AI Platform Engineer with DevOps Experience

Net2Source (N2S); Halifax; On-site; CAD 90,000 - 130,000; Full time

Job summary

Net2Source is seeking an AI Platform Engineer with DevOps experience to drive automation and efficiency across Capital Markets teams. The role involves building value-add DevOps services, CICD pipelines, and scaling AI/GenAI platforms for large language models.

You will mentor application teams, champion best practices, and lead tool adoption through POC cycles while evolving DevOps capabilities for cross-team delivery.

Qualifications

• SDLC experience with production delivery.
• Experience with system design patterns.
• Experience with Docker or Kubernetes.
• Experience with Agile methodologies, SCRUM.
• Design, build, and operate enterprise AI/GenAI platforms supporting LLMs and AI-powered applications.
• Develop scalable LLMOps and MLOps frameworks for model deployment, monitoring, versioning, evaluation, and governance.
• Build reusable AI services including: Retrieval Augmented Generation (RAG) architectures, Embedding and Vector Search Services, AI Gateway and Inference APIs, Agentic AI Orchestration Frameworks.

Responsibilities

• Develop value-add services which integrate with the existing DevOps stack.
• Develop CICD pipelines using GitHub Actions, TypeScript, Python, Groovy and Jenkins.
• Coach application teams on how to leverage DevOps offerings.
• Champion developer-experience and best practices in conjunction with DevOps to ensure no developer is left behind.
• Participate in new tool adoption, POC process and provide recommendations.
• Evolve DevOps services beyond current state for application teams.

Skills

SDLC experience

System design patterns

Docker

Kubernetes

Agile SCRUM

GenAI platforms

LLMOps

MLOps

RAG architectures

Vector search

Tools

Docker

Kubernetes

GitHub

GitHub Actions

Jenkins

UrbanCodeDeploy

Azure

AWS

Elastic Search

Kibana

Job description

AI Platform Engineer with DevOps Experience

6-12 months

DevOps, Docker (Software), GitHub, GitHub Actions, Information Technology (IT) Infrastructure, Kubernetes, Programming Languages, Red Hat Ansible, Software Product Design, Software Product Technical Knowledge, Software GenAI, LLM

Job Description

What is the Opportunity?

Are you looking to make an impact across many teams? Excited at the thought of transforming the flows that help these teams deliver their products to production? If so, you’ve come to the right place.

We are looking for a Developer obsessed with efficiency and automation to be part of an autonomous team to deliver services for application teams across Capital Markets. An open-minded individual who is not afraid to fail fast and pivot when needed. An individual who seeks out gaps and challenges to drive efficiency not only for other application teams but also for their own team. Knowledge sharing is key in this respect. As a Developer, you will participate in transforming DevOps for Capital Markets.

What will you do?

• Develop value-add services which integrate with the existing DevOps stack
• Develop CICD pipelines using GitHub Actions, TypeScript, Python, Groovy and Jenkins
• Coach application teams on how to leverage DevOps offerings
• Champion developer-experience and best practices in conjunction with DevOps to ensure no developer is left behind
• Participate in new tool adoption, POC process and provide recommendations
• Evolve DevOps services beyond current state for application teams

What do you need to succeed?

Must-have:

• An engineer mindset, SDLC experience with production class delivery, strong analytical mindset, communication skills, and sense of ownership / drive
• Experience with application and system design patterns
• Experience with Docker or Kubernetes
• Experience with Agile methodologies, ie SCRUM
• Design, build, and operate enterprise AI/GenAI platforms supporting Large Language Models (LLMs) and AI-powered applications.
• Develop scalable LLMOps and MLOps frameworks for model deployment, monitoring, versioning, evaluation, and governance.
• Build reusable AI services including:
  • Retrieval Augmented Generation (RAG) architectures
  • Embedding and Vector Search Services
  • AI Gateway and Inference APIs
  • Agentic AI Orchestration Frameworks

Nice-to-have:

• Experience with Elastic Search and Kibana
• Experience using DevOps CICD tools such as GitHub, GitHub Actions, Jenkins, UrbanCodeDeploy
• Experience with a public cloud technology, i.e. Azure, AWS
• Experience building or supporting distributed applications