Key Responsibilities
Lifecycle & Platform Delivery: 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.
Cross-Functional GenAI Alignment: Drive execution and manage complex technical dependencies across systems engineering, Core ML, Research, and Product teams to deliver unified SGP capabilities with architectural consistency.
Technical Translation & Requirements: 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.
Risk & Dependency Mitigation: Proactively identify, track, and mitigate technical risks unique to massive-scale GenAI infrastructure and global SGP deployments, maintaining momentum despite fast-evolving AI frameworks.
Developer Velocity & Operational Excellence: Establish lightweight agile processes that empower engineers to ship fast without breaking core systems. Define and enforce clear SLOs and performance benchmarks to guarantee production-grade reliability for clients.
Metrics-Driven Adoption: Track and report on SGP adoption metrics, system reliability, delivery forecasts, and engineering bottlenecks directly to executive leadership to ensure the platform scales responsibly.
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).
Compensation & Benefits
Compensation packages include base salary, equity, and benefits. Base salary range for this full-time position in San Francisco, New York, Seattle: $211,200—$264,000 USD. Scale employees in eligible roles are also granted equity based compensation. Benefits include comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. This role may be eligible for additional benefits such as a commuter stipend.