Senior Applied Intelligence Platform Engineer to implement AI governance controls using MLOps, MLflow, Databricks, and NIST AI RMF

S.I. Systems Ltd.; Toronto; On-site; CAD 130,000 - 170,000; Full time

Benefits offered by this job

Office in Downtown Toronto

Job summary

S.I. Systems Ltd. seeks a Senior Applied Intelligence Platform Engineer to implement AI governance controls via MLOps, MLflow, Databricks, and NIST AI RMF.

This hands-on role supports enterprise AI initiatives across Microsoft Foundry, Databricks, Copilot Studio, and mixed-model AI environments. The candidate will translate governance requirements into technical controls, build reusable patterns and guardrails, and collaborate with AI governance, enterprise architecture, cybersecurity, privacy,

Qualifications

• 7+ years in AI engineering, ML, platform, software, or cloud engineering.
• Hands-on MLOps and LLMOps implementation for production AI/ML solutions.
• Enterprise-scale model lifecycle management and AI governance control implementation.

Responsibilities

• Translate AI governance requirements into technical controls and patterns.
• Implement automated guardrails, policy enforcement, and governance evidence.
• Build and maintain pipelines for development, evaluation, deployment, monitoring, and lifecycle management.
• Implement lineage, experiment tracking, and reproducibility using MLflow.
• Support deployment, testing, troubleshooting, and recovery of AI services.
• Create technical runbooks, documentation, and support procedures.
• Collaborate with AI Governance, EA, Privacy, Security, and platform teams.

Skills

AI engineering

MLOps

LLMOps

Model lifecycle management

CI/CD

GitHub Actions

Terraform

Spacelift

Jenkins

Cloud/Platform engineering

Education

Bachelor's degree in a related technical field

Tools

Databricks

MLflow

Job description

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 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.