Position Overview

This role leads company-wide AI/ML infrastructure initiatives at a high-growth tech scale-up, driving strategic programs that bridge engineering, data science, and product management. The Senior Technical Program Manager is central to delivering enterprise-grade ML platforms, enabling robust, scalable, and compliant AI solutions for global markets.

Key Responsibilities

• Orchestrate planning, scheduling, and execution of technical programs for AI/ML and data infrastructure across multiple business units.
• Oversee the full lifecycle of machine learning model development—from data ingestion, governance, and training in distributed environments, to deployment and continuous monitoring.
• Collaborate with MLOps, data engineering, and cloud infrastructure teams (including IBM Cloud) to deliver robust ML systems that meet stringent performance, security, and regulatory requirements.
• Act as the primary interface between technical teams and executives, translating project updates and technical risk into business impact.
• Champion responsible AI practices, ensuring all deliverables meet standards for explainability, bias mitigation, and GDPR compliance.
• Drive cross-functional alignment among global teams, vendors, and C-level partners, managing OKRs and delivering measurable outcomes.
• Evaluate and implement next-generation LLMs, transformer architectures, and AI tooling ecosystems (Kubeflow, MLflow, SageMaker, Vertex AI, Ray, Weights & Biases).
• Monitor and optimize cloud infrastructure costs, particularly around GPU resource management for distributed ML workloads.
• Support agile, product-led experimentation and iterative development cycles.

Ideal Qualifications

• At least 10 years’ experience managing complex technology programs, with 3+ years dedicated to AI/ML or data infrastructure domains.
• Demonstrated delivery of scalable, enterprise ML platforms, preferably within regulated sectors such as fintech or healthcare.
• Deep knowledge of model lifecycle management, ML observability, compliance, and data governance.
• Hands-on familiarity with MLOps, cloud architecture, and relevant AI frameworks and platforms.
• Experience managing stakeholder relationships at the executive level and coordinating globally-dispersed project teams.

Core Soft Skills

• Outstanding communication skills for translating complex technical topics to varied audiences.
• Exceptional stakeholder management and influencing capabilities, driving consensus across disciplines.
• Strong project leadership and organizational skills, with a focus on delivering clear business value.

Reporting Structure

• Reports directly to the Head of Engineering or VP of Product.
• Leads technical program teams and collaborates with product, data science, compliance, and cloud infrastructure groups.

Success Metrics

• On-time, on-budget delivery of prioritized AI/ML infrastructure programs.
• Stakeholder satisfaction and measurable impact on product and business KPIs.
• Continuous improvement in system reliability, governance, and regulatory compliance.
• Effective implementation of responsible, explainable, and unbiased AI solutions at scale.