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Devops AI Developer

  • Toronto, ON, Canada
  • Greater Toronto Area, Canada, Canada

Part-time

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Job details

Job type
Part-time
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Posting language
English
Posted

Original job description

Contract

Job title: Data Scientist

Duration: 12 months

Role status: Current opening

The successful candidate will join the Data & Digital team within Engineering, Innovation & Architecture (EIA). The team consists of junior and senior developers, a Scrum Master, and technical leadership working closely with AI and Operations teams. The group owns, supports, and develops applications that power enterprise data platforms, analytics ecosystems, and emerging AI-enabled solutions. Many current and future initiatives involve modernizing applications, developing APIs, and integrating AI capabilities into business workflows.

Principal tasks and responsibilities include:

Key Responsibilities:
??Software Development & Engineering:
??Design, develop, test, deploy, and support applications, APIs, and cloud-native solutions.
??Participate in application modernization, code reviews, testing, and production support activities.
??Troubleshoot complex application and integration issues and implement sustainable solutions.

??Cloud Engineering & DevOps:
??Build and maintain CI/CD pipelines, Infrastructure as Code, and deployment automation frameworks.
??Automate infrastructure provisioning, application deployments, monitoring, and operational processes.
??Improve platform reliability, scalability, security, and operational efficiency through automation and DevOps practices.

Our client:
  • An established financial services organization within the insurance sector.
Qualifications and pre-requisites:
  1. 5+ years of experience in software development, cloud engineering, DevOps, or data engineering.
  2. 3+ years of hands-on development experience using: C#, .NET / .NET Core, Python, SQL, Blazor or similar web application frameworks.
  3. Proven experience designing, developing, deploying, and supporting enterprise applications and APIs in production environments.
  4. Strong understanding of software engineering principles, application architecture, and cloud-native development patterns.
  5. Hands-on experience building and maintaining CI/CD pipelines using Azure DevOps, Azure Pipelines, GitHub Actions, or similar tools.
  6. Experience working with AWS services, including: EC2, S3, RDS, EKS, IAM, CloudWatch.
  7. Experience with Docker and Kubernetes/containerized application deployments.
  8. Familiarity with Snowflake or comparable cloud-based data and analytics platforms.
Nice to Have:
AI engineering, AI application development, or intelligent automation experience. Candidates who have contributed to AI-enabled solutions will be highly regarded.
More about this job

Responsibilities

Design, develop, test, deploy, and support enterprise applications, APIs, and cloud-native solutions, including application modernization and production troubleshooting. Build and maintain CI/CD pipelines, infrastructure automation, and deployment frameworks to improve reliability, scalability, security, and operational efficiency.

Requirements

Requires 5+ years of experience in software development, cloud engineering, DevOps, or data engineering, including 3+ years of hands-on development with C#, .NET, Python, SQL, and Blazor or similar frameworks. Candidates should have production application and API experience, CI/CD and AWS expertise, Docker and Kubernetes experience, and familiarity with Snowflake or comparable platforms.

Skills

  • C#
  • .NET
  • Python
  • SQL
  • Blazor
  • Software Development
  • Cloud Engineering
  • DevOps
  • CI/CD
  • Infrastructure as Code
  • Azure DevOps
  • AWS
  • Docker
  • Kubernetes
  • Snowflake
  • AI Application Development

Visa sponsorship

Not detected in the job text

Categories

  • Technology
  • Software
  • Data & Analytics
  • Engineering

Keywords

  • C#
  • .NET
  • .NET Core
  • Python
  • SQL
  • Blazor
  • Software Engineering
  • Enterprise Applications
  • APIs
  • Cloud-Native Development
  • Application Modernization
  • CI/CD Pipelines
  • Infrastructure as Code
  • Azure DevOps
  • Azure Pipelines
  • GitHub Actions
  • AWS
  • EC2
  • S3
  • RDS
  • EKS
  • IAM
  • CloudWatch
  • Docker
  • Kubernetes
  • Snowflake
  • Data Engineering
  • AI Engineering
  • Intelligent Automation
  • Production Support

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