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Engineering Operations Manager Jobs in London, ON

CARFAX

Senior Software Engineer - Dev Ops

London, ON

... , Platform Engineering, MLOps, or a closely related infrastructure discipline. Deep Kubernetes expertise - production experience operating Kubernetes at scale on any major managed platform (EKS, GKE ...

BDO Canada

AI Engineer

London, ON · On-site

CA$77K - CA$117K/yr

... software engineering. In this replacement role, you will play a critical role in enabling ... Develop, refine, and optimize complex prompt strategies; manage model context windows; and finetune ...

Alimentiv

Manager, Clinical Data Management

London, ON · On-site

CA$99K - CA$166K/yr

Responsible for meeting operational responsibilities and targets including but not limited to ... programming to ensure clinical databases are designed in a standard, accurate, complete, and ...

GEI Consultants

Branch Manager

London, ON · Hybrid

CA$140K - CA$190K/yr

... engineering and/or environmental consulting * Previous leadership or team management experience * Strong understanding of consulting operations and project delivery * Excellent communication ...

Td

Software Engineer I

London, ON · On-site

CA$69K - CA$98K/yr

Hands-on experience with CI/CD pipelines, DevOps practices, and development automation ... in a software engineering environment. * Strong time management skills, with the ability to ...

Td

Manager, Network Service Delivery

London, ON

CA$96K - CA$136K/yr

Manage service delivery team of engineers for enterprise campus and retail network services. * Drives a culture of automation and operational excellence, leveraging Infrastructure-as-Code and process ...

Td

Software Engineer II (AI Integration)

London, ON · On-site +1

CA$96K - CA$115K/yr

Work with product managers and business teams to translate business problems into AI solutions. * Partner with cloud engineers and DevOps teams for scalable deployment. * Communicate complex ...

JLL

Automation Manager

London, ON

Partner with operations, engineering, and support teams to optimize MHE systems and deliver ... investment management services. We take our responsibility to protect the personal information ...

New

Td

Software Engineer III (AI Integration)

London, ON · On-site +1

CA$125K - CA$154K/yr

Work with product managers and business teams to translate business problems into AI solutions. * Partner with cloud engineers and DevOps teams for scalable deployment. * Communicate complex ...

KPMG

Security Architect

London, ON · On-site

... managers, solution architects, Business, and QA analysts. This individual will also provide ... Coordinate with DevOps teams to advocate secure coding practices and escalate concerns related to ...

Wood Plc

Senior Site Project Manager

London, ON

... operations, procurement, accounting and finance; * Actively manage and lead day to day execution of ... Professional Engineer (P Eng) and PMP are considered strong assets; * Must have 20+ years ...

Wood Plc

Senior Site Project Manager

London, ON

... operations, procurement, accounting and finance; * Actively manage and lead day to day execution of ... Professional Engineer (P Eng) and PMP are considered strong assets; * Must have 20+ years ...

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All JobsEngineering Operations JobsEngineering Operations Manager JobsEngineering Operations Manager Jobs in London, ON

Engineering Operations Manager information

See London, ON salary details

$53.5K

$87K

$115.2K

How much do engineering operations manager jobs pay per year?

As of Aug 6, 2026, the average yearly pay for engineering operations manager in London, ON is $87,007.00, according to ZipRecruiter salary data. Most workers in this role earn between $77,685.00 and $97,106.00 per year, depending on experience, location, and employer.

What are some common challenges faced by engineering operations managers, and how can they be effectively managed?

Engineering Operations Managers often face challenges such as balancing project timelines with resource constraints, coordinating cross-functional teams, and ensuring quality standards are met while controlling costs. Effective management involves clear communication, proactive risk assessment, and continuous process improvement. Leveraging project management tools and fostering a collaborative team culture can help address these challenges and drive successful project outcomes.

What does an engineering operations manager do?

An Engineering Operations Manager oversees the daily operations of engineering teams to ensure projects are delivered on time and within budget. They coordinate between different departments, manage resources, implement processes to improve efficiency, and resolve operational issues. Their role often includes supervising staff, developing operational policies, and ensuring compliance with safety and quality standards. Ultimately, they help align engineering activities with the company’s strategic goals.

How much do engineering operations managers make?

Engineering Operations Managers typically earn a median annual salary ranging from $100,000 to $150,000, depending on experience, industry, and location. They often oversee engineering teams, manage processes, and utilize tools like project management software, with higher salaries generally associated with advanced certifications and leadership responsibilities.

What is the difference between Engineering Operations Manager vs Mechanical Engineer?

AspectEngineering Operations ManagerMechanical Engineer
CredentialsBachelor's or Master's in Engineering, management experienceBachelor's or Master's in Mechanical Engineering
Work EnvironmentOversees teams, manages projects, strategic planningDesign, analysis, testing, and development of mechanical systems
Industry UsageManufacturing, aerospace, automotive, tech companiesManufacturing, automotive, aerospace, product design

The Engineering Operations Manager focuses on overseeing engineering teams and managing operations, while Mechanical Engineers are involved in designing and developing mechanical systems. Both roles require engineering credentials, but their responsibilities and work environments differ significantly.

What are the key skills and qualifications needed to thrive as an engineering operations manager, and why are they important?

To thrive as an Engineering Operations Manager, you need a strong background in engineering principles, project management, and operations oversight, often supported by a bachelor's degree in engineering or a related field. Familiarity with project management tools (like MS Project or Asana), ERP systems, and relevant certifications such as PMP or Lean Six Sigma is typically required. Excellent leadership, communication, and problem-solving skills set standout candidates apart in managing teams and driving process improvements. These competencies ensure efficient operations, timely project delivery, and alignment with organizational goals in an engineering environment.

Is an engineering operations manager a high paying job?

Engineering operations managers typically earn higher-than-average salaries due to their leadership responsibilities, technical expertise, and experience requirements. Compensation varies by industry, location, and company size but generally reflects the seniority of the role and the need for skills in project management, process optimization, and engineering systems.
What cities near London, ON are hiring for Engineering Operations Manager jobs? Cities near London, ON with the most Engineering Operations Manager job openings:
Infographic showing various Engineering Operations Manager job openings in London, ON as of July 2026, with employment types broken down into 87% Full Time, 12% Part Time, and 1% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $87,007 per year, or $41.8 per hour.

Senior Software Engineer - Dev Ops

CARFAX

London, ON

Full-time

Medical, Retirement

Re-posted 11 days ago

Job description

Join Team CARFAX as a Senior Software Engineer - Dev Ops
We are looking for a seasonedSenior Software Engineer - Dev Opsto join our platform team and take an active role in designing, scaling, and operating the infrastructure that powers Large Language Model (LLM) development and hosting. This is a high-impact, highly technical position where you will own critical platform components, drive architectural decisions, and directly shape the reliability, performance, and security of our AI infrastructure.
At its core, this is aKubernetes-first, cloud-native platform engineering role. We care deeply about your ability to architect and operate scalable, resilient infrastructure for LLM workloads - the specific cloud or tooling you've built that experience on is secondary. Our current platform runs onAWS with EKS, Flyte, ArgoCD, JupyterHub, and the LGTM observability stack, and you'll be working within that environment - but we are far more interested in the depth of your platform thinking than in a specific vendor background.
If you are an engineer who thrives at the intersection ofAI/ML and cloud-native infrastructure, who gets excited about solving the unique scaling and operational challenges that LLM workloads demand, and who wants to work on technology that sits at the absolute cutting edge of the AI industry - this role was built for you.
At CARFAX, we believe in the power of teamwork and value in-person interactions so that we can collaborate and thrive together. This position will require 2 days in the London, ON office per week, subject to change with future business needs. One last thing: Our four-day week continues in Summer 2026!
What You'll Own:
LLM Platform Architecture - Actively participate in the design and evolution of the core infrastructure platform supporting LLM training, fine-tuning, and inference workloads at scale, contributing architectural decisions that balance performance, cost, and reliability across the full platform lifecycle.
Kubernetes & Advanced Autoscaling- Own the design and implementation of sophisticated K8s autoscaling strategies (HPA, VPA, KEDA, Cluster Autoscaler) tailored to the highly variable and GPU-intensive demands of LLM workloads. Our current environment is EKS, though equivalent production Kubernetes experience on GKE, AKS, or on-prem is equally valued.
ML Workflow Orchestration- Participate in the engineering and optimization of ML pipeline infrastructure, contributing to best practices for pipeline design, resource allocation, and workflow reliability across LLM training and evaluation workloads. We currently use Flyte - experience with comparable platforms such as Kubeflow, Airflow, or Prefect translates well.
AI Developer Platform- Own and contribute to the architecture and operations of interactive compute environments used by AI researchers and LLM engineers to develop, experiment, and prototype. We run JupyterHub today, though experience with equivalent multi-user ML development platforms is directly applicable.
CI/CD & GitOps- Participate in the development and ongoing improvement of GitOps workflows and CI/CD pipelines, contributing to deployment best practices and enabling rapid, reliable delivery of platform changes. Our current implementation uses ArgoCD - strong experience with GitOps principles and comparable tooling is what matters.
Observability & Reliability - Contribute to the full observability stack implementation - designing dashboards, defining SLOs, building alerting frameworks, and ensuring deep visibility into LLM workload performance and platform health. We use theLGTM stack (Loki, Grafana, Tempo, Mimir)- experience with Prometheus, OpenTelemetry, ELK, Datadog, or equivalent platforms is welcomed.
Cloud Infrastructure - Participate in cloud infrastructure design across compute (including GPU instance families), storage, networking, and IAM, with a strong emphasis on cost optimization and operational excellence. Our primary cloud isAWS- candidates with strong GCP or Azure backgrounds who are prepared to work in AWS are encouraged to apply.
Security & Compliance- Engage actively in the vulnerability assessment and remediation program across all platform components, contributing to security standards and ensuring the LLM platform meets organizational and regulatory compliance requirements.
Collaborative Engineering- Participate in technical design reviews, contribute to roadmap discussions, and serve as a knowledgeable resource and collaborative partner across AIOps and MLOps disciplines
Required Experience & Skills:
7+ years of experience in DevOps, Platform Engineering, MLOps, or a closely related infrastructure discipline.
Deep Kubernetes expertise - production experience operating Kubernetes at scale on any major managed platform (EKS, GKE, AKS) or on-premises, with advanced knowledge of scheduling, autoscaling, networking, RBAC, and cluster operations.
Cloud infrastructure proficiency- extensive experience designing and operating production workloads on at least one major cloud provider (AWS, GCP, or Azure), covering compute, storage, networking, and identity and access management
MLOps / AI Infrastructure experience- demonstrated experience building and operating infrastructure that supports ML training, model serving, or LLM workloads, including GPU resource management and scheduling at scale
CI/CD & GitOps- strong hands-on experience with GitOps principles and modern CI/CD pipeline design, using any mainstream tooling (ArgoCD, Flux, GitHub Actions, Tekton, or equivalent)
Observability Engineering- production experience designing and operating observability platforms including metrics, logging, and distributed tracing, using any modern stack (Grafana/LGTM, Prometheus, Datadog, ELK, or equivalent)
Infrastructure as Code - strong proficiency with Terraform, Helm, or comparable IaC and configuration management tooling.
Programming & Scripting - solid coding ability in Python and/or Go, with experience writing automation, tooling, and infrastructure integrations.
Security Mindset- hands-on experience with vulnerability scanning, remediation workflows, and cloud security best practices including RBAC hardening and secrets management
Strongly Preferred:
Direct experience withFlyteor comparable ML workflow orchestration platforms (Kubeflow, Airflow, Prefect, Metaflow)
Experience operatingJupyterHubor equivalent multi-user interactive compute platforms at scale
Familiarity withLLM-specific infrastructure- model serving frameworks (vLLM, Triton, TorchServe), GPU cluster management, large-scale distributed training setups
Hands-on experience withAWS(EKS, EC2 GPU families, S3, IAM, VPC) as our current primary cloud environment
Experience withFinOps practices- cloud cost attribution, rightsizing, and spot/preemptible instance strategies for ML workloads
Relevant certifications:CKA / CKS, AWS/GCP/Azure Solutions Architect or DevOps Engineer, or equivalent
Who You Are:
Asystems thinkerwho understands how architectural decisions ripple across reliability, performance, cost, and security - regardless of which cloud or tooling stack those decisions are made within
Operationally minded- you build things to be observable, maintainable, and resilient from day one
Deeplycurious about AI and LLMs- you understand why the infrastructure you build matters and stay current with how the AI landscape is evolving
Proactive and ownership-driven- you identify problems before they become incidents and drive solutions to completion
An effectivecollaborator and communicatorwho can translate complex infrastructure concepts for AI researchers, data scientists, and engineering leadership alike
Comfortable operating with autonomy in a fast-moving environment where priorities evolve alongside the AI landscape
Why This Role Stands Out:
LLM infrastructure is one of the most technically demanding and strategically important engineering domains in the industry today. As a senior member of our AIOps team you will:
Directly shape the platformthat enables LLM development and productionization - your contributions will have immediate, measurable impact
Work ongenuinely hard infrastructure problems- GPU scheduling, large-scale distributed workloads, high-throughput model serving, and multi-tenant ML environments
Be positioned at theepicenter of the AI infrastructure space, one of the fastest growing and highest-demand engineering disciplines in the industry
Have aclear voice in technical direction- your experience and opinions on platform design are genuinely valued and actively sought
Bring your full experience to the table - whether you've built on AWS, GCP, Azure, or hybrid environments, your platform engineering expertise is what drives impact here
What's in it for you:
  • Competitive Compensation: Attractive salary, comprehensive benefits, and generous time-off policies.
  • Flexible Work Schedules: Enjoy 4-day summer work weeks and a winter holiday break.
  • Retirement Support: 401(k) / DCPP matching.
  • Performance Rewards: Annual bonus program to recognize your contributions.
  • Innovative Workspace: Casual, dog-friendly offices designed for creativity and collaboration.
Hear from our Team: Our accolades speak for themselves:
  • 10X Virginia Business Best Places to Work
  • 9X Washingtonian Great Places to Work
  • 9X Washington Post Top Workplace
  • St. Louis Post-Dispatch Best Places to Work
Vacancy Status:
This posting is for an existing vacancy.
Base Salary:
The anticipated base salary range for this position is CAD $92,500 to $136,000 annually. Final base salary will be determined based on geographical location, experience, and qualifications.
Benefits:
Join a company that values your total wellbeing. Carfax offers competitive compensation, comprehensive healthcare coverage, and the chance to make a meaningful impact in an industry-leading organization. Our benefit offerings can be found at:CARFAX Careers.
Employment Type: Full-Time

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