Intern Software Engineer

Overall Purpose of the Role

Summary of the role; overall role contribution to team, department and organisation

As a Software Engineering Intern at Fergus, you'll be responsible for contributing real, shipping work to a live AI feature development project. You'll join a cross-functional team of Product, Design and Engineering and work inside our Shape Up delivery cycles, from shaping through to building and shipping, rather than sitting on a side project set apart from the real work.

You'll partner closely with an assigned senior engineer mentor and the wider engineering team, learning how to use AI coding assistants effectively inside a production codebase: prompting them well, reviewing and validating what they produce, and building features that call LLMs directly, including handling the cases where they get it wrong. You'll also help automate existing workflows using AI tooling.

Areas of Responsibility

Key elements and required results of the role

• Contribute across a full Shape Up cycle (shaping, betting, building and shipping) as a working member of a cross-functional Product, Design and Engineering team
• Use AI coding assistants to build features inside Fergus's production codebase, applying judgement on what to trust, verify or rewrite
• Build AI-facing product features, including prompt design, integrating LLM APIs, and handling failure cases where AI output is wrong or incomplete
• Automate existing internal workflows using AI tooling
• Contribute to and help maintain Fergus's shared prompt library and evaluation practices
• Participate in peer coding sessions and pull request reviews, both giving and receiving feedback
• Escalate ambiguity, risk or uncertain AI output to your mentor rather than guessing
• Write clear documentation of what you build and why, for both internal use and the benefit of future interns

Experience and Professional Qualifications Required

Number of years' experience, Qualifications and People Management experience

• In the final year of an undergraduate or postgraduate engineering, computer science or related degree, on track to graduate
• Some hands-on coding experience through coursework, personal projects or prior internships, in any language
• Genuine curiosity about AI-assisted software development; prior use of AI coding tools is not required, desirable
• Right to work in New Zealand for the full duration of the internship
• Prior internship, part-time or vacation work experience desirable
• Exposure to agile or iterative delivery methods desirable

Skills Required

Highlighting the key technical, language and job-related skills required

• AI Usage & Application:
  • Baseline (preferred): comfortable using AI coding assistants for their own work, iterating on prompts and treating output as a draft to check rather than a finished answer.
  • Intermediate (strongly preferred): some experience using AI tools for debugging, testing, or documentation.
• Problem Solving & Code Fundamentals: Can reason about how software works end to end, from database through to UI, regardless of which language this was learned in.
• Written Communication: Documents what they've built clearly enough for a teammate, or a future AI agent, to pick up and continue.
• Collaboration & Feedback: Comfortable giving and receiving direct feedback through peer coding and pull request reviews.

How: Enablement

• Learns primarily by working alongside senior engineers through peer coding, PR review and weekly 1:1s, not by being left to self-teach
• Communicates clearly with both technical and non-technical teammates (Product, Design) inside their Shape Up cycle
• Operates under Fergus's "No Heroes" value: writes things down, shares work in progress openly, and asks for help early rather than struggling silently

Competencies Required

• Comfort with Ambiguity: Works well with a specification that isn't fully defined yet, and knows when to ask rather than guess.
• Customer-Centric Thinking: Understands that features are ultimately for tradies doing their jobs, not for the elegance of the code.
• Written Communications: Documents decisions and questions clearly enough for a mentor or teammate to follow without re-explanation.
• Responsible AI Judgement: Applies critical thinking to AI-generated output: knows where it can be trusted, where it needs verification, and when to escalate. Aware that AI tools carry evolving regulatory and ethical considerations.
• Opportunity-Seeking Mindset: Looks for ways to improve or automate existing workflows, not just complete assigned tasks.
• Strong Interpersonal Skills: Builds genuine working relationships with engineers, designers and product people inside a small cross-functional team.