AI Platform Engineer - DevOps

Résumé du poste

Design and maintain value-add automation tools and services that integrate with the existing DevOps stack. Optimize CI/CD pipelines and coach internal application teams to improve developer experience and systemic efficiency.

Détails du poste

Staffinity is currently seeking an AI Platform Engineer - DevOps for a premier corporate client located in Halifax. This is a full-time position offering a competitive salary and comprehensive enterprise benefits package. The base salary range is 100-120 + benefits, RRSP matching, vacation and personal days. This is a hybrid position, up to 3 days per week in office. Our client is an innovative digital engineering ecosystem focused on building high-performance, efficient, and automated platform services. Rather than managing manual infrastructure operations, this role is explicitly focused on developing value-add services that integrate with an existing DevOps stack, championing developer experience, and accelerating CI/CD pipeline automation within an autonomous engineering environment. Ideal Candidate Profile: We are looking for an outside-the-box, automation-obsessed engineer who resists a restricted corporate framework and thrives on driving systemic efficiency. The ideal candidate has an engineering mindset, strong analytical skills, and loves creating tools that make life easier for cross-functional application teams. Responsibilities DevOps Service Development: Design, build, and maintain value-add services and automation tools that integrate seamlessly with the existing core platform stack. Pipeline Optimization & Engineering: Programmatically develop and scale robust CI/CD pipelines utilizing GitHub Actions, TypeScript, Python, Groovy, and Jenkins. Developer Experience Championing: Guide and coach internal application teams on how to leverage automated DevOps offerings, ensuring seamless adoption and zero friction. Tool Evaluation & Innovation: Actively participate in new tool adoption, proof-of-concept (POC) execution, and provide strategic recommendations to evolve platform services beyond current states. Agile & SDLC Collaboration: Work within high-performing SCRUM teams to deliver production-class software with a strong sense of ownership and drive. Qualifications Education: Degree or diploma in Computer Science, Software Engineering, or a related technical field. Experience: 2+ years of rigorous development experience within a production-class software delivery environment. Programming Prowess: Strong coding background with a proven track record in at least one of the following languages: Java, Python, JavaScript/TypeScript, C#, or C/C++. Containerization & Architecture: Direct practical experience handling application and system design patterns using Docker or Kubernetes. Methodology: Solid background working within structured Agile (SCRUM) delivery frameworks. Tools & Infrastructure: Familiarity with public cloud technologies (AWS or Azure), Elastic Search, Kibana, Jenkins, GitHub Actions, UrbanCode Deploy, or Ansible.

Ce que vous ferez

Design and maintain value-add automation tools and services that integrate with the existing DevOps stack. Optimize CI/CD pipelines and coach internal application teams to improve developer experience and systemic efficiency.

Exigences

Requires a degree or diploma in Computer Science or a related field with 2+ years of production-class software development experience. Proficiency in languages like Java or Python and practical experience with containerization tools like Docker or Kubernetes is essential.

Avantages

• Enterprise benefits package • RRSP matching • Vacation • Personal days

Compétences indiquées

• TypeScript · Souhaitée

Autres compétences pertinentes

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• DevOps
• CI/CD Pipeline Automation
• GitHub Actions
• TypeScript
• Python
• Groovy
• Jenkins
• Docker
• Kubernetes
• AWS
• Azure
• Elastic Search
• Kibana
• UrbanCode Deploy
• Ansible
• Agile SCRUM

Domaines d’emploi

• Software
• Technology
• Engineering
• Data & Analytics
• Consulting