Lead Business Transformation Architect

This role focuses on translating business needs into AI/ML roadmaps and designing scalable cloud architectures for AI solutions. It involves leading the deployment and integration of AI models and applications on cloud platforms, managing the necessary cloud infrastructure, and overseeing security, compliance, cost, and performance aspects. The role requires experience with AI/ML concepts, cloud platforms, and technology architecture, with a focus on deploying AI solutions in cloud environments.

What you'd actually do

  1. Translating business needs into artificial intelligence and machine learning roadmaps and scalable cloud architecture designs
  2. Leading the design, deployment, and integration of artificial intelligence models and applications across cloud platforms such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform
  3. Managing cloud infrastructure components, including compute, storage, and networking, to support artificial intelligence workloads
  4. Overseeing security, compliance, cost, performance, and disaster recovery considerations for artificial intelligence solutions
  5. Collaborating with executives, developers, and cross-functional teams to define requirements, secure alignment, and support solution adoption

Skills

Required

  • 2+ years of experience with artificial intelligence or machine learning concepts and algorithms
  • 5+ years of experience with Amazon Web Services, Microsoft Azure, Google Cloud Platform, or their artificial intelligence, agentic, or data services
  • 3+ years of technology architecture experience
  • Experience designing or deploying artificial intelligence solutions in cloud environments
  • Experience managing security, compliance, cost, or performance considerations for cloud-based solutions
  • Ability to travel 50%
  • Must be legally authorized to work in the United States without the need for employer sponsorship

Nice to have

  • Experience with marketing technology platforms or customer engagement platforms
  • Experience developing artificial intelligence or machine learning strategy for client or enterprise use cases
  • Experience leading cloud-based artificial intelligence implementation across cross-functional teams
  • Experience with governance, risk, or disaster recovery planning for artificial intelligence solutions
  • Experience presenting technical recommendations to executive stakeholders

What the JD emphasized

  • artificial intelligence or machine learning concepts and algorithms
  • Amazon Web Services, Microsoft Azure, Google Cloud Platform, or their artificial intelligence, agentic, or data services
  • artificial intelligence solutions in cloud environments
  • security, compliance, cost, or performance considerations for cloud-based solutions

Other signals

  • Translating business needs into artificial intelligence and machine learning roadmaps
  • Leading the design, deployment, and integration of artificial intelligence models and applications
  • Managing cloud infrastructure components to support artificial intelligence workloads
  • Overseeing security, compliance, cost, performance, and disaster recovery considerations for artificial intelligence solutions
  • Experience designing or deploying artificial intelligence solutions in cloud environments