Sr. Solutions Architect, HCLS AI/ML and Data Strategy Specialists, Global Healthcare - Amazon Web Services
Solutions Architect
We're looking for a Solutions Architect focused on designing and building scalable technical solutions. This lead role requires 6+ years of relevant experience.
About the role
DESCRIPTION
Leading complex, multi-stakeholder technical engagements focused on enterprise analytics strategy, data governance, and AI/ML — presenting decisions to leaders multiple tiers above your level
Defining data and analytics reference architectures and reusable patterns for healthcare use cases (enterprise data platforms, data lakes/lakehouses, data mesh, real-world evidence, population health analytics, clinical & operational reporting, value-based care analytics)
Designing data governance frameworks for healthcare organizations — including data quality, lineage, cataloging, access controls, and compliance in regulated environments (HIPAA, HITRUST, state privacy laws)
Bridging the gap between data strategy and AI/ML — ensuring customers have the data foundations, pipelines, and governance needed to operationalize AI/ML and generative AI at scale
Handling complex business and technology problems — defining and validating requirements, leading end-to-end design, and representing benefits and challenges of each approach
Influencing stakeholders and partners across the organization to drive best practices and force-multiply team impact
Mentoring and developing other technical professionals across the HCLS organization
Producing thought leadership content (blogs, reference architectures, re:Invent sessions, workshops) that simplifies and scales the team's impact
Helping healthcare organizations unlock the value of their data to improve patient outcomes and operational efficiency through responsible analytics and AI
Designing enterprise-grade data platforms, governance frameworks, and analytics architectures in regulated environments (HIPAA, HITRUST, FDA, GxP)
Bridging the worlds of data engineering, analytics, and AI/ML to create end-to-end value for customers
Simplifying and driving the use of best practices across technical communities
Executive engagement and communication — trusted to present to and influence senior leadership; whiteboard sessions, EBCs, and executive presentations
Healthcare data and analytics — architecting, building, or deploying enterprise analytics platforms, data governance programs, or data strategy engagements in healthcare/life sciences
AI/ML foundations — understanding of how data strategy enables AI/ML and generative AI; experience with production ML pipelines, model training/inference, or GenAI applications
Technical leadership — independently designing long-term solutions, taking the lead on initiatives, and delivering without close supervision
Influence and force multiplication — driving adoption of best practices, mentoring others, and scaling impact beyond individual contribution