Senior Manager

Alzheimer's Disease Data Initiative • Seattle, WA

6d • $225,000 - $235,000

About The Position

The Senior Manager will lead the Global Research and Imaging Platform (GRIP) engineering and AI applications efforts. GRIP is a low- or no-cost, multimodal, white-labeled data platform that supports the end-to-end process from data capture and curation to secure analytics workspaces. It is supported by GRP, LLC, a nonprofit entity within the Alzheimer’s Disease Data Initiative, and uses a collaborative, modular, open-access approach to build and reuse capabilities across research and therapeutic areas.

GRIP currently supports the European Platform for Neurodegenerative Diseases (EPND) Tech Hub and AD Discovery Portal, the SpeechDx study app, the A4 study data-sharing portal, and secure AD Workbench workspaces, modules, and analysis workflows. The role owns the AI Applications Platform and interoperability roadmap, leads a remote engineering team, translates partner and organizational needs into product specifications, and guides platform and AI architecture. The position also oversees delivery quality, timelines, success metrics, and cloud and AI cost stewardship.

Requirements

• At least 3 years of direct experience managing engineers or technical teams in a fast-paced environment shipping features.
• Demonstrated engineering/technical leadership and experience co-leading product management.
• Experience building a product roadmap end to end, from partner or customer discovery through specification, build, and iteration.
• Hands-on architectural fluency with cloud infrastructure (Azure, AWS, or GCP), containerized services (Kubernetes/AKS), authentication and multi-tenant isolation patterns, and API/service design.
• Direct experience with AI/LLM-powered applications, including model integration patterns, inference cost drivers, and agent or workflow architectures; a considered perspective on practical product value for AI.
• Track record of cost-conscious infrastructure decisions and ability to explain the relationship between architecture choices and unit economics.
• Strong stakeholder-management skills and experience in a CPTO organization, working with program managers, or providing equivalent cross-functional leadership.
• Excellent written and verbal communication skills, including writing specifications, defending architecture decisions, and briefing executives.
• Bachelor’s degree in computer science, engineering, data science, bioinformatics, or a related technical field, or equivalent practical experience.
• Experience building or running research data platforms, such as secure data environments, trusted research environments (TREs), data commons, or federated analysis systems.
• Hands-on exposure to the modern AI stack, such as Azure OpenAI or other model providers, retrieval-augmented generation (RAG), vector stores, LLM evaluation and observability tooling, and MLOps/LLMOps practices.
• Experience managing distributed or vendor/partner engineering teams across time zones.
• Experience with Agile delivery and engineering tools such as Azure DevOps, Jira, GitHub, CI/CD pipelines, and infrastructure as code (Terraform/Bicep).

Nice To Haves

• Advanced degree.
• Experience in a regulated, research, healthcare, or scientific-data domain where privacy, data governance, and partner trust are important product constraints.
• Experience working in mission-driven organizations or with high-profile stakeholders.
• Experience in life sciences, ideally neuroscience or Alzheimer’s disease and related dementias (ADRD).

Responsibilities

• Lead and grow a remote team of engineers delivering AI features.
• Run engineering sprints and delivery rhythms; own outcomes from specification through build and release, and hold the team accountable for quality and timelines.
• Coach product managers to write clear, testable specifications.
• Build a culture of accountability, fast learning, attention to detail, and continuous improvement suited to a startup pace.
• Own the roadmap for the AI Applications Platform and interoperability layer, working with the CPTO and product leaders to align priorities with organizational goals and partner needs.
• Lead discovery with research partners, data scientists, and internal teams, translating unclear needs into problem statements, requirements, and feature specifications.
• Set and track adoption, reliability, cost, and partner-satisfaction metrics and use them to guide iteration.
• Influence platform architecture for Azure while supporting design patterns that can extend to AWS, GCP, or on-premises environments as needed, including containerized services, Kubernetes/AKS, APIs, service design, and interoperability standards.
• Influence and deliver architecture for AI/LLM integration, including model selection, inference patterns, agent and workflow orchestration, and evaluation frameworks.
• Present and defend design decisions in architecture reviews, weighing cost, security, performance, and scalability.
• Steward infrastructure and inference costs by modeling the unit economics of key architecture choices.
• Track cloud and AI spend, identify optimization opportunities, and build cost awareness into specifications and design reviews.

What This Job Offers

• Career Level: Senior