Senior Healthcare & Life Sciences Solutions Architect, AI Solutions, Hcls

Amazon Amazon · Big Tech · Chicago, IL · Solutions Architect

This role focuses on designing and implementing cloud architectures, particularly leveraging AI/ML and Generative AI, for Healthcare and Life Sciences customers on AWS. The Solutions Architect will build prototypes, provide technical guidance, and create reference architectures to accelerate customer adoption of AWS services in the HCLS domain.

What you'd actually do

  1. Ensure success in building and migrating applications, software, and services on the AWS platform for HCLS customers
  2. In partnership with the account management team, formulate and execute a customer engagement strategy
  3. Build prototypes, proofs of concept, and demonstration assets that showcase AWS capabilities — particularly in AI/ML, Generative AI, and data analytics — tailored to healthcare and life sciences use cases
  4. Educate customers on the value proposition of AWS and participate in deep architectural discussions and ensure solutions are designed for successful deployment in the cloud
  5. Stay current on emerging AI/ML technologies and cloud-native patterns, and translate that knowledge into actionable guidance and reference architectures for HCLS customers

Skills

Required

  • 3+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
  • Experience in a technical role within a sales organization

Nice to have

  • Experience in IT development or implementation/consulting in the software or Internet industries
  • Knowledge of software development tools and methodologies

What the JD emphasized

  • Healthcare & Life Sciences (HCLS)
  • AI/ML
  • Generative AI
  • cloud architectures
  • AWS services
  • HIPAA-compliant

Other signals

  • design cloud architectures
  • accelerate the adoption of AWS services
  • craft highly scalable, flexible, and resilient cloud architectures
  • define or invent cloud-native reference architectures for a variety of use cases (e.g., Artificial Intelligence, Machine Learning, Generative AI, Serverless and Container-based architectures, Analytics and Big Data, DevOps, and Security)
  • build prototypes, proofs of concept, and demonstration assets that showcase AWS capabilities — particularly in AI/ML, Generative AI, and data analytics — tailored to healthcare and life sciences use cases
  • Stay current on emerging AI/ML technologies and cloud-native patterns, and translate that knowledge into actionable guidance and reference architectures for HCLS customers