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Added 2 hours ago
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Full-time
Experience with Terraform, Bicep, ARM templates, or Ansible.
Added 3 hours ago
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Added 3 hours ago
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Added 3 hours ago
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$135,000 to $170,000 CAD / year
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Added 7 hours ago
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Added 7 hours ago
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Added 7 hours ago
Manager, Infrastructure and Cloud Services
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$120,000 to $160,000 CAD / year
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Added 7 hours ago
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Added 8 hours ago
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EPITEC

Cloud Engineering Senior Engineer

Ottawa, ON, Canada

Job type: Contract
Apply by: Oct 24, 2026
Experience: Approximately 7+ years of software development experience.
Working hours: 40 hours per week
Posting language: English
Posted: Sep 24, 2026

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Original job description

Job Title: Software Developer - Telemetry & Observability Platform (TOP)

Location: Ottawa Ontario K2V 1C8 Canada

Job Type: W2 Contract | No C2C

Expected hours per week: 40 hours per week

Schedule: Hybrid

Job Description

The Software Developer in this role will support the design, development, testing, and deployment of the Telemetry & Observability Platform (TOP). TOP is an enterprise platform that integrates vehicle telemetry, diagnostic information, engineering artifacts, manufacturing evidence, service data, and software lifecycle signals to provide actionable diagnostic and software-health insights.

This role will work within a cross-functional Agile team to build cloud-native services, data integrations, user-facing capabilities, and platform observability. The developer will receive technical direction from senior engineers and architects while progressively taking ownership of well-defined platform components and features.

Employees in this job function are responsible for designing, building, and deploying cloud-based infrastructure and managed services to achieve scalability, flexibility, and cost efficiencies for private and public cloud systems that support the business. They are focused on creating opinionated cloud environments and systems such as Storage as a Service and Infrastructure as a Service, which form building blocks used by other enterprise and product teams.

Skills Required

GCP
AWS
REST APIs
JavaScript
SQL
Kubernetes
Docker
Apigee
Agile Software Development
Software Development Lifecycle (SDLC)
GitHub
Spring Boot

Technical Requirements

AWS - Deploy or support basic applications using AWS services such as S3, EC2, or RDS.
GCP - Use GCP 2.0 or GCP 3.0 cloud services such as Compute Engine, Cloud Storage, and BigQuery to run applications or work with data.
API Development - Understand how an application communicates with another system through requests and responses and be capable of developing API endpoints as well as consuming them.
REST APIs - Create or use HTTP endpoints (e.g., GET requests, POST requests).
Java - Write and maintain Java code for application features, business logic, and error handling.
JavaScript - Write basic scripts or application functionality, such as validating form input or updating a webpage/UI.
SQL - Write queries to retrieve, insert, update, and summarize data in a relational database.
Kubernetes - Deploy and manage containerized applications, including checking pod status or updating deployments.
Docker - Build and run containers to ensure applications behave consistently across development and test environments.
Apigee - Publish and manage APIs, configure API proxies, set up authentication, apply policies such as rate limiting, and monitor API traffic.
Agile Software Development - Participate in sprint planning, daily stand-ups, reviews, and retrospectives while delivering work in small increments.
Software Development Lifecycle - Understand the stages of software delivery from requirements and design through development, testing, deployment, and maintenance.
GitHub - Access repositories, create branches, commit changes, open pull requests, and respond to review feedback.
Spring Boot - Build or support Java applications and REST services using Spring Boot.

Skills Preferred

Artificial Intelligence & Expert Systems

Understanding of agentic AI workflows
Data pipeline development and processing
AI evaluation strategies using RAGAS
Understanding of Retrieval-Augmented Generation (RAG) and vectorization
Large Language Model (LLM) orchestration

Experience Required

Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related discipline, or equivalent practical experience.
Approximately 7+ years of software development experience.
Programming experience in one or more relevant languages, including:

Python
Java
JavaScript or TypeScript

Experience developing or consuming REST APIs and working with structured data formats such as JSON.
Understanding of object-oriented programming, software design principles, and common application architecture patterns.
Experience with relational databases, SQL, and basic data modeling.
Experience using Git-based source control and participating in peer code reviews.
Familiarity with automated unit and integration testing.
Basic understanding of cloud computing, containerization, and CI/CD practices.
Ability to diagnose software issues using application logs and debugging tools.
Strong written and verbal communication skills.
Ability to work collaboratively with product owners, architects, engineers, data specialists, testers, and operations teams.

Experience Preferred

Experience with Google Cloud Platform services such as:

Google Kubernetes Engine (GKE)
Pub/Sub
Cloud Storage
Cloud SQL

Experience with Docker, Kubernetes, Terraform, or similar cloud-native technologies.
Experience developing frontend applications using React and TypeScript.
Familiarity with event-driven architecture, asynchronous processing, and data pipelines.
Experience implementing platform observability using logs, metrics, traces, dashboards, and alerting.
Familiarity with OpenTelemetry or comparable observability standards and tooling.
Experience with API specifications and tools such as OpenAPI or Swagger.
Familiarity with authentication, authorization, role-based access control (RBAC), and secure coding practices.
Experience integrating AI or machine-learning services through APIs.
Familiarity with prompt management, AI response validation, confidence scoring, and human-feedback capture.
Experience working with telemetry, automotive diagnostics, connected-vehicle data, manufacturing information, or engineering lifecycle systems.
General knowledge of diagnostic concepts such as DTCs, CAN, UDS, or DoIP is beneficial but not required.
Experience working in an Agile or Scrum delivery model.
Experience with Data Modeling and Data Science.

Benefits: 80 hours paid time off, medical insurance contributions, dental vision and our 401k retirement savings plan

#INDOEM

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More about this job

Responsibilities

Design, develop, test, and deploy cloud-native services, data integrations, and user-facing capabilities for the Telemetry & Observability Platform. Build and support platform components while contributing to observability and actionable diagnostic and software-health insights within a cross-functional Agile team.

Requirements

Requires a bachelor's degree in a relevant discipline or equivalent practical experience, approximately seven or more years of software development experience, and proficiency in relevant programming languages, REST APIs, SQL, Git, and software testing. Candidates should also understand cloud computing, containers, CI/CD, debugging, and collaborative Agile delivery; experience with GCP, Kubernetes, observability, data pipelines, and AI integrations is preferred.

Skills

Google Cloud Platform
Amazon Web Services
Java
JavaScript
Python
REST APIs
SQL
Kubernetes
Docker
Apigee
Spring Boot
GitHub
Data Pipelines
Platform Observability
Agile Software Development
Retrieval-Augmented Generation

Benefits

Paid Time Off
Dental Insurance
Vision Insurance

Visa sponsorship

Not detected in the job text

Keywords

Google Cloud Platform
Amazon Web Services
Google Kubernetes Engine
Pub/Sub
Cloud Storage
Cloud SQL
BigQuery
Compute Engine
Java
JavaScript
TypeScript
Python
React
Spring Boot
REST APIs
OpenAPI
Swagger
Apigee
SQL
Docker
Kubernetes
Terraform
GitHub
CI/CD
OpenTelemetry
Data Pipelines
Event-Driven Architecture
Retrieval-Augmented Generation
RAGAS
Automotive Diagnostics

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