Job Description

CGI Canada is looking for an experienced Lead Data Scientist to drive the design and deployment of the AgentOps Control Plane on Google Cloud Platform (GCP) a pioneering initiative enabling intelligent, policy-aware collaboration between AI agents in enterprise environments. You'll lead a talented team building the intelligence and observability layers of AgentOps, integrating Agentspace as the foundation for distributed, adaptive AI systems. This role combines hands-on technical leadership with strategic vision applying advanced data science, machine learning, and MLOps practices to shape the future of enterprise AI orchestration.

Your future duties and responsibilities

Lead architecture and model development for AgentOps' intelligence layer enabling adaptive decisioning, agent telemetry, and behavioral analytics. Deploy scalable ML workloads using native GCP services such as Vertex AI, BigQuery, Dataflow, Firestore, and GKE. Integrate with Agentspace, defining how AI agents share context, policies, and execution artifacts in a controlled runtime environment. Develop and operationalize predictive models that enhance agent orchestration, routing, and observability. Implement AI governance, monitoring, and explainability pipelines within the control plane using GCP-native observability and security tools. Collaborate across disciplines data engineering, cloud architecture, and AI operations to align technical outcomes with business priorities. Mentor and guide data scientists and ML engineers, fostering best practices in MLOps, experimentation, and cloud-scale deployment.

Required qualifications to be successful in this role

8+ years of experience in applied data science or machine learning. Proven track record leading ML or AI platform deployments on Google Cloud Platform (Vertex AI, BigQuery, Dataflow, Firestore, GKE). Strong proficiency in Python, TensorFlow, PyTorch, and SQL. Experience working with or designing agent-based systems (e.g., Agentspace, LangGraph, Semantic Kernel, or similar). Solid understanding of cloud-native architectures, CI/CD for MLOps, and containerized workloads. Strong collaboration and communication skills capable of interfacing with both executive stakeholders and engineering teams.



Preferred Skills



Familiarity with multi-agent orchestration frameworks and adaptive AI systems. Experience developing AI observability, policy enforcement, or telemetry analytics pipelines. Background in AI governance, explainability, or trust and safety frameworks.


Join us to lead a team at the forefront of enterprise AI control and orchestration powered by Agentspace and Google Cloud.



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