AI & Cloud Computing Analyst

Mjolnir Security•Toronto, ON

19h•Hybrid

About The Position

Mjolnir Security is a Canadian MSSP and Digital Forensics & Incident Response (DFIR) firm operating at the intersection of security and advanced technology. We design, build, and operate proprietary AI-augmented platforms that power security operations, threat intelligence, forensic workflows, and infrastructure automation for enterprise clients across regulated industries. Canadian data residency is a non-negotiable design principle across everything we build and operate. We're looking for an AI & Cloud Computing Analyst who is technically curious, cloud-literate, and genuinely excited about applying modern AI to real security and operational problems. You'll support the design, deployment, and maintenance of cloud infrastructure, AI-integrated workflows, and Zero Trust network architecture — working directly with the senior leadership team on both internal platform development and client-facing cloud engagements. This is a hands-on, high-exposure role in a small firm. You'll work across the full stack — infrastructure, automation, AI integration, and documentation — and be expected to grow fast.

Requirements

3+ years of experience in cloud infrastructure, DevOps, or AI/ML engineering — or a strong academic foundation with demonstrable hands-on project work
Working knowledge of at least one major cloud platform, with Microsoft Azure preferred
Comfort with Linux administration: CLI proficiency, service management, SSH, networking fundamentals, and basic system hardening
Ability to read, write, and debug Python; comfort with REST API patterns and integrations
Familiarity with AI/LLM concepts: API usage, prompt engineering, or retrieval-augmented generation (RAG) architecture is a strong asset
Understanding of Zero Trust networking principles and secure remote access design is an advantage
Strong documentation habits — you write things down clearly and precisely so others can follow
A builder's mindset: you want to understand how systems work at a level deeper than the documentation suggests

Nice To Haves

Microsoft Azure certifications (AZ-900, AZ-104, or AI-102) are valued but not required

Responsibilities

Support deployment and maintenance of Canadian-resident cloud and on-premise virtualization infrastructure, including server provisioning, VM lifecycle management, and environment hardening
Assist with Zero Trust network architecture configuration: endpoint agent deployment, access policy management, secure tunneling, and per-device access controls
Help build, test, and refine AI-powered workflows that integrate large language models into security operations, document processing, and internal automation pipelines
Support the deployment and operation of self-hosted AI inference environments, including local model serving and retrieval-augmented generation (RAG) pipelines
Contribute to Python-based tooling: API backend development, automation scripts, data processing pipelines, and third-party integrations
Assist with Linux system administration for server infrastructure, thin client deployments, and VM templates — including hardening, networking, and remote access configuration
Support Microsoft Azure and M365 administration including identity management, endpoint management, and cloud resource oversight
Document infrastructure configurations, deployment runbooks, and architecture decisions to a high standard
Participate in internal platform testing, debugging, and iterative improvement cycles across a portfolio of proprietary security tools