Technical Program Manager, Enterprise
Leads enterprise technical programs across engineering, product, and executive stakeholders, managing delivery, dependencies, risks, and adoption. Requires 5+ years of technical program or leadership experience, infrastructure or distributed-systems exposure, and foundational generative AI knowledge.
About the job
Responsibilities
- Own the strategic planning, scheduling, and execution of multiple enterprise-grade programs, ensuring on-time delivery against product goals.
- Run weekly cross-functional syncs, surface blockers, and drive decisions.
- Manage complex dependencies and technical communication across Platform, Forward Deployed Engineering, and Product teams.
- Translate technical complexity into concise, actionable insights for engineers and executive stakeholders.
- Identify technical risks and architect mitigations for enterprise AI deployment.
- Modernize and scale agile execution frameworks using tools such as Jira and Linear.
- Define, track, and report program health metrics, delivery forecasts, and engineering bottlenecks to executive leadership.
Requirements
- 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.
- 2+ years of experience managing programs focused on engineering infrastructure, platform services, or distributed systems.
- Foundational understanding of the generative AI lifecycle, including LLM utilization for structured downstream tasks, model fine-tuning, and performance evaluation.
- Proven ability to present to and influence executive-level stakeholders and translate technical challenges into business impacts.
- Advanced proficiency with iterative development methodologies and modern project management tools.
- Strong interest in modern machine learning, generative AI practices, and infrastructure.
Nice-to-haves
- Prior professional experience as a software engineer or data developer.
- Experience driving adoption of technical platforms, SDKs, or APIs across product lines or business units.
- Familiarity with data quality pipelines, LLM-as-a-judge evaluation frameworks, or automated RLHF systems.
Skills
Generative AI, LLMs, Model Fine-Tuning, Machine Learning, Distributed Systems, Platform Services, Jira, Linear, Agile Methodologies, Software Engineering, Data Pipelines, RLHF, Api Adoption
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