about the company.
一家在日本拥有近1亿客户,全球客户总数达10亿,提供超过70种服务,涵盖电子商务、支付服务、金融服务、电信、媒体、体育等众多领域的集团。
about the team.
AI & Data Division (AIDD)
about the job.
1. Project Management (Primary Scope):
Cross-Functional Delivery: Plan lead end-to-end project execution across engineering, platform/infrastructure, operations teams from kickoff through release.
2. Release Lifecycle Management: Own release readiness, issue triage, version closeout, release-note generation within Jira equivalent tools to ensure high delivery quality.
3. Stakeholder & Dependency Coordination: Act as the primary liaison across teams to surface cross-functional dependencies, risks, blockers early drive resolution.
4. Execution & Communication: Facilitate project ceremonies (standups, status reviews, go/no-go gates), maintain clear status reporting, drive data-informed decision-making.
5. Product Management (Focused Scope):
Strategy & Roadmap: Define product vision, strategy, long-term roadmaps, key metrics fthe AI Platform.
6. Requirements & Definition: Gather requirements from internal stakeholders translate them actionable PRDs key performance indicators.
7. Platform Adoption & Operations: Drive internal platform adoption across business units collaborate on internal cost allocation/chargeback mechanisms.
skills experience required.
1. Mandatory Qualifications:
Project Management Experience: Proven experience as a Project Manager driving cross-functional delivery fdeveloper platforms, infrastructure products, ML/AI platforms, enterprise SaaS.
2. Release Lifecycle Ownership: Hands-on experience owning release readiness, version tracking, issue triage, documentation using Jira equivalent tooling.
3. Cross-Functional Collaboration: Demonstrated capability to coordinate with engineering, platform, operations/SRE teams to deliver complex projects on schedule.
4. Product Management Competency: Experience as a Product Manager translating ambiguous requirements clear PRDs, roadmaps, metrics.
5. Core Soft Skills: Data-driven mindset accompanied by strong communication interpersonal skills in a global, multicultural environment.
Nice-to-Have Skills:
1. Familiarity with GPU/AI infrastructure concepts (e.g., Kubernetes, scheduling, multi-tenancy, inference serving, MLOps).
2. Experience building scaling internal platforms driving product adoption across multiple internal teams.
3. Familiarity with LLM generative AI infrastructure (training, inference, serving).
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