Skills & Knowledge
A demonstrable AI engineering portfolio: personal projects, hackathons, open-source contributions or coursework where you have actually built something with AI, not just studied it.
Confidence to make and defend a technical judgement call, curiosity to keep exploring how the tools are changing, and enough security in your own reasoning to say when you think an AI-generated answer is wrong.
Understanding of programming fundamentals and object-oriented concepts, strong enough to read and critique AI-generated code, not just write your own.
An informed view on how the software engineer's role is shifting: less time producing code, more time specifying, evaluating and taking accountability for it.
Strong communication skills: able to explain a technical decision to an engineer and a business outcome to a product owner, in the same week.
Comfortable working in a squad, taking direction from a Forward Deployed Consultant or technical lead, and contributing across build, evaluation and delivery.
Desirable
Experience with Python or another modern language, including using AI coding assistants (such as Copilot, Claude Code or Cursor) as part of your workflow.
Exposure to agentic frameworks, specification-driven development, or evaluation and testing tooling.
Understanding of software development lifecycles and Agile delivery.
Familiarity with version control (Git), cloud platforms or APIs.
Awareness of AI governance, safety or risk concepts.
Experience gained from academic projects, internships, bootcamps or personal builds, particularly anything you can show us running.
What Success Looks Like
We grade AI fluency separately from technical seniority, using FDM's AI fluency framework: AI Aware, AI Productive, AI Operational, AI Orchestrating. Within your first year, successful graduates will:
Progress from AI Aware to AI Productive, and be working towards AI Operational.
Deliver clean, tested, production-ready code as part of a live client squad.
Specify, build and evaluate agentic and RAG-based solutions that others can trust without re-checking your work.
Apply governed, auditable engineering practice by default, not as an afterthought.
Present technical decisions clearly and confidently to both engineers and non-technical stakeholders, including product owners.
Build the track record that opens the door to specialist tracks such as Agentic AI Engineer (AI Orchestration), FDM's most senior technical capability.
You are:
Confident enough to make a technical call and stand behind it, without needing to be toldyou're right.
Curious about how AI is changing the craft of engineering, and genuinely interested in finding out rather than assuming you already know.
Secure enough to say "I don't know" or "I think this AI output is wrong", and explain why.
Collaborative, and comfortable taking direction inside a squad while still bringing your own point of view.
Committed to building a portfolio of real, working things, not just credentials.
Interested in the business problem behind the code: what it's actually for, and who it serves.