Senior Applied Intelligence Platform Engineer to implement AI governance controls using MLOps, MLflow, Databricks, and NIST AI RMF Our public sector client is seeking a Senior Applied Intelligence Platform Engineer (7+ years) to implement AI governance controls using MLOps, MLflow, Databricks, and NIST AI RMF
This hands‑on engineering role supports enterprise AI initiatives across Microsoft Foundry, Databricks, Copilot Studio, and mixed-model AI environments. The position focuses on operationalizing AI governance requirements through technical controls, reusable patterns, automated guardrails, and governance evidence across the AI lifecycle. The successful candidate will collaborate closely with AI Governance, Enterprise Architecture, Cybersecurity, Privacy, and AI platform teams to deploy and support enterprise‑scale AI and machine learning solutions. The role offers exposure to responsible AI implementation, enterprise AI delivery models, and production‑scale MLOps and LLMOps practices.
Contract Term: ASAP to December 24, 2027
In office requirement: 3 days per week downtown Toronto
Must Haves
7+ years in AI engineering , machine learning, platform, software, or cloud engineering
Hands‑on MLOps and LLMOps implementation for production AI and machine learning solutions
Enterprise‑scale model lifecycle management , model operationalization, and AI governance control implementation
Databricks, MLflow, CI/CD, Infrastructure as Code, GitHub Actions, Terraform, Spacelift, or Jenkins
Bachelor's degree in a related technical field, or equivalent practical experience
Nice to Have
Familiarity with NIST AI Risk Management Framework (Govern, Map, Measure, Manage)
Experience implementing RAG and agent‑based solutions
Experience with Microsoft Foundry, Copilot Studio, and mixed‑model AI environments
Experience in financial services, pension, asset management, or another regulated setting




Experience collaborating with Enterprise Architecture, Privacy, Security, and Governance teams
Responsibilities
Translate AI governance requirements into technical controls and implementation patterns
Implement automated guardrails, policy enforcement, and governance evidence across AI platforms
Build and maintain pipelines for development, evaluation, deployment, monitoring, and model lifecycle management
Implement lineage, experiment tracking, and reproducibility using MLflow
Support deployment, testing, troubleshooting, debugging, and recovery processes for AI services
Create technical documentation, operational runbooks, and support procedures
Collaborate with AI Governance, Enterprise Architecture, Privacy, Security, and AI platform teams
Our public sector client is seeking a Senior Applied Intelligence Platform Engineer (7+ years) to implement AI governance controls using MLOps, MLflow, Databricks, and NIST AI RMF
This hands‑on engineering role supports enterprise AI initiatives across Microsoft Foundry, Databricks, Copilot Studio, and mixed‑model AI environments. The position focuses on operationalizing AI governance requirements through technical controls, reusable patterns, automated guardrails, and governance evidence across the AI lifecycle. The successful candidate will collaborate closely with AI Governance, Enterprise Architecture, Cybersecurity, Privacy, and AI platform teams to deploy and support enterprise‑scale AI and machine learning solutions. The role offers exposure to responsible AI implementation, enterprise AI delivery models,



and production‑scale MLOps and LLMOps practices.
Contract Term: ASAP to December 24, 2027
In office requirement: 3 days per week downtown Toronto
Must Haves
7+ years in AI engineering , machine learning, platform, software, or cloud engineering
Hands‑on MLOps and LLMOps implementation for production AI and machine learning solutions
Enterprise‑scale model lifecycle management , model operationalization, and AI governance control implementation
Databricks, MLflow, CI/CD, Infrastructure as Code, GitHub Actions, Terraform, Spacelift, or Jenkins
Bachelor's degree in a related technical field, or equivalent practical experience
Nice to Have
Familiarity with NIST AI Risk Management Framework (Govern, Map, Measure, Manage)
Experience implementing RAG and agent‑based solutions
Experience with Microsoft Foundry, Copilot Studio, and mixed‑model AI environments
Experience in financial services, pension, asset management, or another regulated environment
Experience collaborating with Enterprise Architecture, Privacy, Security, and Governance teams
Responsibilities
Translate AI governance requirements into technical controls and implementation patterns
Implement automated guardrails, policy enforcement, and governance evidence across AI platforms
Build and maintain pipelines for development, evaluation, deployment, monitoring, and model lifecycle management
Implement lineage, experiment tracking, and reproducibility using MLflow
Support deployment, testing, troubleshooting, debugging, and recovery processes for AI services
Create technical documentation, operational runbooks, and support procedures
Collaborate with AI Governance, Enterprise Architecture, Privacy, Security, and AI platform teams
Disclaimer:
AI may be used in evaluating candidates.
This posting is for an existing vacancy.
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📌 Senior Applied Intelligence Platform Engineer to implement AI governance controls using MLOps, MLflo (Ontario)
🏢 S.I. Systems
📍 Ontario