Product Manager, AI & Applications

The role

The Senior AI Product Manager serves as the product-definition, delivery-planning, and release-execution lead for the AI & Applications team. This person will convert strategic priorities into an executable, sprint-based product roadmap for AI infrastructure and applications.

What you will do

• Translate strategic priorities into a prioritized product portfolio, quarterly roadmap, release plan, and sprint-level delivery plan.
• Establish and maintain a single source of truth for product scope, roadmap priorities, and delivery health.
• Lead product-definition activities including developing problem statements, feature briefs, and product requirements.
• Break strategic initiatives into sequenced epics, features, stories, and technical milestones.
• Own roadmap refinement and sprint-readiness processes.
• Coordinate planning across AI engineers, application engineers, DevOps, and other stakeholders.
• Identify, document, manage, and drive resolution of dependencies between teams and systems.
• Maintain an integrated release plan across all relevant workstreams.
• Define and operate release gates for development completion and production approval.
• Run a regular product-delivery operating cadence including backlog refinement and sprint planning.

Required qualifications

• 5+ years of experience in product management, technical program management, delivery management, release management, solutions architecture, engineering management, or a comparable technical leadershi
• Proven experience working directly with an engineering or product leader to establish delivery discipline and roadmap transparency.
• Demonstrated ownership of complex, multi-team technical product roadmaps.
• Strong experience with agile product delivery, including backlog management, sprint planning, and release planning.
• Practical experience building and managing integrated delivery plans, dependency maps, and executive-level status reporting.
• Strong technical understanding of AI/ML platforms and applications, including training, fine-tuning, inference, model serving, benchmarking, performance optimization, data pipelines, RAG, and agentic
• Familiarity with GPU-accelerated infrastructure, Kubernetes, Slurm or comparable workload schedulers, distributed training, multi-tenant resource management, and AI inference systems.
• Understanding of product and engineering success measures such as feature adoption, release quality, and GPU utilization.
• Experience creating product requirements, technical specifications, acceptance criteria, and release checklists.
• Strong analytical ability to turn technical constraints and stakeholder feedback into execution decisions.
• Excellent written, verbal, and stakeholder-management skills.

About the company

Firmus Technologies is a global leader pioneering the development and operation of efficient AI infrastructure across Asia Pacific. The company designs, builds, and operates AI Factories using a model-to-grid technology approach.