Software Architect

Software Architect - NVIDIA & Clinical Trial Data

My client helps organizations reimagine their business through data-driven strategies, AI-powered solutions, and cutting-edge technology implementations.

Role Overview

We are looking for a Software Architect with deep expertise in NVIDIA AI and GPU technologies to drive the development of high-performance solutions for clinical trial data processing and analysis. This role is ideal for a technology leader with a strong consulting background, who can guide clients in the life sciences sector through digital transformation and AI-driven innovation.

Key Responsibilities

• Architect and design scalable software solutions leveraging NVIDIA AI, GPUs, and accelerated computing for clinical trial data management and analysis.
• Collaborate with data scientists, ML engineers, and healthcare clients to develop AI-driven insights for drug discovery and patient outcomes.
• Optimize data processing pipelines using NVIDIA Clara, RAPIDS, TensorRT, and CUDA for real-time analytics and predictive modelling.
• Provide technical leadership in cloud-based and on-premise deployments, integrating AWS, Azure, or GCP with NVIDIA infrastructure.
• Work closely with regulatory and compliance teams to ensure solutions meet HIPAA, GDPR, and FDA requirements for clinical data.
• Act as a trusted advisor to clients, shaping digital transformation strategies and identifying new opportunities for AI adoption in life sciences.
• Lead and mentor development teams, ensuring best practices in software engineering, MLOps, and DevOps.
• Support business development efforts, including proposal writing, client presentations, and thought leadership.

Required Skills & Experience

• 4+ years in software architecture and development, with at least 2 years working with NVIDIA technologies in healthcare or life sciences.
• Strong knowledge of NVIDIA AI, CUDA, TensorRT, RAPIDS, and Clara for clinical data applications.
• Experience in designing high-performance computing (HPC) and AI-driven data pipelines.
• Familiarity with clinical trial data standards (CDISC, HL7, FHIR) and regulatory compliance.
• Expertise in cloud-based AI deployments (AWS, Azure, GCP) and MLOps best practices.
• Background in management consulting or technology advisory, with experience leading client engagements and delivering enterprise-level solutions.
• Strong problem-solving, stakeholder management, and communication skills.

Preferred Qualifications

Experience with digital twin technology and synthetic data generation for clinical trials.

Knowledge of biostatistics, real-world evidence (RWE), and drug development processes.

Certifications in NVIDIA Deep Learning Institute (DLI), Cloud AI solutions, or Healthcare Data Management.