Ai Software Engineer Intern Jobs in Edmonton, AB

Full Stack Feature Delivery

• Implement features end-to-end across front-end, back-end, and cloud infrastructure layers, taking ownership from design through deployment

• Build and integrate RESTful APIs and cloud-hosted services, primarily on Azure, following established architecture patterns and security standards

• Develop front-end components using modern JavaScript/TypeScript frameworks, with attention to usability, performance, and maintainability

• Write unit, integration, and API tests as a standard part of delivery - not an afterthought - using frameworks appropriate to the stack (xUnit, Pytest, Postman, or similar)

• Use Docker for local development, environment parity, and containerized deployments

• Manage work in Git with clean branching, meaningful commit history, and effective collaboration with AI agents in the same workflow

LLM Feature Development

• Build features that incorporate LLM calls via the Claude API or Azure OpenAI, including prompt design, context management, response handling, and cost-aware API usage

• Implement RAG components and tool integrations as part of product features, working within established architecture patterns and contributing to their evolution

• Write evaluation harnesses for LLM-powered features: regression tests for prompt behaviour, output quality checks, and agent tool use validation

• Document LLM feature behaviour clearly: what the system does, what it does not do, known failure modes, and the guardrails in place

• Develop growing awareness of when LLM-in-the-loop is the right architecture decision versus a conventional software approach - and contribute that perspective in design discussions

Technical Design & Problem-Solving

• Participate actively in epic-level and feature-level design discussions, contributing well-reasoned proposals backed by research or prototype evidence

• Use Claude to accelerate technical research: explore design alternatives, evaluate libraries, and investigate unfamiliar domains quickly - then synthesize findings into a clear recommendation

• Identify and flag technical risks within your work scope early, with enough supporting detail for the tech lead or architect to make an informed decision

• Produce clear technical documentation: decision records, implementation notes, and design summaries that a future team member can act on

AI-Native Development

• Use Claude Code and AI-assisted development tools (Cursor, GitHub Copilot, and similar) as a standard part of the engineering workflow - for prototyping, code generation, refactoring, documentation, and debugging

• Write clear, well-structured prompts and development specs that enable AI agents to produce useful, reviewable output - not vague instructions that generate noise

• Review AI-generated code with the same rigour as human-authored code: check for correctness, edge cases, security issues, and maintainability before merging

• Develop growing fluency in agentic development patterns: structuring repos for agent navigation, decomposing tasks into agent-friendly units, and knowing when human authorship is the right call

• Contribute to internal discussions on AI tooling effectiveness - share what is working, what isn't, and help refine the team's approach

Collaboration & Growth

• Participate in code reviews constructively - give specific, actionable feedback and incorporate peer feedback into your own work without defensiveness

• Collaborate closely with ML engineers, data engineers, and product managers within the pod, understanding adjacent work well enough to minimize integration friction

• Contribute reusable components, utilities, and internal skills to AltaML's shared libraries

• Engage in sprint ceremonies, stand-ups, and retrospectives as an active team member - raise blockers early, communicate progress clearly, and contribute to continuous improvement

• Proactively seek feedback from peers and tech leads to accelerate your own growth toward senior-level ownership and technical leadership

• Degree or equivalent work experience in Computer Science, Software Engineering, or a related technical discipline

• 3-5 years of professional full stack development experience, with a track record of shipping production features end-to-end

• Hands-on, daily-driver experience using Claude (Claude Code, claude.ai, or the Claude API), Cursor, or GitHub Copilot for real software engineering work - not just occasional use

• Strong working experience with cloud services, ideally Azure (Functions, App Service, Blob Storage, Azure OpenAI, or similar)

• Proficiency in a modern object-oriented language - C#, Python, TypeScript, or equivalent - with a clear point of view on writing clean, maintainable code

• Experience building and consuming RESTful APIs and integrating third-party services

• Solid front-end experience with a modern JavaScript/TypeScript framework (React, Vue, Angular, or similar)

• Experience writing unit and API tests as a standard part of delivery (xUnit, Pytest, Postman, or similar)

• Comfortable with Docker for local development and containerized deployments

• Proficiency with Git, including working effectively in a branch-based workflow alongside AI agents

• Experience working in an Agile environment with iterative delivery cycles

• Strong written and verbal communication skills - able to articulate technical decisions clearly to peers and participate confidently in client-facing discussions

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