Scientific Computing Cloud Architect

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
• Architect and deploy HPC environments
• Design GPU-enabled architectures
• Optimize for performance, scalability, and cost efficiency across distributed compute systems
• 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
• 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
• Act as a trusted advisor to 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
• 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

Essential Qualifications

• 10–12+ years of experience in cloud architecture, infrastructure, or platform engineering
• Cloud Professional Certification(s)
• Proven expertise in:
• HPC administration (Slurm or similar)
• GPU-enabled computing environments
• Linux system architecture and administration
• Strong experience designing enterprise data platforms and data pipelines
• Knowledge of:
• Data governance, metadata management, and data lifecycle frameworks
• Security and compliance standards (GxP, HIPAA, GDPR)
• Experience working in client-facing or consulting environments
• Excellent communication and cross-functional collaboration skills
• Familiarity with:
• Bioinformatics workflows (e.g., genomics pipelines)
• Scientific workflow orchestration tools
• Experience with:
• Containerization (Docker) and orchestration (Kubernetes)
• Distributed storage systems and high-performance file systems
• Azure CycleCloud or equivalent HPC orchestration platforms
• Programming/scripting: Python, Bash, or similar

Preferred Qualifications

• Experience in life sciences, biotech, or healthcare data environments