Reporting to the Enterprise Architect, the AI & Cloud Infrastructure Specialist will be responsible for the infrastructure and controls underpinning our internal agentic AI platform, our portfolio of AI services, our enterprise API gateway and our LLMs on Azure AI Foundry, OpenAI and Anthropic.
Principal Duties & Responsibilities:Cloud & AI infrastructure- Design, deploy, and maintain secure, scalable cloud infrastructure supporting AI workloads, including containerized environments, relational and vector databases, object storage, secret management, logging, and application monitoring.
- Architect and manage network services for AI platforms, including virtual networks, private endpoints, DNS, subnets, firewall routing, ingress controls, and cross-service connectivity.
- Develop and maintain Infrastructure as Code (Terraform) templates and deployment pipelines.
AI Gateway & Model Access Management- Manage the enterprise API management layer for AI services, including API publishing, versioning, backend configuration, credential management, and policy enforcement.
- Implement secure authentication and authorization models, including on-behalf-of-flows and shared service identities.
- Publish and maintain AI models, internal tools, third-party services, and enterprise endpoints through the API gateway.
- Troubleshoot and resolve API gateway and connectivity issues.
Model and AI Platform Lifecycle Management- Provision, secure, and administer AI platform environments, ensuring private connectivity, restricted access, and compliance with security standards.
- Manage the complete AI model deployment lifecycle, from provisioning to production operations and ongoing maintenance.
Identity, Access & Secrets Management- Collaborate with Information Security team to design and administer identity and access controls for AI systems, including application registrations, permissions, and delegated access models.
- Manage Key Vaults, credentials, secret inventories, and private endpoint configurations.
- Design and maintain secure mailbox and workload-specific access models for automation and service identities.
Tool & Enterprise Data Integration- Design and manage integrations between AI agents and enterprise systems using the Model Context Protocol (MCP) and related frameworks, connecting platforms such as document management, CRM, matter and deal management, enterprise data, legal research, marketing, and financial systems.
- Collaborate with AI developers, Information Security, and business stakeholders to assess, approve, and implement secure integrations, ensuring appropriate authentication, permissions, and governance.
- Partner with vendors to design integration architectures, address connectivity and authentication challenges, and support the successful deployment of AI-enabled solutions.
Reliability, Observability & Incident Management- Implement and maintain monitoring, logging, diagnostics, custom metrics, and cost-management telemetry across the AI ecosystem.
- Serve as an escalation point for AI platform incidents and service disruptions.
- Conduct root cause analysis and document incident findings and remediation plans.
Education and Experience Requirements: - 8+ years of experience in cloud infrastructure, platform engineering, or DevOps, including hands-on responsibility for production AI, machine learning, or LLM-based solutions.
- Proven experience designing, deploying, securing, and operating cloud environments in regulated and confidentiality-sensitive environments.
- Demonstrated ability to act as a technical subject matter expert, influencing technical teams and senior business stakeholders.
- Experience in a law firm, professional services, financial services, or other regulated industry is considered an asset.
- Familiarity with enterprise business systems such as document and email management, CRM, practice and matter management, time and billing, virtual data rooms, and their integration with AI solutions.
- Experience administering enterprise AI platforms and assistants, as well as enterprise data, analytics, and reporting solutions.
Qualifications:- Expertise in Microsoft Azure (preferred), including compute, networking, storage, security, monitoring, and Infrastructure as Code.
- Strong knowledge of identity and access management, including Entra ID, OAuth 2.0, application permissions, managed identities, and role-based access control (RBAC).
- Experience with API management, gateway administration, and secure service integration.
- Hands-on experience with Terraform, CI/CD pipelines, and containerized environments.
- Experience deploying and supporting AI platforms, including model deployment, embeddings, and vector search technologies.
- Knowledge of agentic AI architectures, including MCP and secure integration patterns for AI agents.
- Strong understanding of network and cloud security, including firewalls, TLS, certificates, and secure connectivity.
- Experience integrating enterprise platforms and services through Microsoft Graph APIs and other enterprise integration technologies.
Salary Range (Toronto Only):$115,000- $130,000 annually.
The position is for an existing vacancy.
