Private Draft

The 29 personas behind AI

We’ve organized every stage and persona in the AI supply chain, informed by real recruiting at frontier companies. Click any row to see matching profiles from our talent graph.

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Developer Experience

Makes engineers build faster

Developer Experience

Summary

Known as: DevEx Engineer, Developer Infrastructure Engineer, SDK Engineer, Developer Productivity Engineer, Software Engineer, DevX

Builds the tooling and infrastructure that makes engineers productive: internal dev environments, build systems, CI/CD, SDKs, APIs, and AI-powered development workflows. The function spans internal developer infrastructure (making the org's own engineers faster) and external developer surfaces (making the platform usable to outside developers).

Specializations

Internal Developer Infrastructure — Build systems, CI/CD pipelines, dev environments, toolchain management, and productivity metrics. Keeps compilers, drivers, and frameworks current across heterogeneous hardware (GPU, TPU, custom accelerators). Surfaces bottlenecks through dashboards and automation, and systematically eliminates friction from engineering workflows. At AI companies, includes specialized concerns: accelerator toolchains, multi-hardware dev environments, and the testing infrastructure for model-serving code.

AI-Powered Dev Tooling — Builds AI agents and workflows into the software development lifecycle: code generation, automated review, intelligent diagnostics for build failures and deployment issues, and agent-driven engineering platforms. A rapidly growing sub-function as companies embed AI into their own internal tooling. Designs for human-only, agent-only, and hybrid workflows where the hard problem is balancing capability with control and trust.

SDKs, APIs & Platform Interfaces — Client libraries, API design, CLI tools, developer-facing workspaces, and the surfaces that determine how engineers (internal or external) interact with AI platforms. Owns ergonomics: sensible defaults, clear error messages, type safety, and versioning that doesn't break consumers. At AI platform companies, includes prompt playgrounds, eval runners, and model comparison tools.

Where the Work Lives

[1]Substrate

[2]Compute

[3]Intelligence

[4]Systems

Primary

Builds SDKs, APIs, and internal tooling that makes AI systems usable for other engineers.

[5]Distribution

Secondary

Drives developer adoption through ergonomics, documentation, and integration patterns.

Candidate Archetypes