Generative and Agentic AI Data Security Architect

Generative and Agentic AI Data Security Architect Quebec City, QC (Hybrid) Full time Job Summary Our team conducts research and development (R&D) work to meet the needs of the Department of National Defence (DND) and the Canadian Armed Forces (CAF). The projects focus on innovative digital solutions combining software development, systems integration, modern infrastructure, and generative artificial intelligence.

As part of accelerating our artificial intelligence initiatives, we want to develop a new generation of applications based on Agentic AI. These solutions go beyond traditional conversational assistants by allowing intelligent agents to analyze data, reason, make decisions, orchestrate complex workflows, and interact with multiple enterprise systems autonomously and securely.

We are looking for someone to fill a Generative and Agentic AI Data Security Architect role to join our team in Quebec, specializing in knowledge management. Our multidisciplinary team focuses on data collection, transformation, and enrichment. Our projects involve defining and deploying automated processing chains to make data accessible to users. With the support of our data scientists, the team designs, trains, and integrates artificial intelligence models, including Generative AI (GenAI) based on Large Language Models (LLMs), to improve data analysis. Our team also uses AI and machine learning (ML) concepts to increase analysis efficiency.

Essential Functions The incumbent of the C2 Data Security Architect position is responsible for defining, implementing, and governing the data and operations security architecture for next-generation data fusion and artificial intelligence solutions in the context of a C2IS (Command and Control Information System). In collaboration with data, AI, cybersecurity, and development teams, this person will ensure the application of Data Centric Security (DCS) principles, the securing of Generative AI and Agentic AI platforms, and the implementation of robust compliance, auditability, and traceability mechanisms. They will also contribute to the evolution of DevSecOps, MLOps, and LLMOps practices on Google Cloud to ensure the secure, reliable, and operational deployment of critical AI capabilities in defense and national security environments.

The incumbent of the Generative and Agentic AI Data Security Architect position will play a key role in the design, development, and production release of intelligent platforms and applications integrating language models (LLMs), multi-agent architectures, RAG (Retrieval-Augmented Generation) engines, orchestration tools, and next-generation cloud services. The person occupying this position will contribute to strategic projects aimed at improving operational efficiency, decision support, and the automation of complex processes in environments where security, reliability, and traceability are essential. This person must be autonomous, curious, and comfortable in an R&D context where needs evolve rapidly. They will work with architects, developers, and artificial intelligence specialists to transform technical concepts into concrete, demonstrable, and scalable solutions.

This person is part of a multidisciplinary team. A strong team spirit and teamwork capabilities are mandatory. The ideal person is therefore able to demonstrate cross-functional skills that would facilitate the transfer of work done to all stakeholders involved. Therefore, good communication skills are required.

Responsibilities of the Generative and Agentic AI Data Security Architect:

Define data and operations security architecture for data fusion, Generative AI, and Agentic AI platforms.

Design and enforce Data Centric Security (DCS), Zero Trust, and Security by Design principles across the entire data lifecycle.

Ensure the application of compliance policies during the ingestion, analysis, fusion, and sharing of multi-source data.

Design governance, traceability, provenance, auditability, and data lineage mechanisms for data, models, and AI agents.

Define security architectures for LLM solutions, RAG, multi-agent systems, and generative AI platforms.

Establish security controls and guardrails enabling the safe and explainable use of AI agents in critical environments.

Lead risk management, threat assessment, and compliance activities for AI/ML and cloud solutions.

Design and oversee DevSecOps, MLOps, and LLMOps practices ensuring secure and reproducible deployments.

Collaborate with product, data, AI, cybersecurity, and operations teams to integrate security requirements from design.

Support validation, certification, accreditation, and operational demonstration activities with internal and external stakeholders.

Minimum Requirements

Bachelor's degree in computer science, software engineering, information systems, data science,