Choose the gap that matches your background
| Starting point | Likely advantage | Likely gap to close |
|---|---|---|
| Software engineer | Production code and system design | Customer discovery, ROI, ambiguous scoping |
| ML or AI engineer | Models, data, evaluation | Enterprise integration and stakeholder ownership |
| Data engineer | Integration, pipelines, messy systems | Product judgment and user adoption |
| Solutions engineer or architect | Customer communication and architecture | Sustained production-code ownership |
| Consultant | Ambiguity, executive communication, delivery | Hands-on engineering depth |
| New graduate | Learning speed and flexibility | Production scars and credible customer evidence |
A four-part roadmap
- Clear the engineering floor
Be able to build and debug a small service, work in an unfamiliar codebase, design an integration, use SQL, reason about APIs and data flow, and explain reliability tradeoffs. For AI-facing roles, add retrieval, tool use, evaluations, guardrails, observability, cost, and deployment. Start with AI Systems.
- Learn the customer lifecycle
Practice turning a feature request into a user, workflow, constraint, measurable outcome, first release, adoption plan, and handover. The Customer Outcomes section teaches the complete arc.
- Create production evidence
Add one real user, one real constraint, one quality measure, and one operational responsibility to work already in motion. A simple integration used by a real team is stronger than a sophisticated demo no one depends on. Use Build the Evidence to plan the work and keep a decision log.
- Prepare for the actual loop
Clear the coding floor, then concentrate on decomposition, customer pushback, unfamiliar code, production system design, and company-specific motivation. The Interview Guide maps the signals and the practice section supplies timed drills.
What current employers signal
Employer requirements vary. OpenAI's public FDE description emphasizes end-to-end ownership from discovery and scoping through build and production rollout; Anthropic's Applied AI role emphasizes customer embedding, ambiguity, and production artifacts in the customer's ecosystem. Re-check the live postings because titles, experience bands, and team structures change. OpenAI careers · Anthropic careers.
NextFDE Resume Guide