensorFlow
• Experience with cloud platforms including AWS, GCP, or Azure, and modern data stacks
• Strong understanding of distributed systems, CI/CD, experimentation frameworks, and observability
• Ability to operate as both a technical leader and business partner
• Strong executive communication and stakeholder management skills
• Experience influencing senior stakeholders and driving alignment across highly matrixed organizations
• Ability to translate complex technical systems into clear business value
• Experience with building AI solutions for Enterprise and driving value through revenue growth like New Logo’s, Recommendations for Crosssell-Upselll

Desirable

• We are seeking a Director of AI Solutions to lead the design, engineering, and deployment of generative AI and machine learning systems across Sales, Marketing, and Customer Success
• This is a hands-on technical leadership role responsible for building and scaling production-grade AI systems that directly drive revenue outcomes, including pipeline growth, deal acceleration, customer retention, and operational efficiency
• You will operate at the intersection of AI engineering, enterprise architecture, and go-to-market strategy, partnering closely with Sales, Product, and Engineering leaders to translate AI capabilities into measurable business value
• Lead End-to-End GenAI and ML System Delivery
• Design and deploy generative AI and machine learning solutions embedded in CRM and customer workflows
• Build systems including LLM-powered copilots, agentic workflows, retrieval-augmented generation pipelines, and predictive models
• Own the full lifecycle from data sourcing and model development to evaluation, deployment, and monitoring
• Architect and guide implementation of model training and fine-tuning pipelines using frameworks such as PyTorch, TensorFlow, and Hugging Face. Build real-time and batch inference systems, embedding pipelines, and vector database integrations. Establish best practices for CI/CD, experimentation, model evaluation, and observability across AI systems
• Design and deploy agent-based systems capable of multi-step reasoning, tool usage, and workflow orchestration across enterprise platforms. Establish reusable patterns for prompt management, tool integration, policy enforcement, and agent lifecycle management
• Partner with Sales and go-to-market leadership to embed AI into deal strategy and customer engagements. Contribute directly to pipeline growth, deal velocity, and account expansion. Translate AI capabilities into measurable outcomes including conversion improvement, productivity gains, and customer retention
• Collaborate across Engineering, Data, Product, Sales, and Customer Success to deliver integrated AI solutions. Translate complex business problems into scalable technical architectures and ensure alignment across systems, data, and workflows
• Lead and grow teams of ML engineers, ML scientists, and AI architects. Establish a high bar for engineering quality, execution, and technical depth. Build scalable development practices and delivery models for enterprise AI