Principal Software Architect

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) Applying prompt engineering, evaluation techniques, and guardrails to ensure reliability and compliance Collaborating with data and platform teams to operationalize AI—not just prototype it Deep ML expertise is not required —we’re looking for strong engineers who understand how to apply AI capabilities in real products . Take the first step toward your dream career.  Here is what we are looking for in this role.   Qualifications 10+ years in web application development , service-oriented architecture, cloud-native platforms, and AI-enabled application design preferred   10+ years in full-stack enterprise application development roles, with experience integrating AI, automation, analytics, or data-driven capabilities preferred   10+ years leading Software Engineering teams, including mentoring architects and engineers on AI adoption, architectural trade-offs, and modern delivery practices preferred   Professional Skills   Demonstrate ability to evaluate new technologies, including AI platforms and frameworks, and present comparative analysis of benefits, risks, costs, and implementation considerations   Strong problem-solving abilities    Excellent written and verbal communication skills    Ability to influence technical strategy across product, engineering, security, data, and business stakeholders while advocating for responsible and practical AI adoption   Technical Skills    Mastery level of software architecture and design , with strong understanding of AI-enabled system design patterns   Deep understanding of Microsoft .NET and modern application integration patterns for AI-enabled services   Expert level in relational and non-relational database design, data modeling, and data architecture for analytics and AI use cases   Experience with enterprise applications in a SaaS Cloud Environment (AWS, Azure, etc.), including scalable deployment patterns for AI, ML, and data-intensive workloads   Knowledge of AWS products and deployment, with familiarity in cloud AI services, model hosting, automation, monitoring, and secure integration patterns   Familiarity with AI/ML concepts such as model lifecycle management, prompt engineering, retrieval-augmented generation, evaluation frameworks, observability, and MLOps practices   Understanding of responsible AI, enterprise data protection, privacy, security, compliance, and governance considerations for production AI systems   AI Use Statement Employees are expected to appropriately leverage company-approved AI tools to improve productivity and quality while adhering to company policies, protecting confidential information, validating AI-generated content, and exercising sound professional judgment. AI is intended to augment—not replace—professional judgment, critical thinking, accountability, and decision-making. Accountability for all work remains with the employee. Accelerate your skills and career within a fast-growing company while impacting the future of healthcare. We have shared our story, now we look forward to