Product Owner

About Publicis Re:Sources

Publicis Re:Sources is the backbone of Publicis Groupe, the world’s most valuable agency group. We are the only full-service, end-to-end shared service organization in the industry, enabling Groupe agencies to do what they do best: innovate and transform for their clients. Formed in 1998 as a small team to service a few Publicis Groupe firms, Publicis Re:Sources has grown to 5,000+ employees in over 66 countries. We provide technology solutions and business services including finance, accounting, legal, benefits, procurement, tax, real estate, treasury and risk management. We continually transform to keep pace with our ever-changing communications industry and thrive on a spirit of innovation felt around the globe. Learn more about Publicis Re:Sources and the Publicis Groupe agencies we support at http://www.publicisresources.com/.

Job Title: Technical Product Owner – AI/ML or Cloud or Data Platforms

Experience

Location

Employment Type:

Role Overview:

We are seeking a Technical Product Owner (TPO) who combines strategic business ownership with strong technical understanding of AI/ML or data or cloud ecosystems

You will define the vision, roadmap and measurable outcomes for data-driven/ Cloud and AI-powered products while also owning the backlog, technical decisions and delivery of platform capabilities.

This role demands an ability to bridge business strategy and engineering execution ensuring every technical initiative drives tangible business impact and adheres to enterprise standards.

Key Responsibilities

A. Business Product Ownership (Strategic PO Responsibilities)

• Define and communicate the product vision, roadmap and business outcomes for AI/ML/ Cloud or data platform initiatives.
• Align the AI/ML product strategy with organizational OKRs, ROI goals and digital transformation objectives.
• Partner with business leaders to translate high-level use cases (e.g., personalization, forecasting, anomaly detection) into actionable technical features.
• Define value hypotheses, track business KPIs and report impact on efficiency, automation and customer experience.
• Prioritize investments based on business value risk and readiness.
• Champion Responsible AI and ethical data use as part of business governance.

B. Tactical / Technical Product Ownership (Execution-Level Responsibilities)

• Own the backlog including epics, user stories, data pipelines, model lifecycle features and infrastructure capabilities.
• Collaborate with data engineers, ML engineers and cloud architects to design scalable solutions for data ingestion, training and inference.
• Define technical acceptance criteria for ML features, APIs and pipelines.
• Ensure strong alignment between data availability, model readiness and deployment environments.
• Partner with the MLOps team to standardize model deployment, monitoring and retraining processes.
• Contribute to architecture discussions, data platform evolution and reusable component development.
• Manage sprint ceremonies, backlog grooming and release planning with engineering teams.
• Track progress via technical KPIs (e.g., model latency, data quality SLAs, deployment frequency).

C. Technical Environment / Stack Awareness

• Domain:

  Key Tools / Platforms

• Cloud Platforms:

  Azure (ADF, Synapse, ML Studio), AWS (Glue, Redshift, SageMaker), GCP (BigQuery, Vertex AI)

• Data Engineering:

  Databricks, Apache Spark, Airflow, Kafka, Delta Lake, Snowflake

• MLOps & Deployment:

  MLflow, Kubeflow, Docker, Kubernetes, DVC, GitHub Actions

• AI/ML Frameworks:

  Scikit-learn, PyTorch, TensorFlow, Hugging Face (conceptual)

• GenAI & LLM Ecosystem:

  LangChain, OpenAI API, Vertex AI, Azure OpenAI, Pinecone, FAISS

• Analytics & BI:

  Power BI, Tableau, Looker

• Governance & Monitoring:

  Data Catalog, Lineage, SHAP, LIME, Model Monitoring

D. Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science or Engineering.
• 10+ years of experience in product ownership, technical program management or AI/ML delivery.
• Strong knowledge of AI/ML model lifecycle, data pipelines and cloud-native architecture.
• Proven ability to balance business priorities with technical feasibility.
• Experience in Agile / Scrum environments writing epics, managing sprints and working with cross-functional teams.
• Exposure to LLM/GenAI, data modernization or AI platform products preferred.

E. Certifications (Preferred)

• Certified Scrum Product Owner (CSPO) or Professional Scrum Product Owner (PSPO).
• Microsoft / AWS / GCP certifications in AI, Data or Cloud.
• Any recognized AI Product Management or Responsible AI certification.

F. Soft Skills

• Strong communication and stakeholder management able to engage with business, engineering and data science leaders.
• Analytical mindset; capable of linking technical metrics to business KPIs.
• Skilled in prioritization, trade-off decisions and dependency management.
• Growth mindset and adaptability to emerging AI technologies.

*Please apply only if you are an immediate joiner or join within a week*