Technical Program Manager (Enterprise)

Join Scale AI as a Technical Program Manager (Enterprise) and play a crucial role in driving the strategic alignment and execution of our most critical enterprise initiatives. You will manage timelines, milestones, risks, and dependencies across technical deliverables, serving as the core communication backbone between engineering, product, and executive leadership. This high-leverage, technical leadership role requires a strong understanding of the Generative AI lifecycle and a proven track record of influencing executive-level stakeholders.

• Assurer l'exécution opérationnelle et la livraison de notre travail technique en gérant les délais, les jalons, les risques et les dépendances.
• Diriger l'alignement stratégique et l'exécution de bout en bout de nos initiatives critiques pour l'entreprise, en possédant la livraison du programme depuis la définition initiale jusqu'à l'adoption à l'échelle de l'entreprise.
• Servir de lien de communication central entre l'ingénierie, le produit et la direction exécutive, en traduisant la complexité technique en stratégies d'exécution claires.
• Masterful Communication: Proven track record of presenting to and influencing executive-level stakeholders, with the ability to translate complex technical challenges into clear business impacts
• Execution Excellence: Advanced proficiency with iterative development methodologies and modern project management tooling (Jira, Linear, etc.)
• 5+ Enterprise-Scale Experience: 5+ years of experience as a Technical Program Manager or in a technical leadership role managing complex, large-scale software engineering or machine learning development projects
• Engineering Domain Expertise: 2+ years of dedicated experience managing programs focused directly on core engineering infrastructure, platform services, or distributed systems
• Growth Mindset: An insatiable appetite for learning and deeply engaging with modern ML/GenAI practices and infrastructure
• AI/ML Literacy: Strong foundational understanding of the Generative AI lifecycle, including LLM utilization for structured downstream tasks, model fine-tuning, and performance evaluation
• Engineering Roots: Strong software engineering fundamentals, ideally with prior professional experience as a software engineer or data developer before transitioning into program management
• Platform Adoption Track Record: Proven success driving the internal adoption of technical platforms, SDKs, or APIs across disparate product lines or independent business units
• Data-Centric AI Familiarity: Direct experience working with data quality pipelines, LLM-as-a-judge evaluation frameworks, or automated RLHF systems