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Open nowPosted 41 days ago

Product Owner, AI Factory

cogeco46 open roles

Where
Burlington ON
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Your applicationOpen nowProduct Owner, AI Factorycogeco · Burlington ON

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. cogeco postings stay open a median of 7 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.7%14 days
  5. 35.6%30 days
  6. 58.0%60 days
This job: posted 41 days ago

cogeco median: 7 days open

The posting

Our culture lifts you up—there is no ego in the way. Our common purpose? We all want to win for our customers. We aim to always be evolving, dynamic, and ambitious. We believe in the power of genuine connections. Each employee is a part of what makes us unique on the market: agile and dedicated.

Time Type:

Regular

Job Description :

Product Owner, AI Factory

POSITION SUMMARY

The Product Owner (PO) – AI Factory Squad is a pivotal technical product leader responsible for defining, industrializing, and executing the product vision and roadmap for the enterprise AI Factory platform. Operating within the Enterprise IT & Architecture Crew, this role drives the operational backbone (MLOps, LLMOps, AgentOps) that enables cross-functional business squads to repeatedly, safely, and cost-effectively build, deploy, and scale high-value AI models and Agentic AI solutions.

Acting as the central bridge between enterprise architecture, data science, engineering, and business stakeholders, the Product Owner establishes an end-to-end platform blueprint. The PO champions self-serve capabilities, reusable components (e.g., Model Context Protocol [MCP] frameworks, tool belts, API gateways, certified skill libraries, semantic knowledge graphs), and automated CI/CD deployment pipelines to compress AI delivery time from months to days. Furthermore, the role enforces enterprise AI governance, Trust & Safety standards, AISecOps, and token unit economics (FinOps) to ensure all AI initiatives are scalable, secure, compliant, and directly tied to measurable business outcomes.

KEY RESPONSABILITIES

1. Product Vision, Strategy & Roadmap Execution

  • Define, prioritize, and execute the product vision and multi-quarter roadmap for the AI Factory Platform, serving as the central hub for the enterprise Agentic AI hub-and-spoke model.
  • Own and manage the squad backlog, translating architectural guidelines, enterprise strategic goals, and cross-squad AI requirements into clear user stories, acceptance criteria, and technical deliverables.
  • Deliver self-serve platform capabilities (such as the Service Catalog) to accelerate onboarding across internal squads and foster democratization of AI development.

2. MLOps, LLMOps & Agentic Operations (AgentOps) Industrialization

  • Drive the industrialization of end-to-end automated CI/CD pipelines for AI models and autonomous agents, targeting rapid code-commit-to-production cycles .
  • Lead the product roadmap for advanced multi-agent orchestration, arbitration platforms, tracing tools, and automated evaluation frameworks using Golden Datasets.
  • Standardize and catalogue reusable platform assets, API tool belts, certified agent skill libraries, and semantic data/knowledge graph layers for widespread reuse across squads

3. AI Governance, Trust & Safety, and Security (AISecOps)

  • Embed lightweight, continuous architectural guardrails, data access controls, and compliance mechanisms (privacy, security, model risk) directly into the platform pipeline.
  • Implement robust observability, model lineage, and monitoring frameworks to maintain high availability (99.9%) and minimize hallucination rates (< 5% on verified benchmarks).
  • Partner with InfoSec and Enterprise Architecture to enforce unified AISecOps standards and MCP tool registry protocols across all AI deployments.

4. FinOps & Token Unit Economics

  • Establish enterprise-wide FinOps controls, tracking token attribution and implementing optimization best practices to prevent runaway LLM costs across consuming squads.
  • Monitor Total Cost of Ownership (TCO) and unit economics for foundational models, cloud infrastructure (e.g. GCP), and external API consumption, aligning spend with tangible business value.

5. Cross-Functional Stakeholder Alignment & Enablement

  • Act as the strategic liaison between Enterprise Architecture, Infrastructure, Data & Analytics, Security, and consuming business squads.
  • Partner with consuming squads to facilitate smooth onboarding to the AI Factory platform, driving adoption while maintaining clear operational boundaries (empowering squads while AI Factory owns the core platform backbone).

ESSENTIAL QUALIFICATIONS

ACADEMIC TRAINING

  • Bachelor's or Master’s degree in Computer Science, Information Technology, or a related field.

WORK EXPERIENCE

  • Minimum of 8+ years of progressive experience in Information Technology, Software Engineering, or Data Platforms.
  • At least 3–5+ years in a Product Owner, Technical Product Manager, or Product Lead role leading technical platforms, or cloud infrastructure solutions
  • Exposed and experienced to MLOps/LLMOps and data engineering.
  • Demonstrated track record of building and scaling platform products from concept to enterprise-wide adoption using Agile/Scrum methodologies.
  • Hands-on experience with modern AI/ML lifecycle management, Large Language Model (LLM) architectures, and Agentic AI frameworks.
  • Experience in telecom or large enterprise environments with complex BSS/OSS or decoupled enterprise system integrations is an asset.
  • Experience managing platform unit economics, cloud cost optimization (FinOps), and cloud infrastructure budgets (especially Google Cloud Platform / GCP).

.

SPECIFIC COMPETENCIES

  • AI & Agentic Technologies: Strong understanding of generative AI, LLM orchestration/arbitration, Model Context Protocol (MCP), RAG, semantic layers/knowledge graphs, and automated agent evaluation.
  • MLOps/LLMOps Tooling: In-depth familiarity with CI/CD for ML/AI, containerization (Docker, Kubernetes), model registries, feature stores, and observability/tracing tools.
  • Cloud & Platform Architecture: Solid grasp of cloud-native architectures (GCP preferred), API management, event-driven architecture, and secure microservices design.
  • Agile & Product Management: Proven expertise in backlog prioritization, stakeholder management, OKR tracking, user journey mapping, and value realization.
  • Communication & Collaboration: Exceptional communication and leadership skills with the ability to bridge deep technical details and executive business outcomes.
  • Bilingualism: Bilingual in English and French is an asset.

Location :

Burlington, ON

Company :

Cogeco Connexion Inc

At Cogeco, we know that different backgrounds, perspectives, and beliefs can bring critical value to our business. The strength of this diversity enhances our ability to imagine, innovate, and grow as a company. So, we are committed to doing everything in our power to create a more diverse and inclusive world of belonging.

By creating a culture where all our colleagues can bring their best selves to work, we’re doing our part to build a more equitable workplace and world. From professional development to personal safety, Cogeco constantly strives to create an environment that welcomes and nurtures all. We make the health and well-being of our colleagues one of our highest priorities, for we know engaged and appreciated employees equate to a better overall experience for our customers.

If you need any accommodations to apply or as part of the recruitment process, please contact us confidentially at [email protected]

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