# Technical Program Manager, Platform

**Company:** [Scale AI](https://hotfix.jobs/companies/scale-ai)
**Location:** San Francisco, CA, New York, NY
**Role:** Technical Program Management
**Salary:** $211k – $264k/yr
**Experience:** 5+ years
**Skills:** Technical Program Management, Kubernetes, AWS, GCP, Distributed Systems, Jira, Linear, Generative Ai Infrastructure, Cloud-Native Ecosystems, Project Management
**Posted:** 2026-06-04

> Lead strategic planning and execution for Scale's Generative AI Platform infrastructure. Partner with engineering, ML, and product teams to deliver scalable developer tooling and distributed systems from scoping through production adoption.

## Job Description

## 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.

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