Technical Program Manager, Platform
Technical Program Manager partnering with engineering teams to accelerate the Scale Generative AI Platform. Own end-to-end execution of infrastructure initiatives, manage cross-functional dependencies, mitigate risks in large-scale GenAI systems, and drive adoption metrics for orchestration, model serving, and APIs. Requires 5+ years TPM/PM/SE experience with 3+ years in platform infrastructure.
About the job
Key Responsibilities
- Lead strategic planning and high-velocity execution for SGP core capabilities (orchestration layers, model serving, APIs). Manage features from technical scoping and architecture design through production launch.
- Drive execution and manage complex technical dependencies across systems engineering, Core ML, Research, and Product teams to deliver unified SGP capabilities with architectural consistency.
- Translate complex infrastructure metrics (LLM inference optimization, GPU utilization, compute orchestration) into actionable roadmaps. Map demands like multi-tenancy, data privacy, and isolation into platform features.
- Proactively identify, track, and mitigate technical risks unique to massive-scale GenAI infrastructure and global SGP deployments.
- Establish lightweight agile processes that empower engineers to ship fast without breaking core systems. Define and enforce clear SLOs and performance benchmarks.
- Track and report on SGP adoption metrics, system reliability, delivery forecasts, and engineering bottlenecks directly to executive leadership.
Minimum Qualifications
- 5+ years of experience as a Technical Program Manager, Product Manager, or Software Engineer, with a proven track record of having built and shipped technical products or platforms from scratch (e.g., internal cloud infrastructure, developer APIs, distributed systems, or ML platforms).
- 3+ years of dedicated experience managing programs focused directly on core engineering infrastructure, cloud-native ecosystems (AWS/GCP), container orchestration (Kubernetes), or distributed systems.
- Foundational understanding of the infrastructure required for the Generative AI lifecycle, including high-throughput data pipelines, GPU/CPU cluster utilization, or model training/evaluation setups.
- Proven track record of presenting to and influencing executive-level stakeholders, with the ability to translate complex technical/architectural challenges into clear business impacts.
- Advanced proficiency with iterative development methodologies and modern project management tooling (Linear, Jira, etc.) applied to foundational infrastructure environments.
Nice-to-Have Qualifications
- Strong software engineering fundamentals, with prior professional experience as a Software Engineer, DevOps Engineer, or Data Developer before transitioning into program management.
- Proven success driving the internal adoption of technical platforms, SDKs, or APIs across disparate, fast-moving product lines.
- Direct experience working with large-scale data quality pipelines, distributed vector databases, or specialized AI inference engines (e.g., Triton, Ray).
Skills
Technical Program Management, Kubernetes, AWS, GCP, Distributed Systems, Llm Inference, Gpu Utilization, Jira, Linear, Generative Ai Infrastructure, Cloud Native, Agile Methodologies
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