Systems Architect

HTS Engineering Ltd.•Toronto, ON

1d•Hybrid

About The Position

Founded in 2015 in Toronto, Canada, KORE Solutions is a subsidiary company of HTS and an innovative technology solutions and services provider with a strong focus on the HVAC manufacturer’s representative industry. With a variety of offerings including business intelligence software, help service support, and more, KORE delivers end-to-end solutions that empower our partners and clients to build their successful business. At KORE, communication and collaboration is our top priority. As a team member, you’ll be working closely with all departments to develop our software, TRAX, and the infrastructure surrounding it. We have a strong teamwork-oriented culture, meaning you’re surrounded by resources who want you to succeed. Your contributions will also have a direct impact. You’ll be providing meaningful change to the company and serve to enhance our processes.

Requirements

IT related degree/diploma or equivalent in related field preferred
10+ years of experience in IT architecture, systems engineering, or related roles, with increasing responsibility in solution and platform design
Deep expertise in Microsoft Azure, including compute, networking, storage, identity, and security domains
Proven experience designing and delivering cloud-native and distributed systems architectures
Hands-on experience with Kubernetes and container orchestration in production environments
Strong understanding of infrastructure design, including virtual machines (VMs), Docker, and Linux-based container platforms
Working knowledge of networking fundamentals (TCP/IP, DNS, routing, firewalls, load balancing) and secure network design principles
Experience designing highly available, scalable, and resilient infrastructure solutions, including hybrid environments
Solid understanding of modern application architectures, including microservices, API-driven, and event-driven design
Experience with full-stack development concepts and technologies such as Python, C#, React, Angular, and Flutter
Experience with mobile application architectures and integration patterns
Familiarity with middleware and distributed data technologies such as MongoDB, Redis, and messaging platforms
Experience with CI/CD pipelines and modern DevOps practices, including infrastructure-as-code and automated deployments
Understanding of data platforms and pipelines supporting scalable and real-time processing
Exposure to AI/ML concepts and platforms, including integration of AI services into enterprise applications
Familiarity with MLOps concepts (model lifecycle, deployment, monitoring) is an asset
Strong documentation and architecture communication skills, including experience producing ADRs and TOGAF-aligned artefact
Excellent communication, stakeholder management, and organizational leadership skills
Proven ability to influence technical decisions and align cross-functional teams
Strategic and analytical thinking
Operational excellence mindset
Leadership and team development
Cross-functional collaboration
Risk management and decision-making
Ability to simplify complex technical concepts for non-technical audiences

Nice To Haves

Certifications such as TOGAF and/or cloud certifications (e.g., Azure Solutions Architect)
Experience with modern technology stacks, including Kubernetes, cloud-native platforms, observability tools, virtualization, storage, and enterprise networking
Hands-on experience with microservices and event-driven architectures at scale
Experience with Infrastructure as Code (Terraform, Bicep, ARM templates)
Experience in hybrid cloud and/or multi-cloud environments
Familiarity with observability and monitoring tools such as Elasticsearch, Prometheus, Grafana, and Azure Monitor
Understanding of logging, tracing, and metrics strategies for distributed systems
Knowledge of service mesh technologies (e.g., Istio, Linkerd)
Experience designing platforms supporting AI/ML workloads or data-intensive applications
Exposure to security frameworks and zero-trust architecture principles

Responsibilities

Own and evolve enterprise architecture across cloud, hybrid, and AI-enabled systems
Define and enforce standards for scalability, security, resiliency, and responsible AI
Translate business strategy into technology and AI-enabled architecture roadmaps
Lead architecture governance, design reviews, and technology selection
Evaluate emerging technologies and drive adoption aligned to business value
Architect and optimize solutions on Microsoft Azure, including compute, data, and AI services
Design and govern Kubernetes-based platforms supporting microservices and AI/ML workloads
Define architecture for model deployment, inference, and scaling (real-time and batch)
Lead cloud modernization initiatives with automation, observability, and cost optimization
Establish platform capabilities for MLOps, CI/CD, and infrastructure-as-code
Define architecture for compute, storage, and networking, including GPU-enabled environments for AI workloads
Design secure, scalable network architectures aligned with zero-trust principles
Architect for high availability, disaster recovery, and cross-region resilience
Align infrastructure capabilities with data and AI platform requirements
Define patterns for API-first, event-driven, and microservices architectures
Design integration strategies across enterprise systems, including AI and data platforms
Guide development of AI-enabled applications, including generative AI integration
Standardize service communication, orchestration, and service mesh approaches
Define enterprise data architecture supporting analytics, real-time processing, and AI/ML
Establish patterns for data ingestion, transformation, governance, and lifecycle management
Architect and oversee MLOps (training, deployment, monitoring, retraining)
Ensure data quality, privacy, compliance, and responsible AI practices (bias, explainability, drift)
Enable scalable use of structured and unstructured data for AI-driven insights
Partner with engineering, DevOps, data, and business teams to deliver architecture outcomes
Provide technical leadership, mentorship, and architectural direction
Participate in solution delivery, risk management, and technical decision-making
Collaborate with vendors and partners, including cloud and AI providers
Communicate architecture decisions, risks, and trade-offs to technical and business stakeholders