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AI Platform Engineer with DevOps Experience

  • Halifax, NS, Canada

Full-time

This opening has closed.

The original listing is kept below for reference.

Job details

Job type
Full-time
Closing date
Experience
· 2+ years of development experience in one of the following languages: Java, Python, Javascript/TypeScript, C#, C/C++, Python
Posting language
English
Posted

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Original job description

Archived listing. The details below describe a past opening.

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

· 2+ years of development experience in one of the following languages: Java, Python, Javascript/TypeScript, C#, C/C++, Python

· 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:

· Prompt Management Frameworks

· 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

More about this job

Responsibilities

Develop and integrate value-add DevOps services and CI/CD pipelines to support application teams. Design, build, and operate enterprise AI/GenAI platforms including LLMOps frameworks and reusable AI services.

Requirements

Requires 2+ years of development experience in languages such as Java, Python, or TypeScript and experience with Docker or Kubernetes. Candidates must possess an engineer mindset with strong SDLC experience and knowledge of Agile methodologies.

Skills

  • DevOps
  • CI/CD
  • Python
  • TypeScript
  • Java
  • Docker
  • Kubernetes
  • LLMOps
  • MLOps
  • RAG
  • GitHub Actions
  • Jenkins
  • Agile
  • System Design
  • Prompt Management
  • Inference APIs

Visa sponsorship

Not detected in the job text

Categories

  • Technology
  • Software
  • Data & Analytics
  • Engineering
  • Finance & Accounting

Keywords

  • AI Platform Engineer
  • DevOps
  • CI/CD
  • GitHub Actions
  • TypeScript
  • Python
  • Groovy
  • Jenkins
  • Docker
  • Kubernetes
  • Agile
  • SCRUM
  • LLMOps
  • MLOps
  • Large Language Models
  • RAG
  • Embedding
  • Vector Search
  • AI Gateway
  • Inference APIs
  • Agentic AI
  • Elastic Search
  • Kibana
  • UrbanCodeDeploy
  • Azure
  • AWS
  • Distributed Applications
  • SDLC
  • Capital Markets
  • Automation

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