Technical Program Manager; AI Infrastructure

Requirements

• 5–8 years of experience in program management, technical operations, or product execution in a fast-moving, technical environment
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• Proven ability to lead complex, multi-team initiatives spanning engineering and infrastructure systems
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• Strong communication skills with the ability to bridge technical and non-technical stakeholders
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• Experience working closely with engineering teams on distributed systems, cloud infrastructure, or platform development
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• Ability to break down ambiguous problem spaces into clear plans and drive alignment across teams
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• Analytical mindset with experience using data to inform decisions and measure impact
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• Strong ownership and execution mindset, with the ability to manage multiple priorities simultaneously

• We’re hiring a Program Manager, AI Infrastructure to lead high-impact programs that power Character.
  
  AI’s model development and serving systems at scale
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• In this role, you’ll partner closely with engineering, research, and product teams to shape infrastructure strategy, align roadmaps, and drive end-to-end execution for critical initiatives across training, evaluation, and inference
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• You’ll help ensure our systems are reliable, efficient, and capable of supporting rapid iteration as we scale AI experiences to millions of users
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• This role is a good match for someone who thrives in technically complex environments, enjoys bringing structure to ambiguous problem spaces, and can drive alignment across deeply cross-functional teams
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• You’ll often operate at the intersection of research and production, helping teams navigate tradeoffs between speed, quality, and reliability
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• You should be comfortable influencing without authority, anticipating risks early, and keeping large, interdependent efforts moving forward
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• Lead planning and execution of major AI infrastructure initiatives spanning training pipelines, data systems, model evaluation, and inference/serving
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• Build structures that keep teams aligned: scopes, goals, requirements, timelines, risks, and success metrics
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• Partner with engineering, research, and product to translate model and product needs into infrastructure roadmaps and priorities
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• Drive cross-functional accountability and communication across teams working on tightly coupled systems
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• Track key infrastructure metrics (e.g., reliability, latency, throughput, cost efficiency) and define reporting that surfaces progress and risk
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• Identify bottlenecks in infrastructure workflows and lead efforts to improve tooling, automation, and developer velocity
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• Support capacity planning and resource allocation to ensure infrastructure scales with model and product growth
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• Develop repeatable frameworks and operational patterns that improve execution quality across infrastructure programs
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• Serve as a strategic partner to leaders on prioritization, sequencing, and tradeoffs across infrastructure investments
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• Work closely with AI cloud providers and serve as the primary bridge between internal engineering teams and external partnership efforts
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• Technical understanding of GPU clusters, AI accelerator chips, and cloud providers to effectively evaluate requirements and guide infrastructure decisions