#EG AI Delivery Project Manager / Scrum Master

About the Company

Responsibilities

• ● Own delivery of the squad's engagement through the FDE lifecycle - Discover, POC, POV, PRR, Scale, Operate - tracking where each workstream sits and what's needed to move it to the next gate.
• ● Plan and execute short-cycle POCs/POVs from concept to evaluation, including receiving and refining scoped opportunities handed off from AI Mission.
• ● Define minimal scope, success criteria, and timelines appropriate to each lifecycle stage; prioritize features based on value, feasibility, and constraints.
• ● Coordinate the PRR gate as the delivery-side owner - tracking the five-pillar checklist to readiness, in partnership with the AI Architect and AI/LLM Specialist.
• ● Run lightweight Agile ceremonies - daily stand-ups, sprint planning & refinement, demo reviews, and retrospectives - adapted for AI/Gen AI work.
• ● Promote velocity, transparency, and continuous improvement across experimentation-heavy sprints.
• ● Unblock progress quickly - including chasing down data access, model access, or compliance sign-offs that commonly stall AI engagements - and minimize ceremony overhead.
• ● Maintain a working risk register specific to AI delivery - hallucination/accuracy risk, data quality dependency, model/token cost exposure, and latency - and translate these into scope and timeline decisions the squad can act on.
• ● Advise stakeholders directly when a request is technically impractical, high-risk, or better served by a non-Gen AI approach, drawing on input from the AI Engineer, AI/LLM Specialist, and Data Scientist.
• ● Maintain working awareness of the Gen AI model landscape - including China-origin models as increasingly viable, cost-effective options - sufficient to have an informed feasibility conversation with technical leads and clients.
• ● Own secure software delivery and governance practices as a standing checkpoint through the lifecycle, not just at PRR - flagging compliance gaps early enough to act on them.
• ● Act as the delivery-side connective tissue across AI Mission, AIIS, and AI Experience for the squad's engagement.
• ● Translate problem statements into achievable POC/POV plans, and manage expectations around what can be delivered, when, why, and at what lifecycle stage.
• ● Facilitate clear communication between business and engineering, bringing a consulting mindset and customer-first attitude to stakeholder interactions.
• ● Socialize learnings, outcomes, and next steps; present outcomes and lifecycle-stage recommendations to stakeholders.