Platform Architect HPC & AI

We are seeking a strategic and systems-oriented Platform Architect to lead the architectural vision and technical direction for our next-generation high-performance and AI computing platform. This role is critical to scaling a secure, fault-tolerant, and cloud-native infrastructure that supports advanced scientific modeling, AI/ML workflows, and data-intensive computing across the life sciences and other innovation-driven sectors with a heavy emphasis on Model-informed Drug Development (MiDD).

The ideal candidate brings deep expertise in distributed systems, AI infrastructure, and HPC environments, combined with the ability to align architecture with regulatory, operational, and business requirements. The candidate should also have a deep understanding of HPC within AWS including ParallelCluster. You will collaborate across engineering, product, and compliance teams to ensure cohesive design, sustainable implementation paths, and a platform that is reliable and easy to support and use.

• Develop and guide an architectural blueprint that supports modular, scalable, and secure delivery of productized HPC and AI capabilities in the domains of Model-Informed Drug Development (MiDD), pharmacometrics, biostatistics and quantitative systems pharmacology.
• Design for resilience, fault tolerance, and operational durability to ensure platform services are stable and supportable at scale.
• Translate emerging scientific and business needs into infrastructure strategies that prioritize reliability, usability, and maintainability.
• Collaborate with engineering, infrastructure, product, and compliance teams to ensure architectural alignment with implementation and operational goals.
• Lead technical design reviews and act as an advisor on systems-level challenges, promoting clarity and coherence across teams.
• Foster shared understanding of platform design tradeoffs, emphasizing outcomes that improve the experience of users and those who support the platform.
• Define infrastructure requirements for reproducible, on-demand, and GxP-compliant compute environments.
• Ensure that security, observability, and operational control are embedded into platform architecture from the outset.
• Guide the use of containerization, orchestration, and service mesh technologies (e.g., Kubernetes, Istio, Argo) in collaboration with engineering teams.
• Architect scalable infrastructure for the full AI/ML lifecycle, including model training, deployment, and real-time inference.
• Evaluate and integrate emerging HPC and AI technologies (e.g., accelerators, AI agents, distributed frameworks) to enhance long-term platform capability.
• Define workload orchestration strategies that balance performance, cost-efficiency, and operational resilience.
• Perform feasibility and sustainability impact assessments for proposed architectures, including risk analysis, cost implications, and long-term maintainability.
• Represent architectural perspectives in customer engagements and business development efforts where platform design is a key differentiator.
• Collaborate with stakeholders to scope and shape technical solutions that align with product vision and customer requirements.
  Identify systemic architectural or operational issues and drive improvements that benefit both internal teams and external users.
• Please note: that this job description is not meant to be all-inclusive. Other duties may be assigned

• 10+ years of experience in software or platform architecture, including 5+ years in HPC, large-scale compute infrastructure, or AI platform development.
• Strong understanding of cloud-native architecture (AWS, Azure, or GCP), container technologies, and orchestration frameworks.
• Experience designing infrastructure that is resilient, fault-tolerant, and easy to operate, especially in regulated or high-stakes environments.
• Background in supporting AI/ML workflows (e.g., TensorFlow, PyTorch) and integrating workflow orchestration tools (e.g., Airflow, Nextflow, Argo Workflows).
• Familiarity with distributed systems and job scheduling (e.g., Slurm, HTCondor) in both research and production environments.
• Technical fluency across multiple languages and systems (e.g., Python, Go, R, Linux-based infrastructure).
• Strong communication and systems-thinking skills with a track record of collaborative problem solving.

• Familiarity with GxP compliance, 21 CFR Part 11, or regulated computing frameworks.
• Background in scientific computing, pharma R&D, or life sciences infrastructure.
• Exposure to AI agent orchestration frameworks (e.g., LangChain, NVIDIA NeMo, AutoGen).
• Experience with semantic data platforms or data lakehouse architecture.

• Bachelor’s degree in computer science, engineering, or a related field - or equivalent work experience with demonstrable expertise in platform-scale architecture.
• Experience collaborating across disciplines including engineering, infrastructure, networking, and security.
• Certifications in cloud, security, or systems architecture are preferred

The job frequently requires working at a computer terminal, standing or sitting, and the ability to operate the computer with proficiency.

The work environment is quiet with no adverse conditions.

Metrum Research Group offers competitive salaries and an excellent benefits package. You can read more about us by clicking the link at the top of this page, 'Company Website'.

Metrum Research Group is an Equal Opportunity Employer

Metrum Research Group EEO Statement