Career notes
Career notes
Field guides to AI-era job titles and transitions. The strongest pieces are source-backed analysis; some role guides are still being re-sourced before release.
Featured analysis
Will AI replace software engineers?
The short answer is no. The more useful answer is that software work is splitting: some specialties are growing, some entry paths are tightening, and the value of judgment is rising faster than the value of routine output.
What this piece covers
BLS growth projections versus the pressure showing up in junior hiring.
Which engineering tasks current AI tools help with, and which still depend on context.
What to do next if you are senior, mid-career, or still trying to break in.
AI Engineer
Applied engineers who turn model capability into stable product behavior under cost, latency, and safety constraints.
GTM Engineer
A hybrid commercial and technical role built around pipeline generation, workflow automation, and measurable revenue lift.
Vibe Coder
A developer workflow built around AI-assisted implementation, rigorous review, and unusually strong editing instincts.
Prompt Engineer
A discipline of prompt systems, evaluation loops, and behavioral tuning rather than clever wording tricks.
AI Product Manager
A product seat centered on model judgment, rollout discipline, and the economics of shipping AI features responsibly.
ML Ops Engineer
Infrastructure-heavy work focused on serving, reliability, observability, and the cost of keeping AI systems alive after launch.
AI Safety Researcher
Technical safety work built around red teaming, evaluation, policy-sensitive decision-making, and failure analysis.
Forward Deployed Engineer
Customer-facing technical delivery work for teams that need engineers in the room when messy deployments become real.
AI UX Designer
Interaction design for AI products where trust, ambiguity, and model error have to be made legible to real users.
Context Engineer
A retrieval-and-memory specialization for teams building agents or long-running AI systems that fail when context is thin or stale.
AI Solutions Engineer
Technical translation work spanning discovery, demos, proofs of concept, integrations, and the early moments of customer adoption.
Data Annotation Specialist
Entry-level AI operations work centered on labeling, quality control, rubric interpretation, and model-evaluation support.