Principal Software Architect

About the role

About eClinical Solutions

eClinical Solutions is transforming clinical development with elluminate®, our Clinical Data Cloud, helping life sciences organizations unify, analyze, and unlock the value of their data faster than ever before. By combining a modern cloud platform with expert data services, we empower smarter decisions across the clinical trial lifecycle—accelerating innovation that ultimately improves patient outcomes.

Our engineering teams build enterprise-grade, revenue-generating products at the intersection of cloud, data, analytics, and emerging AI technologies. If you’re excited about building sophisticated software that makes a real-world impact on healthcare, this is the place to do it.

You will make an impact:

The Principal Software Architect will lead the design and evolution of AI-enabled software platforms, helping translate business and product needs into scalable, secure, and responsible technical solutions. This role partners closely with software engineers, product teams, data specialists, and business stakeholders to identify opportunities for AI, guide architecture decisions, review implementations, and mentor teams on modern engineering practices, AI-assisted development, and sound design principles.

Your day to day:

- Research emerging AI, machine learning, generative AI, cloud, and software architecture technologies and evaluate their fit for the product platform

- Analyze existing features, data flows, and system designs for scalability, performance, security, and AI-readiness in order to design and recommend solutions

- Document current and future architectural patterns, including AI integration patterns, model lifecycle considerations, data governance, observability, and responsible AI guardrails

- Communicate complex AI, data, and architecture concepts clearly to technical and cross-functional colleagues

- Define reference architectures for AI-enabled capabilities, including data ingestion, retrieval-augmented generation, model integration, inference services, monitoring, and human-in-the-loop workflows

- Promote responsible AI practices, including privacy, security, explainability, bias mitigation, regulatory awareness, and appropriate use of enterprise data

- Guide teams in the effective use of AI-assisted engineering tools to improve productivity, code quality, documentation, testing, and delivery velocity

AI & Modern Engineering Focus

We’re actively incorporating AI-powered capabilities into our platform, and you’ll help shape how this is done responsibly and effectively in an enterprise environment. This includes:

- Integrating LLMs and AI services into .NET- and Python-based systems

- Designing and implementing AI-assisted workflows, copilots, or intelligent automation features

- Working with agentic AI patterns (e.g., task orchestration, tool-using agents, workflow automation)