Senior Tech Program Lead: AI/ML & App Delivery

Photon; Paris; Hybride; EUR 90 000 - 130 000; Plein temps

Résumé du poste

Photon is seeking a Senior Technical Project Manager to own end-to-end delivery of complex, multi-team programs spanning application engineering and data/AI/ML platforms. You will connect engineering, product, data science, architecture, QA, and business stakeholders to turn ambiguous goals into sequenced, resourced plans and drive them to production.

This hands-on role requires reading architectures, challenging estimates, and making credible trade-offs.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8–12 years of total experience with 4–5 years in technical software delivery programs.
• Hands-on experience delivering both application/product engineering and data/AI/ML initiatives.

Responsabilités

• Own end-to-end delivery for two or more concurrent technical programs.
• Build and maintain integrated delivery plans with milestones and entry/exit criteria.
• Identify and manage cross-team dependencies; drive resolution before slips.
• Run structured risk and issue management with mitigation options.
• Manage release readiness, go/no-go reviews, and post-launch stabilization.
• Partner with Engineering Managers and Product Owners for Agile squads.
• Review designs to ensure non-functional requirements are planned, not retrofitted.
• Track debt and its impact on delivery timelines.
• Coordinate data/AI/ML initiatives across data engineering/science/MLOps teams.

Connaissances

Leadership

Stakeholder management

Agile delivery

Risk management

Delivery planning

Executive communication

Formation

Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field

Outils

Jira

Confluence

Azure DevOps

MS Project

Description du poste

Photon is seeking a Senior Technical Project Manager to own end-to-end delivery of complex, multi-team programs spanning application engineering and data/AI/ML platforms. You will connect engineering, product, data science, architecture, QA, and business stakeholders to turn ambiguous goals into sequenced, resourced plans and drive them to production.

This hands-on role requires reading architectures, challenging estimates, and making credible trade-offs.