Technical Project Manager -AI Platform at Bitdeer Technologies Group in Singapore; Penang

  • Company: Bitdeer Technologies Group
  • Location: Singapore; Penang, Malaysia
  • Job type: full time
  • Workplace: onsite
  • Posted: 2026-10-15

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Job description

About Bitdeer: Bitdeer is a world-leading technology company for Bitcoin mining and AI cloud. Bitdeer is committed to providing comprehensive Bitcoin mining solutions for its customers. Apart from designing industry-leading ASIC chips and manufacturing mining rigs, the Group handles complex processes involved in computing across the value chain. This includes equipment procurement, transport logistics, datacenter design and construction, equipment management, and network and facility operations. Bitdeer also offers advanced cloud capabilities to customers with a high demand for artificial intelligence. Headquartered in Singapore, Bitdeer operates globally with a diversified 3 GW energy portfolio, and deploys Bitcoin mining and HPC datacenters in the United States, Bhutan, Norway, Canada, Malaysia, and Ethiopia. About the role We are seeking a Technical Project Manager to drive the day-to-day delivery rhythm of Bitdeer's AI platform, working with the engineering team leaders and system architects to turn the platform-wide roadmap into a concrete, trackable execution plan. The AI platform spans multiple product lines and workstreams — Model-as-a-Service (MaaS), Managed Kubernetes, and the shared infrastructure, security, and billing services beneath them — and needs a dedicated owner for delivery across all of them. This role defines milestones alongside the architects, keeping epics and tickets current and correctly linked, surfacing blockers before they slip a release, and turning raw engineering status into clear, decision-ready updates for stakeholders. The person who thrives here is equally comfortable in the details of a sprint board and in a roadmap conversation with an architect, stays organized without prompting, communicates plainly across technical and non-technical audiences, and treats a stale ticket or missed dependency as something to chase down, not ignore. What you will be responsible for: Delivery Timeline Planning : Partner with the engineering team leaders and system architects to translate the platform roadmap across both product lines — MaaS (new model onboarding, inference API features, fine-tuning pipelines) and Managed Kubernetes (cluster provisioning, console, infrastructure-as-code) — into phased delivery timelines. Break architectural milestones into sprint-sized increments across the platform engineering teams. Continuously reforecast dates as scope or dependencies shift, and flag schedule risk to leadership before it becomes a missed deadline. Jira Ticket and Backlog Hygiene : Own the health of the Jira workspace for the AI platform build-out, ensuring epics, stories, and tasks are correctly scoped, estimated, linked, and assigned across frontend, QA, release engineering, security, integrations, performance, and documentation. Audit boards regularly for stale, duplicate, or orphaned tickets, and enforce consistent labeling and workflow states so reported status reflects real progress rather than board drift. Cross-Workstream Dependency Tracking : Map dependencies between the workstreams across MaaS, Managed Kubernetes, and shared platform components, such as a model integration blocked on a security review, a console release blocked on performance sign-off, or a billing or identity change that both product lines depend on, and maintain a live dependency register. Proactively chase owners for at-risk handoffs, escalate blockers a single team cannot resolve alone, and coordinate sequencing so parallel workstreams converge on the same release date. Progress Reporting and Stakeholder Communication : Produce regular, accurate status reports and dashboards that translate raw Jira and engineering data into a clear picture of what shipped, what is at risk, and what decisions are needed. Run or support standups, sprint reviews, and milestone check-ins, ensuring the team leaders, architects, and broader stakeholders always have an honest, current view of AI platform delivery progress. Process and Tooling Impr

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