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Intern, AI & Software Engineering

Job in Calgary, Alberta, D3J, Canada
Listing for: Aker
Apprenticeship/Internship position
Listed on 2026-10-05
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Backend Developer, Python, Software Engineer
Salary/Wage Range or Industry Benchmark: 70000 - 100000 CAD Yearly CAD 70000.00 100000.00 YEAR
Job Description & How to Apply Below

Aker is seeking a Software & AI Engineer Intern/Co-op to join its AI & Platform Engineering team. This role will contribute to the design, development, and operation of production-grade software, data, and artificial intelligence systems that support intelligent decision-making and automation across the firm.

The position combines full-stack software engineering with applied AI development. Interns and co-op students will work on large language model applications, agentic workflows, internal platforms, data pipelines, APIs, and user-facing tools.

This opportunity is designed for students who want to build and own real systems end-to-end—from raw data ingestion and backend services to retrieval systems, AI orchestration layers, and polished frontend experiences. Team members contribute to live, production-facing initiatives that directly impact firm operations rather than isolated research, classroom exercises, or demonstration projects.

Responsibilities

Software Engineering

  • Design, build, test, and maintain production-grade software applications and internal tools.
  • Develop backend services, REST APIs, data models, and application integrations.
  • Build responsive and intuitive user interfaces using modern frontend frameworks.
  • Write clean, maintainable, and well-tested code following established software engineering practices.
  • Debug application issues, improve performance, and contribute to system reliability.

LLM and Agentic Systems

  • Build and enhance LLM-powered applications, including retrieval-augmented generation pipelines, tool-using agents, and structured-output systems.
  • Develop agentic workflows that can plan, reason, and execute tasks across internal tools and data sources.
  • Integrate models and APIs from providers such as OpenAI and Anthropic.
  • Contribute to the evaluation, monitoring, and continuous improvement of AI system accuracy, reliability, and performance.

Data and Retrieval Infrastructure

  • Develop scalable pipelines for ingesting, transforming, indexing, and retrieving structured and unstructured data.
  • Work with SQL databases, vector databases, embeddings, and retrieval strategies.
  • Improve data quality, schema design, validation, and governance practices that support software and AI applications.
  • Optimize systems for relevance, accuracy, latency, and operational reliability.

Platforms and Integrations

  • Evaluate and integrate software libraries, LLM frameworks, orchestration tools, and third-party services.
  • Build reusable platform components that support AI workflows and internal applications.
  • Contribute to architectural decisions involving scalability, security, maintainability, and system performance.
  • Support deployment, monitoring, and ongoing operation of production-facing systems.

Ownership and Documentation

  • Own discrete features, services, or system components from design through implementation, deployment, and iteration.
  • Collaborate with engineers and business stakeholders to translate operational needs into technical solutions.
  • Document system architecture, technical decisions, experiments, APIs, and operational behavior.
  • Participate in code reviews and contribute to shared engineering standards and best practices.
Minimum Qualifications
  • Currently in the third or fourth year of a degree program in Computer Science, Software Engineering, Mathematics, Physics, or a related technical discipline.
  • Familiarity with:
    • REST APIs
    • Backend frameworks such as FastAPI, Flask, or Express
    • Modern frontend frameworks such as React or Next.js
    • Git-based development workflows
    • Software testing, debugging, and profiling techniques
  • Solid understanding of:
    • Data structures
    • Algorithms
    • Object-oriented or functional programming concepts
    • Core software engineering principles
  • Experience working programmatically with data using:
    • SQL
    • Python…
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