Senior Manager

The Global Research and Imaging Platform

(GRIP) is a low / no-cost, multi-modal, white-labeled data platform that provides end to end capabilities from data capture to curation to secure analytics environments (e.g., workspaces).

GRIP is supported by GRP, LLC

, a non-profit entity within the Alzheimer’s Disease Data Initiative

, a 501(c)(3) nonprofit organization, that brings data and tools together in a cloud-based environment to accelerate disease insights. Originally established to manage the increasingly complex workflows required for multimodal data curation and analysis in Alzheimer’s disease and related dementias, GRIP follows a “build it once and re-use” philosophy and a collaborative approach to co-building with partners. Its open-access, modular design incorporates open-source tools and workflows that can evolve with researcher needs.

A white-labeled approach supports expansion across therapeutic and research areas.

• GRIP currently powers the European Platform for Neurodegenerative Diseases (EPND) Tech Hub and
• AD Discovery Portal, the SpeechDx study app, A4 study data sharing portal, and secure
• AD Workbench workspaces, modules, and analysis workflows for scientists worldwide. Enabled by the AD Workbench, the Global Neurodegeneration Proteomics Consortium (

GNPC

) provides an established scientific collaboration through which shared data, tools, and analytical workflows can advance AD and related dementia research.

KEY RESPONSIBILITIES

• Lead and grow a remote team of engineers to deliver on the AI features
• Run engineering sprints and delivery rhythms, own outcomes across the path from spec to build to 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 set priorities that match organizational goals and partner needs.
• Lead discovery with research partners, data scientists and internal teams, and turn unclear needs into clear problem statements, requirements and feature specifications.
• Set and track success metrics for adoption, reliability, cost and partner satisfaction, and use them to guide iteration.
• Influence the platform architecture for Azure keeping design patterns to extend AWS/GCP /on premises when needed, containerized services (Kubernetes/AKS), API and service design, and interoperability standards.
• Influence and deliver the 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.
• With Cost stewardship governance, keep infrastructure and inference costs sustainable by modeling the unit economics of key architecture choices.
• Track cloud and AI spend, find ways to optimize it, and build cost awareness into specs and design reviews.
• REQUIRED SKILLS
• Demonstrated engineering/technical leadership and co-leading product management, with at least 3+ years managing engineers or technical teams directly in a fast-paced environment shipping features.
• Demonstrated experience in building a product roadmap end-to-end — from partner/customer discovery through spec, build, and iteration
• Hands-on architectural fluency: comfortable making and defending decisions on cloud infrastructure (Azure/AWS/GCP), containerized services (Kubernetes/AKS), authentication and multi-tenant isolation patterns, and API/service design
• Direct experience with AI/LLM-powered applications — model integration patterns, inference cost drivers, agent or workflow architectures — and a point of view on where AI adds real product value versus novelty
• A track record of cost-conscious infrastructure decisions — you can talk fluently about the relationship between architecture choices and unit economics
• Strong stakeholder management skills; experience being in a CPTO org, working with program managers, or equivalent cross-functional leadership Excellent written and verbal communication — you can write a spec, defend an architecture decision, and brief an executive in the same week
• Bonus: experience in a regulated, research, healthcare, or scientific-data domain, where privacy, data governance, and partner trust are first-order product constraints

QUALIFICATIONS OR RELATED EXPERIENCE

• Bachelor's degree in computer science, Engineering, Data Science, Bioinformatics, or a related technical field, or equivalent practical experience. An advanced degree is a plus.
• 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 tooling, such as Azure DevOps, Jira, GitHub, CI/CD pipelines, and infrastructure-as-code (Terraform/Bicep).
• Bonus: 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).