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Open nowPosted 38 days ago

Intermediate AI Engineer

price65 open roles

Where
Winnipeg, MB, Canada
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Your applicationOpen nowIntermediate AI Engineerprice · Winnipeg, MB, Canada

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The clock on this job

Early applications get read.

7.8% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 1.7%1 day
  2. 3.5%3 days
  3. 7.8%7 days
  4. 14.6%14 days
  5. 34.1%30 days
This job: posted 38 days ago

The posting

Position Summary Join our AI team as an Intermediate AI Engineer, where you'll build and deploy AI applications, agents, and automation solutions that solve real business problems. You'll work closely with business and technology teams to bring these solutions from concept to production, creating measurable impact across the organization. Key Responsibilities

Design, develop, and deploy AI applications, from proof of concept through production. Build ML, deep learning, and generative AI models to solve specific business problems. Develop AI agents and intelligent workflow automations that orchestrate tools, APIs, and decision logic. Integrate AI solutions with enterprise systems, applications, APIs, and data sources. Partner with business stakeholders to translate requirements into technical solutions. Evaluate, monitor, and optimize models and applications for performance, reliability, and scalability. Document technical designs and contribute to AI development standards and best practices. Track emerging AI technologies and recommend solutions aligned with business objectives.

Qualifications Required

Bachelor's degree in Computer Science, Software Engineering, Information Technology, Data Science, or a related field. 3-5 years of experience in AI, machine learning, agentic AI, and workflow automation. Experience developing applications, APIs, and system integrations. Strong analytical, problem-solving, and communication skills. Ability to manage multiple initiatives and work effectively across cross-functional teams. Knowledge of AI governance, security, and responsible AI practices.

Technical Skills

Languages & Core ML: Python, Machine Learning, Deep Learning, Generative AI LLMs & Agentic AI: LLM Development, Prompt Engineering, RAG, AI Agent Frameworks (LangChain, LangGraph), Multi-Agent Orchestration, Fine-Tuning ML/DL Frameworks: PyTorch, TensorFlow, Scikit-learn, Hugging Face Transformers Microsoft Azure AI Stack: Azure OpenAI Service, Azure AI Studio, Azure Machine Learning, Azure AI Search, Azure Functions Data & Retrieval: Vector Databases, Semantic Search, Embeddings, Data Pipelines Integration & APIs: REST APIs, Webhooks, Enterprise System Integrations DevOps & Deployment: Docker, Azure DevOps, Git, CI/CD, MLOps

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