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Intermediate Full Stack Developer Jobs in London, ON

Penske

Yard Administrator - Night Shift

Woodstock, ON · On-site

... Logistics engineers state-of-the-art transportation, warehousing and supply chain management ... Intermediate skills in Microsoft Office, Outlook and Inter / Intranet use - Ability to work ...

Penske

Yard Administrator - Night Shift

Woodstock, ON · On-site

... Logistics engineers state-of-the-art transportation, warehousing and supply chain management ... Intermediate skills in Microsoft Office, Outlook and Inter / Intranet use - Ability to work ...

Penske

Yard Coordinator - 2nd Shift

Woodstock, ON · On-site

... Logistics engineers state-of-the-art transportation, warehousing and supply chain management ... required - Intermediate skills in Microsoft Office - Entry level skills with Outlook and Inter ...

Carmeuse

Environmental Area Manager

Ingersoll, ON

CA$120K - CA$159K/yr

Comprehensive benefits package that includes Health, Dental, Vision, and a full pension plan ... Work with operations and engineering to understand process emissions and develop data. * Interact ...

Ellisdon

Lead Estimator

London, ON · On-site

CA$110K - CA$120K/yr

You have a Degree or Diploma in Engineering or Construction * 10+ years of civil construction ... Intermediate knowledge of Microsoft Word, Excel, and Outlook The salary range for this job is $110 ...

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All JobsIntermediate Full Stack Developer JobsIntermediate Full Stack Developer Jobs in London, ON

Intermediate Full Stack Developer information

What is L1, L2, L3, and L4 developer?

In the context of an Intermediate Full Stack Developer role, L1, L2, L3, and L4 typically refer to different levels of seniority or expertise within a company's technical ladder. L1 is usually entry-level, L2 and L3 are mid-level with increasing responsibilities, and L4 often denotes senior or lead developers who handle complex tasks and mentorship. These levels help define expectations, skills, and experience required for each stage in a developer's career progression.

What are the key skills and qualifications needed to thrive as an Intermediate Full Stack Developer, and why are they important?

To thrive as an Intermediate Full Stack Developer, you need solid proficiency in front-end and back-end programming languages (such as JavaScript, HTML/CSS, and a backend language like Node.js, Python, or Java), along with experience in database management and version control systems. Familiarity with frameworks (e.g., React, Angular, Express), cloud services, and tools like Git is typically required, and certifications in relevant technologies can be advantageous. Strong problem-solving abilities, effective communication, and teamwork distinguish high-performing developers in this role. These combined technical and interpersonal skills are crucial for efficiently building, deploying, and maintaining robust, user-friendly web applications in collaborative environments.

Is full stack worth it in 2026?

For an Intermediate Full Stack Developer, full stack development remains a valuable skill set in 2026 due to ongoing demand for versatile developers proficient in both front-end and back-end technologies. Staying current with frameworks like React, Node.js, and cloud platforms enhances job prospects and career growth in this field.

What is the difference between Intermediate Full Stack Developer vs Front End Developer?

AspectIntermediate Full Stack DeveloperFront End Developer
Required SkillsProficiency in both front-end and back-end technologies, including JavaScript, HTML, CSS, and server-side languagesSpecialized in client-side technologies like HTML, CSS, JavaScript, and frameworks such as React or Angular
Work EnvironmentWorks on both server and client-side applications, often in full project cyclesFocuses primarily on user interface and experience
Common UsageUsed across startups and full-stack teams in various industriesCommon in front-end teams within larger organizations

The Intermediate Full Stack Developer has a broader skill set covering both front-end and back-end development, while the Front End Developer specializes in creating and optimizing user interfaces. The choice depends on whether the role requires full-stack capabilities or a focus on client-side development.

Will Fullstack be replaced by AI?

Full Stack Developers perform tasks that involve designing, coding, and maintaining both frontend and backend systems, which require complex problem-solving and creativity. While AI tools can assist with coding and automation, they are unlikely to fully replace the need for human developers who understand project context, user experience, and system architecture. Continuous learning and adapting to new technologies remain essential in this role.

What is an Intermediate Full Stack Developer?

An Intermediate Full Stack Developer is a software professional with a few years of experience who is proficient in both front-end and back-end web development. They are capable of working on the user interface, server-side logic, databases, and APIs, often collaborating with other team members to build and maintain web applications. Intermediate developers have moved beyond entry-level tasks, can work independently on moderately complex projects, and are familiar with industry-standard tools and frameworks. Their role often includes troubleshooting, optimizing code, and contributing to architecture decisions while still learning and expanding their skill set.

Can I become a full stack developer with no experience?

Becoming an intermediate full stack developer typically requires gaining experience through self-study, coding projects, or coding bootcamps, as employers often look for demonstrated skills in front-end and back-end technologies. While it is possible to start learning without prior experience, reaching an intermediate level usually involves building a portfolio and understanding frameworks, databases, and version control tools like Git.

What are some common challenges faced by Intermediate Full Stack Developers when balancing front-end and back-end responsibilities?

Intermediate Full Stack Developers often encounter the challenge of effectively managing tasks across both front-end and back-end domains, which requires staying updated with rapidly evolving technologies on both sides. Coordinating the integration of user interfaces with server logic, ensuring seamless communication between components, and maintaining code quality across the stack can be demanding. Additionally, they frequently collaborate with UI/UX designers, DevOps engineers, and QA teams, making strong communication and time management skills essential. Addressing these challenges provides valuable experience and prepares developers for more advanced roles in the future.
What are the most commonly searched types of Full Stack Developer jobs in London, ON? The most popular types of Full Stack Developer jobs in London, ON are:
What cities near London, ON are hiring for Intermediate Full Stack Developer jobs? Cities near London, ON with the most Intermediate Full Stack Developer job openings:
Intermediate Full Stack Developer jobs near you
Senior Platform Engineer - LLM and AI Infrastructure

Senior Platform Engineer - LLM and AI Infrastructure

CARFAX

London, ON

Full-time

Medical, Retirement

Posted 15 days ago

Job description

Join Team CARFAX as a Senior Platform Engineer - LLM and AI Infrastructure
 
We are looking for a seasoned Senior Platform Engineer - LLM and AI Infrastructure to 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 a Kubernetes-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 on AWS 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 of AI/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 the LGTM 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 is AWS — 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 with Flyte or comparable ML workflow orchestration platforms (Kubeflow, Airflow, Prefect, Metaflow)
Experience operating JupyterHub or equivalent multi-user interactive compute platforms at scale
Familiarity with LLM-specific infrastructure — model serving frameworks (vLLM, Triton, TorchServe), GPU cluster management, large-scale distributed training setups
Hands-on experience with AWS (EKS, EC2 GPU families, S3, IAM, VPC) as our current primary cloud environment
Experience with FinOps 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:
A systems thinker who 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
Deeply curious 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 effective collaborator and communicator who 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 platform that enables LLM development and productionization — your contributions will have immediate, measurable impact
Work on genuinely hard infrastructure problems — GPU scheduling, large-scale distributed workloads, high-throughput model serving, and multi-tenant ML environments
Be positioned at the epicenter of the AI infrastructure space, one of the fastest growing and highest-demand engineering disciplines in the industry
Have a clear 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.