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Junior Engineer

Remote / Online - Candidates ideally in
Trail, BC, Canada
Listing for: KOOTENAY SAVINGS CREDIT
Remote/Work from Home position
Listed on 2026-08-25
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 70000 - 88000 CAD Yearly CAD 70000.00 88000.00 YEAR
Job Description & How to Apply Below

LOCATION

Preference is for onsite work in Trail, BC however remote work in the province of British Columbia may be considered for the right candidate.

Kootenay Savings Credit Union is seeking a highly motivated and experienced Junior Engineer to join our team. In this role, you will support KSCU’s digital transformation by assisting in the development, implementation and maintenance of artificial intelligence and machine learning solutions within the credit union’s technology ecosystem. Working under the guidance of senior technical staff, this role contributes to AI-powered initiatives that enhance member experience, operational efficiency, and data-driven decision-making while ensuring compliance with regulatory obligations.

This position provides hands‑on learning opportunities in AI/ML technologies, cloud platforms, and responsible AI practices within a highly regulated financial services environment.

Some of your key responsibilities will include:

  • Assists in developing, testing, and deploying AI/ML models to support business objectives and member services.
  • Supports data collection, cleaning, preprocessing, and feature engineering activities to prepare datasets for machine learning applications.
  • Participates in prompt engineering and fine‑tuning of large language models (LLMs) and generative AI solutions.
  • Helps integrate AI solutions with existing systems including CRM platforms, core banking systems, and Microsoft technology stack through APIs and Azure services.
  • Assists in building and maintaining serverless AI workflows using Azure Functions and Durable Functions for scalable, event‑driven AI processing.
  • Assists in monitoring AI model performance, identifying anomalies, and supporting model maintenance and optimization efforts.
  • Supports the implementation of AI solutions using Azure AI services, Azure OpenAI, and other cloud‑based AI platforms.
  • Collaborates with cross‑functional teams to understand business requirements and translate them into technical AI/ML solutions.
  • Documents AI workflows, model specifications, data pipelines, and technical processes to support audit and compliance requirements.
  • Participates in code reviews and follows version control best practices using Git and Dev Ops workflows.
  • Supports compliance with Canadian data privacy and financial regulations (such as but not limited to; OSFI, SOC
    2) in all AI development activities.
  • Assists in implementing responsible AI practices including bias detection, fairness evaluation, and ethical AI principles.
QUALIFICATIONS
  • Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Mathematics, Statistics or in another discipline with a significant AI/ML or programming component, OR completion of a college program in Computer Science, Data Science, or related technical field.
  • Certifications in AI/ML, Azure AI, or related technologies are considered an asset.
  • A minimum of 2 years’ experience in software development, data science, AI/ML engineering or an equivalent combination of education and experience.
  • Academic project experience or internships involving machine learning, data analysis, or AI applications.
  • Exposure to cloud platforms (preferably Microsoft Azure) is an asset.
  • Familiarity with Agile development methodologies is preferred.
  • Experience or coursework in financial services or highly regulated industries is an asset.
Foundational proficiency required in:
  • Python programming for data science and machine learning applications.
  • Basic understanding of machine learning concepts (supervised/unsupervised learning, classification, regression, neural networks).
  • Familiarity with at least one ML framework (Tensor Flow, PyTorch, scikit-learn, or similar).
  • SQL and database fundamentals.
  • RESTful APIs and basic integration concepts.
  • Data manipulation and analysis libraries (pandas, Num Py).
  • Azure Functions for serverless computing and event‑driven architectures.
  • Understanding of Durable Functions for workflow orchestration and stateful processing.
Developing proficiency or familiarity with:
  • AI orchestration frameworks (Lang Chain, Semantic Kernal, or similar).
  • Prompt engineering and working with large language models.
  • Vector…
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