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Infrastructure Management Services, Digital and Technology Solutions

Entrust

Principal Application DevOps Engineer, AI & Automation

Canada

Full-time

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Job details

Job type: Full-time
Experience: 10+ years of experience across software engineering, DevOps, site reliability engineering, application operations, production engineering, or related disciplines.
Posting language: English
Posted: Oct 7, 2026

Original job description

Position Overview:

The IFI Cloud Service includes a broad set of customer-facing services, application components, databases, integrations, and on-premises cloud infrastructure. The Principal Application DevOps Engineer, AI & Automation will bring an application-first engineering perspective to Cloud Services and serve as a key bridge between R&D and Operations.

This is a senior, hands-on individual contributor role for a technical leader who can anchor application operations and progressively build AI-enabled automation capability within Cloud Services. The role is responsible for advancing application observability, production triage, release engineering, deployment automation, and operational readiness, while reducing reliance on development resources for day-to-day production insight and release support.

The individual will also lead practical adoption of AI within operational workflows. The focus is not limited to using AI as a personal productivity tool. This role will identify, design, build, and operationalize AI-assisted solutions that improve incident response, monitoring quality, deployment assurance, root cause analysis, and operational decision-making. The successful candidate will be comfortable moving from an idea or proof of concept to a secure, supportable solution used by the team.

Responsibilities:

Application Operations & Observability

Develop deep working knowledge of IFI application architecture, service dependencies, transaction flows, and common failure modes.
Define and implement application health indicators, service-level indicators, dashboards, alerts, and diagnostic views that connect system behavior to customer and application impact.
Advance monitoring beyond infrastructure signals such as CPU, disk, memory, and connections by incorporating application behavior, transactions, errors, latency, dependencies, and business-process health.
Partner with engineers and support teams to improve telemetry, logging, tracing, application diagnostics, and supportability.
Establish standards for actionable alerting, monitoring coverage, operational runbooks, and application readiness.

Incident Triage, Reliability & Problem Management

Lead application-focused triage for complex production incidents and help the team distinguish symptoms from application, integration, data, deployment, or infrastructure causes.
Use logs, metrics, traces, code-level context, database signals, and deployment history to accelerate diagnosis and recovery.
Drive root cause analysis and corrective-action planning for recurring or high-impact issues.
Identify reliability risks and translate findings into engineering improvements, automation, monitoring changes, and backlog items.
Coach Cloud Services engineers in application-aware troubleshooting and production engineering practices.

Software Delivery & Release Engineering

Own and improve deployment automation, CI/CD pipelines, release engineering practices, and environment promotion processes.
Establish release standards, deployment validation, post-deployment assurance, rollback procedures, and production-readiness criteria.
Partner with R&D to define clear operational handoffs, ownership boundaries, and support expectations for new and changed capabilities.
Advance practices such as automated testing, progressive delivery, Blue/Green deployments, controlled cutovers, and automated recovery.
Reduce manual steps, release risk, and dependency on individual subject matter experts.

AI-Enabled Operations & Automation

Identify and prioritize operational problems where AI can materially improve speed, quality, consistency, or engineering capacity.
Design and build practical AI-assisted solutions for alert enrichment, incident summarization, triage guidance, log and telemetry analysis, deployment validation, anomaly investigation, knowledge retrieval, and corrective-action recommendations.
Move AI opportunities from concept through prototype, validation, production implementation, adoption, and measurable outcome tracking.
Integrate approved AI capabilities with operational data sources, monitoring platforms, delivery pipelines, knowledge repositories, and team workflows.
Apply appropriate security, access, data-handling, validation, auditability, and human-review controls to AI-enabled operational solutions.
Establish reusable patterns and coach engineers so AI adoption becomes a team capability rather than a collection of isolated experiments.

Technical Leadership & Partnership

Serve as a senior technical leader and change agent without requiring formal people-management responsibility.
Influence architecture, tooling, engineering priorities, and operating practices across Cloud Services, R&D, AppOps, and related partners.
Turn ambiguous operational needs into a clear technical approach, delivery plan, and measurable result.
Mentor engineers through hands-on pairing, technical reviews, troubleshooting sessions, and reusable guidance.
Communicate technical findings and recommendations clearly to engineering, operations, product, and leadership audiences.
Participate in scheduled daytime on-call coverage as part of a follow-the-sun support model and in off-hours maintenance windows as assigned.

Success Measures

Improved application-level observability and earlier detection of customer-impacting conditions.
Faster, more consistent application triage with less dependency on R&D or individual subject matter experts.
Increased Cloud Services ownership of release, deployment, validation, and operational-readiness activities.
Reduced avoidable alert noise, recurring incidents, manual release effort, and deployment failures.
Production use of AI-enabled operational capabilities with demonstrated adoption and measurable value.
Greater application and software-delivery depth across the broader Cloud Services engineering team.

Basic Qualifications:

Bachelor's degree in Computer Science, Software Engineering, Information Technology, or an equivalent combination of education and relevant experience.
10+ years of experience across software engineering, DevOps, site reliability engineering, application operations, production engineering, or related disciplines.
Extensive experience supporting enterprise SaaS or distributed microservices applications in production environments.
Strong software-development or scripting capability and the ability to read, troubleshoot, and improve application code and automation.
Hands-on experience with CI/CD, configuration automation, deployment tooling, source control, and software release practices.
Demonstrated expertise with application performance monitoring, centralized logging, distributed tracing, alert design, and production diagnostics.
Experience leading complex incident triage, root cause analysis, and reliability improvements across application and infrastructure boundaries.
Experience building or integrating AI-assisted engineering or operations solutions, including agentic AI workflows, AI agents, or tool-using automation beyond basic code generation or ad hoc analysis.
Ability to lead through influence, mentor experienced engineers, and deliver meaningful progress in an environment with shared ownership.

Preferred Qualifications:

Experience supporting highly available applications and services in on-premises or private-cloud environments.
Experience with tools such as Datadog, Splunk, Jenkins, Octopus Deploy, Ansible, Terraform, GitHub, or comparable platforms.
Experience designing operational workflows that use generative AI, AI agents, retrieval-augmented generation, or machine-learning-based analysis.
Familiarity with responsible AI practices, including data protection, validation, human oversight, prompt and model risk, and production monitoring.
Experience with secure, highly available, regulated, or payment-related services.
Experience with Blue/Green deployment models, automated post-deployment assurance, and production-readiness reviews.

About Entrust

Entrust keeps the world moving safely by enabling trusted identities, payments, and data protection around the globe. People rely on seamless, secure experiences when crossing borders, making purchases, accessing corporate networks, and interacting with digital services. Entrust delivers a broad portfolio of identity, payment, and data-protection solutions to organizations around the world.

Entrust Corporation is an equal opportunity employer, including veterans and people with disabilities.

NO AGENCIES, NO RELOCATION

At Entrust, we don’t just offer jobs – we offer career journeys. Here is what you can expect when you join our team:

Career Growth: Whether you’re a budding developer or a seasoned expert, we’re invested in your professional journey. With learning-forward initiatives and exciting challenges, your growth is our priority.
Flexibility: Life is all about balance. Whether you’re remote, hybrid, or on-site, we offer flexible options that fit your lifestyle.
Collaboration: Here, your voice matters. Our teams thrive on sharing ideas, brainstorming solutions, and working together to build a better tomorrow.

We believe in securing identities - but it doesn’t stop there. At Entrust, we’re passionate about valuing all identities. Our culture is built on diversity, inclusion, and respect. From unconscious bias training for our leaders to global affinity groups that connect colleagues across the globe, we’re creating a community where everyone is encouraged to be themselves.

Ready to Make an Impact?

If you’re excited by the prospect of innovating, growing your career, and collaborating in a dynamic environment, Entrust is the place for you. Join us in making a difference. Let’s build a more secure world - together.

Apply today!

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More about this job

Responsibilities

Lead application operations, observability, production incident response, reliability improvements, and release engineering for Cloud Services, while strengthening operational ownership and collaboration with R&D. Identify, build, and operationalize secure AI-enabled tools and workflows that improve monitoring, triage, deployment assurance, and operational decision-making.

Requirements

Requires a bachelor's degree or equivalent relevant education and experience, 10+ years in software engineering, DevOps, SRE, application operations, or related fields, and extensive production experience with enterprise SaaS or distributed microservices. Candidates need strong development or scripting skills, CI/CD and release expertise, application monitoring and diagnostics experience, complex incident leadership, and experience building or integrating AI-assisted engineering or operations solutions.

Skills

Application Operations
DevOps
Site Reliability Engineering
Application Observability
Incident Triage
Root Cause Analysis
CI/CD
Release Engineering
Deployment Automation
AI-Assisted Operations
Agentic AI Workflows
Distributed Tracing
Centralized Logging
Application Performance Monitoring
Infrastructure as Code
Production Diagnostics

Benefits

Career Growth
Flexible Work Options
Collaborative Work Environment
Diversity and Inclusion

Visa sponsorship

Not detected in the job text

Keywords

Cloud Services
Enterprise SaaS
Microservices
Application Observability
Service-Level Indicators
Application Performance Monitoring
Centralized Logging
Distributed Tracing
Incident Management
Root Cause Analysis
CI/CD
Jenkins
Octopus Deploy
Ansible
Terraform
GitHub
Datadog
Splunk
Blue/Green Deployment
Progressive Delivery
Generative AI
AI Agents
Retrieval-Augmented Generation
Machine Learning
Responsible AI
Production Readiness
Deployment Validation
Configuration Automation
On-Premises Infrastructure
Regulated Services

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