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 workplace 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. #J-18808-Ljbffr

📌 Senior Applied Intelligence Platform Engineer to implement AI governance controls using MLOps, MLflo (Toronto)
🏢 S.I. Systems
📍 Toronto