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 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

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

Disclaimer

AI may be used in evaluating candidates.

This posting is for an existing vacancy.

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