Advisor Clinical Tech Systems Engineering

Key Responsibilities

• Identify the toughest problems across the clinical technology landscape and shape modern, resilient, secure solutions, owning the full technical direction in partnership with business owners.
• Lead data and solution integration across the ecosystem, ensuring reliable, performant connectivity between clinical platforms, data products, and services.
• Partner tightly with Software Product Engineering, Cyber Security, and Infrastructure & Digital Core to drive aligned strategies, shared standards, and secure-by-design architectures.
• Research, evaluate, and apply emerging technology—including AI/ML, LLM-based tooling, and agentic workflows—driving adoption across clinical systems.
• Champion modernization and resilience, reducing technical debt and improving fault tolerance, observability, and recoverability.
• Embed secure and AI-assisted engineering practices (code generation, automated testing, intelligent monitoring, threat-aware design) into delivery to accelerate value and raise quality.
• Serve as a recognized expert for one or more clinical technologies, setting integration patterns and engineering standards adopted across teams.
• Elevate technical colleagues by sharing data, integration, and security knowledge to accelerate their growth.
• Improve engineering processes and guide the organization through change, making benefits and trade-offs clear.
• Gain support for and influence initiatives spanning clinical capabilities, engineering, cyber, and infrastructure.
• Provide authoritative technical leadership on complex integration, implementation, and troubleshooting efforts.

Basic Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field.
• Extensive software/systems engineering experience with a track record of owning and delivering complex, enterprise-scale solutions.
• Strong data and solution integration experience across large, complex, evolving ecosystems.
• Recognized depth in one or more technologies, able to set integration and engineering standards and guide other engineers.
• Experience applying AI in day-to-day engineering (e.g., AI-assisted coding, automated testing, intelligent observability).
• Experience across integration patterns, APIs, event-driven architecture, and cloud platforms (Azure, AWS, or GCP).
• Experience designing resilient solutions in partnership with engineering, cyber, and infrastructure teams.
• Experience with solving the toughest technical problems with broad business impact.