Artificial Intelligence Engineer

Role: AI Platform Engineer

Location: Halifax, NS

Duration: Long Term Contract

Job Description

We are looking for an experienced AI Platform Engineer to design, build, and maintain scalable infrastructure and platforms that support AI/ML workloads, Generative AI applications, and agentic AI solutions. The ideal candidate will have strong experience in cloud infrastructure, Kubernetes, MLOps/LLMOps, automation, and deploying AI models and services into production environments.

Key Responsibilities

• Design, build, and maintain scalable AI platforms supporting machine learning, Generative AI, and LLM-based applications.
• Develop and manage cloud-native infrastructure using AWS, Azure, or GCP.
• Deploy, manage, and scale AI workloads using Docker, Kubernetes, and container orchestration technologies.
• Build and maintain CI/CD pipelines for AI model deployment, application releases, and infrastructure automation.
• Implement MLOps and LLMOps practices for model lifecycle management, versioning, deployment, monitoring, and continuous improvement.
• Support the deployment and integration of LLMs, RAG pipelines, vector databases, and AI agent frameworks.
• Automate infrastructure provisioning and configuration management using Terraform, Ansible, or similar tools.
• Establish monitoring, logging, observability, security, and governance standards for AI platforms.
• Optimize platform performance, scalability, reliability, and cloud infrastructure costs.
• Collaborate with data scientists, ML engineers, AI developers, and DevOps teams to deliver production-ready AI solutions.
• Implement access controls, secrets management, data protection, and responsible AI platform practices.

Required Skills

• Strong experience in platform engineering, DevOps, cloud engineering, or ML infrastructure.
• Hands-on experience with AWS, Azure, or GCP.
• Proficiency in Kubernetes, Docker, and containerized application deployment.
• Experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI/CD, or Azure DevOps.
• Infrastructure as Code experience using Terraform, CloudFormation, or equivalent tools.
• Knowledge of Python and scripting for automation.
• Experience with MLOps/LLMOps tools and AI model deployment workflows.
• Understanding of LLMs, Generative AI, RAG architectures, embeddings, and vector databases.
• Experience with monitoring and observability tools such as Prometheus, Grafana, ELK, or cloud-native monitoring services.
• Strong understanding of networking, IAM, security, and production system reliability.