IT Solutions Architect

Aversan Inc; Montreal; Hybrid; CAD 125,000 - 150,000; Full time

Job summary

An established industry player is seeking an IT Solutions Architect to design and implement scalable IT solutions that leverage Big Data, AI, and MLOps. This role involves creating end-to-end solutions that enhance data processing and decision-making, while also mentoring teams and aligning technical strategies with business goals. The ideal candidate will have a strong background in big data platforms, AI integration, and MLOps practices, ensuring that the organization remains at the forefront of technological advancements. Join this innovative firm and contribute to impactful projects that drive business performance and efficiency.

Qualifications

• Certifications in AWS, Google Cloud, or Azure are required.
• Experience with Docker and Kubernetes for AI and MLOps workflows.

Responsibilities

• Develop scalable solutions integrating big data and AI to solve business problems.
• Establish MLOps pipelines for seamless deployment and monitoring of ML models.

Skills

Big Data

AI

MLOps

Technical Leadership

Collaboration

Education

Certifications in AWS, Google Cloud, or Azure

Tools

Docker

Kubernetes

CI/CD Tools

Job description

IT Solutions Architect

Aversan Inc. is a trusted multi-service engineering and electronics manufacturing company. Aversan delivers leading-edge and reliable safety-critical electronics and software systems to the aerospace, defence, and space industries.

We are currently seeking a qualified IT Solutions Architect. The role involves designing and implementing scalable IT solutions that integrate Big Data, AI, and MLOps, enabling efficient data processing, AI-driven insights, and streamlined machine learning operations for optimized business performance.

Location: St. Laurent, QC

Job Type: Hybrid

Responsibilities

1. Architecture Design: Develop scalable, end-to-end solutions that integrate big data and AI to solve complex business problems.
2. Big Data Expertise: Provide technical guidance on big data platforms, covering ingestion, storage, processing, and analytics.
3. AI Integration: Architect AI-powered solutions by implementing machine learning and deep learning models to enhance decision-making and automation.
4. MLOps Implementation: Establish and maintain MLOps pipelines for seamless deployment, monitoring, and lifecycle management of ML models in production.
5. Collaboration: Work closely with data scientists, engineers, and business stakeholders to align technical solutions with business objectives.
6. Technical Leadership: Mentor teams and promote best practices in big data, AI, and MLOps adoption.
7. Continuous Learning: Stay updated with emerging technologies and assess their relevance for improving business operations.

Basic Qualifications

1. Certifications in relevant areas such as AWS Certified Solutions Architect, Google Cloud Professional Data Engineer, or Microsoft Certified: Azure AI Engineer Associate.
2. Experience with containerization technologies such as Docker and Kubernetes, and their application in AI and MLOps workflows.
3. Knowledge of DevOps practices and tools for continuous integration and deployment (CI/CD).