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Generative Ai Developer Jobs in Alberta (NOW HIRING)

Modular Solutions

Software Developer

Calgary, AB

AI is now a standard part of modern software development. At Modular Solutions, we expect engineers to be comfortable using generative AI tools as part of their daily workflow and to apply strong ...

Modular Solutions

Software Developer

Calgary, AB · On-site

AI is now a standard part of modern software development. At Modular Solutions, we expect engineers to be comfortable using generative AI tools as part of their daily workflow and to apply strong ...

Kyndryl

Senior Data & AI Consultant

Calgary, AB

Oversee delivery of end-to-end engagements spanning data engineering, machine learning, generative AI, and intelligent automation . * Ensure engagement quality, business alignment, and client ...

Lantern

Power Platform Developer

Edmonton, AB · Remote

... understanding of generative AI applications in business process automation. Familiarity with ... The position operates within an Agile remote software engineering team, requiring proficiency with ...

AssetWorks

Senior Full-Stack Developer

Calgary, AB

We are looking for a Senior Full-Stack Developer to lead the technical realization of our generative AI roadmap. In this role, you won't just be using AI to write code; you will be building the AI ...

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Kyndryl

Data & AI Architect

Calgary, AB

CA$118.70K - CA$168.70K/yr

Generative AI: LLM integration, RAG, vector databases (e.g., Pinecone, FAISS), prompt engineering. * MLOps/LLMOps frameworks: MLflow, Kubeflow, or similar. * Strong foundation in data architecture ...

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Generative Ai Developer information

What are the key skills and qualifications needed to thrive as a Generative AI Developer, and why are they important?

To thrive as a Generative AI Developer, you need strong programming skills (especially in Python), a deep understanding of machine learning concepts, and an advanced degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and experience with cloud platforms or model deployment tools are typically required. Creative problem-solving, adaptability, and effective collaboration are standout soft skills in this evolving field. These abilities are crucial to design, implement, and refine generative models that solve real-world problems and drive innovation.

What are some common challenges faced by Generative AI Developers when deploying models in production environments?

Generative AI Developers often encounter challenges such as ensuring model reliability, managing computational resource requirements, and addressing ethical considerations like data bias or content safety. Deploying generative models at scale requires robust monitoring to detect unexpected outputs or model drift, and collaboration with data engineers and product teams to optimize performance. Staying up-to-date with evolving frameworks and best practices is essential, as production environments demand both technical rigor and adaptability to new AI advancements.

What is a Generative AI Developer?

A Generative AI Developer is a technology professional who specializes in designing, building, and deploying artificial intelligence systems that can create new content, such as text, images, audio, or code. They work with advanced machine learning models, like generative adversarial networks (GANs) or large language models, to enable computers to produce original outputs. These developers often collaborate with data scientists, researchers, and product teams to integrate AI-generated content into software applications and business solutions.

What is the difference between Generative Ai Developer vs Machine Learning Engineer?

AspectGenerative Ai DeveloperMachine Learning Engineer
CredentialsBachelor's or higher in CS, AI, or related fields; experience with deep learning frameworksBachelor's or higher in CS, Data Science, or related fields; strong programming skills
Work EnvironmentDevelops AI models for content creation, chatbots, and creative applicationsBuilds and deploys ML models for various data-driven solutions across industries
Industry UsageTech, entertainment, marketing, and creative sectorsFinance, healthcare, tech, and e-commerce sectors

While both roles involve AI and machine learning, Generative Ai Developers focus on creating models that generate content, such as images or text, whereas Machine Learning Engineers develop broader ML solutions for diverse applications. The roles often overlap but differ mainly in their specific focus areas and use cases.

What are popular job titles related to Generative Ai Developer jobs in Alberta? For Generative Ai Developer jobs in Alberta, the most frequently searched job titles are:
What job categories do people searching Generative Ai Developer jobs in Alberta look for? The top searched job categories for Generative Ai Developer jobs in Alberta are:
Generative Ai Developer jobs near you
Infographic showing various Generative Ai Developer job openings in Alberta as of May 2026, with employment types broken down into 31% Full Time, 65% Part Time, and 4% Contract. Highlights an 80% Physical, 1% Hybrid, and 19% Remote job distribution.

Generative AI Developer - Microsoft Azure AI Stack

Lantern

Calgary, AB

Other

Posted 18 days ago

Job description

Key Responsibilities
We are looking for a hands-on Generative AI Developer with strong experience in building intelligent applications using the Microsoft Azure AI stack. As part of a Microsoft partner consultancy, you will work on developing and deploying cutting-edge AI solutions powered by Azure OpenAI, Azure AI Foundry, LangChain, LangGraph, and Retrieval-Augmented Generation (RAG).
This role is ideal for a developer who thrives in a fast-paced environment and is passionate about building real-world applications with large language models (LLMs), agent-based workflows, and scalable AI infrastructure.
Skills, Knowledge and Expertise

   Develop and deploy Generative AI applications using: 
   Azure OpenAI Service (GPT models, embeddings, fine-tuning)
   Azure AI Foundry for managing LLM lifecycle and deployment
   LangChain and LangGraph for orchestrating multi-agent and multi-step workflows
   RAG pipelines using Azure AI Search and vector databases
   AI agents and MCP servers for task automation and reasoning
   Implement prompt engineering strategies and optimize LLM interactions.
   Build APIs and microservices to integrate AI capabilities into enterprise applications.
   Collaborate with architects and client teams to understand requirements and deliver solutions.
   Ensure code quality, performance, and security in cloud-native environments.
   Stay up to date with the latest in generative AI frameworks, tools, and best practices.

Required Qualifications:

   Bachelor's degree in Computer Science, Engineering, or related field.
   3+ years of experience in software development, with a focus on AI/ML applications.
   Hands-on experience with Azure OpenAI, LangChain, and LangGraph.
   Solid understanding of LLM orchestration, agent frameworks, and RAG architectures.
   Proficiency in Python and experience with cloud-native development.
   Familiarity with Azure services such as Azure Functions, Azure AI Search, Azure Storage, and containerization (Docker/Kubernetes).
________________________________________

What We Offer:


   Opportunity to build impactful generative AI solutions for enterprise clients.
   Access to exclusive Microsoft partner resources and training.
   A collaborative, innovative, and growth-oriented work environment.
   Competitive compensation and benefits.
   Career development in a rapidly evolving AI landscape.

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