Senior Applied Intelligence Platform Engineer to implement AI governance controls using MLOps, MLflow, Databricks, and NIST AI RMF
S.I. Systems Ltd. Senior Applied Intelligence Platform Engineer to implement AI governance controls using MLOps, MLflow, Databricks, and NIST AI RMF
Summary
Contract senior platform engineer role (via S.I. Systems) for a public-sector client in downtown Toronto, operationalizing AI governance through technical controls. Day to day involves building MLOps/LLMOps pipelines, MLflow lineage and experiment tracking, and automated guardrails using Databricks, CI/CD, Terraform, and GitHub Actions.
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
AI may be used in evaluating candidates.
This posting is for an existing vacancy.