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Gen Ai Software Developer Jobs in Edmonton, AB (NOW HIRING)

What you'll do As a Data Scientist, you'll work closely with stakeholders and software engineers to ... Develop analytical models and leverage AI capabilities to support strategic decision-making and ...

... digital AI inference chip. We are seeking an experienced Compiler Engineer to join our exceptional team. Responsibilities: * Design and implement software that maps neural nets onto our spatial ...

... digital AI inference chip. We are seeking an experienced Compiler Engineer to join our exceptional team. Responsibilities: * Design and implement software that maps neural nets onto our spatial ...

... AI innovation. As part of Teledyne Technologies-a global leader in enabling technologies for ... Experience with CAD software for generating drawings of BE fixtures and tooling * Working knowledge ...

Proficiency in programming tools such as RSLogix5000 Studio, FT View, and other control software ... Using AI capabilities, we analyze your application for relevant skills, experiences, and ...

Support pilot deployments of AI enabled manufacturing optimization, digital work instructions, and ... software * Strong troubleshooting skills and a mindset capable of driving tasks to completion

Showing results 41-60

Gen Ai Software Developer information

How do Gen AI software developers typically collaborate with data scientists and product managers during the development process?

Gen AI Software Developers regularly work alongside data scientists to translate machine learning models into scalable, production-ready applications. They collaborate closely with product managers to understand user requirements and ensure that AI-powered features align with business goals. This teamwork often involves participating in cross-functional meetings, iterative feedback cycles, and joint problem-solving sessions to address technical challenges and optimize model performance. Clear communication and a shared understanding of project objectives are essential for success in this collaborative environment.

What are the key skills and qualifications needed to thrive as a Gen AI software developer, and why are they important?

To thrive as a Gen AI Software Developer, you need strong programming skills (especially in Python), a background in computer science or a related field, and expertise in machine learning and deep learning principles. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud platforms (such as AWS or Azure), and knowledge of version control systems are typically required, along with certifications in AI or data science being advantageous. Creative problem-solving, collaboration, and effective communication help developers work across technical and non-technical teams and drive innovation. These skills ensure the development of robust, scalable AI solutions that address real-world needs and integrate seamlessly within organizations.

What is a Gen AI software developer?

A Gen AI Software Developer is a professional who designs, builds, and maintains software systems that leverage generative artificial intelligence models, such as large language models (LLMs) or generative adversarial networks (GANs). Their work often involves training, fine-tuning, and deploying AI models to generate content, automate tasks, or enhance user experiences in applications. They need strong programming skills, a solid understanding of machine learning principles, and familiarity with AI frameworks. Gen AI Software Developers collaborate with data scientists, engineers, and product teams to deliver innovative AI-driven solutions. As generative AI becomes more prevalent, these developers play a key role in shaping the future of software development.

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

AspectGen Ai Software DeveloperMachine Learning Engineer
Required CredentialsBachelor's in CS, AI, or related; experience with AI frameworksBachelor's or higher in CS, Data Science, or related; strong programming skills
Work EnvironmentTech companies, startups, AI-focused teamsResearch labs, tech firms, AI/ML departments
Employer & Industry UsageAI product development, software solutionsModel development, data analysis, AI system deployment
Common Search & ComparisonFocuses on AI application development in softwareFocuses on building and optimizing ML models

While both roles involve AI and require programming skills, Gen Ai Software Developers primarily focus on creating AI-powered software applications, whereas Machine Learning Engineers specialize in designing, building, and optimizing machine learning models. The roles often overlap but differ in their core focus and typical work environments.

What are popular job titles related to Gen Ai Software Developer jobs in Edmonton, AB? For Gen Ai Software Developer jobs in Edmonton, AB, the most frequently searched job titles are:
Infographic showing various Gen Ai Software Developer job openings in Edmonton, AB as of August 2026, with employment types broken down into 88% Full Time, 8% Part Time, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Data Engineer - Intermediate (REMOTE) JP975

P@thlion Staffing Careers

Edmonton, AB โ€ข Remote

Full-time

Posted 18 days ago


Job description

Project Name:

Digital Regulatory Assurance System

Scope:

Modernization initiatives across the Government of Alberta are fundamentally changing how ministry users collect, manage, analyze, and use data as legacy systems are transformed into modern Data Management and Geospatial Platforms. This shift requires dedicated analytical capacity to ensure that the value of modernized data assets is fully realized.

DRAS is a Government of Alberta regulatory transformation initiative led by Environment and Protected Areas (EPA) to modernize, digitize, and streamline environmental and natural resource regulatory processes. DRAS supports the full regulatory lifecycle, from application and authorization to monitoring, compliance, remediation, and closure through a single, consolidated digital platform

As DRAS development continues, the volume, variety, and complexity of structured data continue to grow, creating a sustained need for dedicated data engineering and data product expertise. The Data Product Analyst role is critical to ensuring that modernization delivers tangible business value. This role will design, build, and operate reliable data pipelines that ingest and integrate data into the DMP, apply standardized transformations, enforce data quality and governance controls, and produce trusted, analytics‑ready datasets that support regulatory oversight, compliance monitoring, and evidence‑based decision‑making aligned with DRAS objectives.

This position will primarily support the Digital Regulatory Assurance System (DRAS) program, where high quality, timely analytics are essential to regulatory and compliance functions. As data and analytics maturity increases, the role may be expanded to support additional enterprise data initiatives.

Duties:

  • Design and implement scalable, secure, and high-performance data architecture on Microsoft Azure, supporting both cloud-native and hybrid environments.
  • Lead the development of data ingestion, transformation, and integration pipelines using Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
  • Work with the Data Architect and manage data lakes and structured storage solutions using Azure Data Lake Storage Gen2, ensuring efficient access and governance.
  • Integrate data from diverse source systems including ServiceNow, and geospatial systems, using APIs, connectors, and custom scripts.
  • Develop and maintain robust data models and semantic layers to support operational reporting, analytics, and machine learning use cases.
  • Build and optimize data workflows using Python and SQL for data cleansing, enrichment, and advanced analytics within Azure Databricks.
  • Design and expose secure data services and APIs using Azure API Management for downstream systems.
  • Implement data governance practices, including metadata management, data classification, and lineage tracking.
  • Ensure compliance with privacy and regulatory standards (e.g., FOIP, GDPR) through role-based access controls, encryption, and data masking.
  • Monitor and troubleshoot data pipelines and integrations, ensuring reliability, scalability, and performance across the platform.
  • Utilize AI and automation tools to streamline data engineering workflows, including pipeline development, testing, monitoring, and documentation.
  • Leverage AI-assisted tools for code generation, optimization, and review to improve development efficiency and code quality.
  • Design and curate standardized, high‑quality datasets that are suitable for advanced analytics and future AI use cases.
  • Other duties as needed