Platform Customer Engineer, Healthcare and Life Sciences, Google Cloud

Google Google · Big Tech · San Diego, CA +3

Customer Engineer for Google Cloud's Healthcare and Life Sciences sector, focusing on AI/ML solutions. This role involves partnering with technical sales teams to understand customer challenges, develop cloud solutions, conduct proofs-of-concept, and troubleshoot technical issues. The position requires experience with cloud-native architecture, ML model development and deployment, and customer-facing technical engagement.

What you'd actually do

  1. Own the technical account plan and strategy by participating in planning and supporting targeted sales motions.
  2. Leverage combined expertise in sales, programming, and solutions architecture to demonstrate the value of Google Cloud Platform through complex demos, pilots and in-depth workshops.
  3. Design cross-pillar solutions, secure technical wins, define initial delivery plans for customers, and lead technical engagement throughout the solution phase.
  4. Support the post-sales transition by managing pricing activities and transitioning the final delivery plan to implementation teams.
  5. Maintain awareness of progress against the delivery plan, providing support to cross-functional teams during ramp, delivery, migration or implementation phases.

Skills

Required

  • cloud native architecture
  • customer-facing support
  • technical stakeholder engagement
  • cloud engineering
  • programming languages
  • systems design
  • prototyping
  • demos
  • customer workshops
  • Machine Learning model development
  • Machine Learning model deployment

Nice to have

  • Infrastructure Modernization
  • Application Modernization
  • Data Management
  • Data Analytics
  • Cloud AI
  • Security
  • Networking
  • Migrations
  • SAP
  • sales cycle management
  • technical strategy development
  • delivery and consumption plan definition
  • application and service migration to cloud platforms
  • security concepts

What the JD emphasized

  • 10 years of experience with cloud native architecture in a customer-facing or support role.
  • Experience with Machine Learning model development and deployment.