Scientific Computing Cloud Architect (Life Sciences)

1. Solution Architecture & Strategy:

• Provide technical leadership across solution lifecycle (design → implementation → optimization):

  • Lead technical discovery sessions and design reviews.

  • Translate complex scientific and business requirements into scalable, production-ready solutions.

  • Define end-to-end cloud architecture strategies for life sciences clients, aligning with business and scientific objectives.

  • Lead architecture design for hybrid and cloud-native HPC platforms.

• Act as a trusted advisor, guiding clients through architecture decisions and industry best practices.
  
  

2. HPC & Accelerated Computing Platforms:

• Architect and deploy HPC environments.

• Design GPU-enabled architectures. 

• Optimize for performance, scalability, and cost efficiency across distributed compute systems.
  
  

3. Enterprise Data & Analytics Platforms:

• Architect modern data platforms to support scientific and operational workloads.

• Design and implement: 

  • Data ingestion frameworks (ETL/ELT, streaming pipelines).

  • Metadata and lineage management solutions.
    

• Align data platforms to FAIR principles for scientific data usability and reproducibility.

• Enable downstream use cases including analytics, AI/ML, and data science.
  
  

4. Governance, Security & Regulatory Compliance:

• Design compliant architectures aligned with: 

  • GxP validation frameworks.

  • HIPAA data protection requirements.

  • GDPR privacy and data handling guidelines.

• Implement enterprise-grade: 

  • Access controls and IAM strategies.

  • Data encryption, auditing, and traceability.

• Support documentation and validation requirements for regulated workloads.
  
  

5. Client Engagement & Leadership:

• Act as a trusted advisorto clients.

• Facilitate architecture workshops, design reviews, and technical discovery sessions.

• Bridge business, scientific, and engineering teams to ensure aligned outcomes.

• Provide hands-on guidance during POCs, migrations, and production deployments.

• Contribute to solution proposals, roadmaps, and technical strategy development.
  
  

6. Engineering Enablement & Best Practices:

• Promote automation and infrastructure-as-code practices (Terraform, Ansible).

• Encourage best practices for: 

  • Performance optimization.

  • Cost management.

  • Security and governance.

• Mentor engineering teams and support capability development.