AI/Digital Project Manager - Healthcare and Life Sciences

5w1 month ago

Sia

Elkridge, US · Full-time · $105,000 – $120,000

About this role

Sia/LBG is seeking an experienced AI/Digital Project Manager / Scrum Master to support early-stage AI and digital initiatives across operational teams at a client's manufacturing site. This role will help guide agile delivery for proof-of-concept and MVP projects involving emerging AI-enabled tools.

As the AI/Digital Project Manager / Scrum Master, you will facilitate agile ways of working including sprint planning, daily stand-ups, backlog refinement, sprint reviews, and retrospectives. You will help teams clarify priorities, define sprint goals, remove blockers, manage dependencies, and maintain momentum in a fast-moving environment.

You will work closely with site-based operations teams, product owners, technical and manufacturing teams, data specialists, cybersecurity, compliance, and business stakeholders. Your focus will be on enabling delivery rather than serving as the technical expert, bridging the gap between operational needs and technical delivery.

You will help ensure AI proof-of-concepts and MVPs are grounded in real business problems and designed for adoption. You will also promote awareness of delivery considerations including data availability, cybersecurity risks, and responsible use of AI, helping the client deliver structured, secure, and impactful solutions.

Requirements

Proven experience as a Scrum Master or Agile Project Manager in a technology or digital environment.
Familiarity with AI tools and emerging technologies, but not a data scientist or AI engineer.
Strong facilitation and stakeholder management skills.
Experience working in the healthcare or life sciences industry.
Ability to translate business needs into technical priorities and sprint goals.
Understanding of cybersecurity and compliance considerations in a manufacturing setting.
Experience supporting proof-of-concept and MVP delivery.

Responsibilities

Facilitate agile ceremonies including sprint planning, daily stand-ups, backlog refinement, sprint reviews, and retrospectives.
Partner with product owners, technical teams, and business stakeholders to translate operational needs into clear priorities and MVP deliverables.
Support early-stage AI proof-of-concept and MVP work.
Help teams manage delivery risks, dependencies, blockers, and scope.
Bridge the gap between operational teams and technical delivery teams.
Promote awareness of delivery considerations such as data availability, latency, compute constraints, model reliability, cybersecurity risks, and responsible use of AI.
Maintain momentum in a fast-moving and often ambiguous environment.