Lead Technology Architect, DevOps

Equitable•Waterloo, ON

2d•CA$97,000 - CA$145,000•Hybrid

About The Position

At Equitable, we believe work should be a place where you feel supported, inspired, and empowered to grow. In our caring and collaborative environment, your curiosity is encouraged, your passion is recognized, and your contributions truly matter. Together, we create meaningful impact, for our clients, our communities, and each other. At Equitable, we believe great things happen when we work together. We’re a Canadian mutual company driven by purpose - putting people first and helping Canadians protect today and prepare for tomorrow. If you’re passionate about making a difference and growing your career in an inclusive and collaborative environment, we’d love to hear from you. Our culture is built on care, passion and curiosity. We put people above all else, strive to be our best and welcome new ideas to deliver positive outcomes. As the Lead Technology Architect, DevOps, this is a chance to shape how modern software delivery works at Equitable — building the automation, platforms, guardrails, and AI-enabled engineering practices that help teams ship faster, safer, and with greater confidence. You’ll help define how AI-assisted development becomes a safe, practical, and measurable part of Equitable’s engineering toolkit. Come join one of the Waterloo Area’s Top Employers for 2024!

Requirements

Proven experience in DevOps, platform engineering, cloud engineering, release engineering, site reliability engineering, or software delivery automation.
Hands-on experience with Azure DevOps, including Azure Boards, Azure Repos, Azure Pipelines, Azure Artifacts, and release management practices.
Hands-on experience with GitHub, including repositories, pull requests, branch protection, GitHub Actions, GitHub Enterprise, and secure collaboration workflows.
Strong understanding of CI/CD, Git, trunk-based development or GitFlow, automated testing, artifact management, deployment automation, and environment promotion models.
Experience with Microsoft Azure services, cloud networking, identity and access management, compute, storage, monitoring, and governance controls.
Working knowledge of Infrastructure as Code, scripting, automation, and configuration management using tools such as Terraform, Bicep, PowerShell, Bash, Python, or similar technologies.
Understanding of DevSecOps practices, secure coding, vulnerability management, secrets management, application security testing, and compliance-driven delivery requirements.
Ability to collaborate across technical and non-technical teams, translate requirements into delivery patterns, and communicate clearly with engineering, security, architecture, and leadership stakeholders.
Self-motivated learner, who can help determine how new technology and solutions fits within the Equitable technology landscape.
Experience designing internal developer platforms, reusable pipeline frameworks, golden paths, self-service templates, or paved-road engineering capabilities.
Knowledge of SRE concepts, service level objectives, observability, incident response, disaster recovery, resilience engineering, and operational readiness reviews.
Experience in regulated environments where auditability, change management, evidence capture, risk management, and compliance controls are required.
Familiarity with Agile delivery, product-aligned teams, continuous planning, backlog management, and iterative delivery practices
Strong analytical and structured problem-solving skills.
B.S. degree in Computer Science, Software Engineering, MIS or equivalent combination of education and experience.
Excellent written and verbal communication skills
Enjoys and excels in a fast-paced environment with some level of ambiguity on requirements.
Experience working with onsite and offshore consultants for timely and quality delivery.

Nice To Haves

Experience in Health Insurance or Financial Services is an asset.

Responsibilities

Design, build, and operate secure CI/CD pipelines using Azure Pipelines, GitHub Actions, reusable YAML templates, release gates, automated approvals, and deployment strategies such as blue/green, canary, and rolling releases.
Modernize source control, branching, pull request, code review, and release management practices using GitHub Enterprise, Azure Repos, GitHub Advanced Security, and policy-based controls.
Implement Infrastructure as Code using Bicep, Terraform, ARM templates, or other approved tooling to provision and manage Azure resources in a repeatable, auditable, and version-controlled manner.
Integrate automated testing, code quality checks, dependency scanning, secret scanning, container scanning, and security controls into development and deployment pipelines.
Enable AI-assisted software delivery by supporting responsible use of GitHub Copilot, AI coding assistants, prompt patterns, agentic development workflows, automated test generation, documentation generation, and developer productivity accelerators.
Develop and maintain platform engineering capabilities, templates, starter kits, reusable pipeline components, self-service automation, and internal developer experience standards.
Partner with security and risk teams to embed DevSecOps practices, including least privilege access, secrets management, vulnerability remediation, policy compliance, auditability, and secure-by-design delivery patterns.
Operate cloud-native environments using Azure services, containers, Kubernetes, observability tooling, logging, monitoring, alerting, and incident response practices.
Support application teams with deployment troubleshooting, performance tuning, environment configuration, release readiness, and production stability improvements.
Champion continuous improvement, automation-first practices, documentation, knowledge sharing, and modern engineering culture across delivery teams.
Partnering with internal teams to align with project delivery frameworks.
Promote responsible adoption of AI-assisted development tools, including GitHub Copilot and related AI productivity capabilities.
Establish guidance for when and how engineers should use AI for code generation, test creation, refactoring, documentation, troubleshooting, and pipeline support.
Help define guardrails for AI-generated code, including human review, secure coding validation, intellectual property considerations, privacy protection, and compliance with internal technology standards.
Use AI to accelerate DevOps workflows where appropriate, including work item summarization, release notes, incident summaries, deployment diagnostics, knowledge base creation, and automation script generation.
Continuously assess emerging AI-enabled DevOps practices and recommend pragmatic adoption patterns that improve quality, reliability, security, and developer experience.
Partner with internal audit, risk, compliance and control teams to evolve control frameworks for AI-enabled development and how it might be affected by various OFSI regulatory requirements such as OFSI B-10 and E-23.