Director, Solution Architecture
HybridSpring House, Pennsylvania, United States
Job Summary
Define and lead the end-to-end architecture for a next-generation, AI-powered Design–Make–Test–Learn engine, establishing a forward-looking roadmap aligned to Discovery strategy. Architect closed-loop data generation systems that integrate molecular design models with laboratory automation, ensuring computational scalability and seamless integration across enterprise platforms. Guide the translation of architectural designs into production-grade solutions while leading a team of solution architects to drive consistency in practices and foster continuous learning. This role sits at the intersection of science, data, and automation to accelerate pipeline delivery and create a durable competitive advantage through proprietary data.
Required Qualifications
- A background in Computer Science or equivalent
- 7+ years of experience leading a commercial or IT domain in digital solutions, systems integration, or architecture
- Proven experience in implementing automation architecture for large initiatives (> USD 500Mio)
- Deep experience with integration patterns to connect multiple solution components and discovery systems
- Ability to assess proposed solutions, articulate options, define architectural principles and recommend a path forward
- Understanding how to translate business process needs into technology solutions
- Comfortable working at an abstract level and shifting to the highest-impact answer
- Skilled at articulating trade-offs among business needs, technology requirements, timelines, costs, and risks
- Ability to influence across multiple levels of a global organization
- Location: Spring House, PA
Desired Qualifications
- Cloud-native and serverless architecture across major cloud providers, including containers and orchestration
- Modern integration: API design, API management, event-driven patterns
- Lab automation and orchestration
- Data & analytics: data integration, MDM, data governance, lakehouse/warehouse patterns, and streaming analytics
- AI/ML enablement: MLOps, DataOps, AgentOps foundations, responsible AI considerations, and implement GenAI and Agentic AI safely for productivity and customer experiences
- DevSecOps and platform engineering: CI/CD, infrastructure as code, automated security scanning, and policy as code
- Observability and reliability engineering: distributed tracing, logging/metrics, and tooling to meet SLO/SLAs
- Confidence operating in complex, regulated global ecosystems
- Change Management
- Consulting
- Cross-Functional Collaboration
- Design Mindset
- Emerging Technologies
- Enterprise IT Governance
- Information Security Management System (ISMS)
- Information Technology Strategies
- IT Architecture
- Process Improvements
- Product Configuration
- Program Management
- Requirements Analysis
- Solution Architecture
- Tactical Planning
- Technical Credibility
- Technical Writing
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