AI Builders. Horizontal across every function.

Builds agents and AI-powered workflows inside marketing, campaign generation, segmentation, content ops, ad creative.

Builds AI inside FP&A, accounting, audit, treasury.

Builds AI for talent acquisition, learning, performance, internal mobility.

Builds AI workflows for contract review, compliance monitoring, regulatory writing.

Builds AI for pipeline scoring, outreach personalization, deal acceleration.

Builds AI inside operations, supply chain, logistics, procurement, fulfillment.

Builds AI inside customer service, success, and support.

The business analyst for the agentic era.

Designs how people work with AI: agent interfaces, conversation flows, the human-in-the-loop moments.

The customer-success motion rebuilt for AI deployments.

The function-native content role rebuilt around AI: produces, edits, and governs AI-generated content.

The most-hired AI Builder role in the market today.

Bridges model labs and customers.

Sits inside the customer's workflow.

FDE pointed inward. Embeds inside a business function (Stripe: 20-marketer pods; Box: cross-functional) and builds the agents the function uses daily. Hands-on: deliverable isn't an integration, it's

Builds multi-step agent workflows.

Builds and operates the agent itself: tool-use, memory, planning, and execution of a single production agent as a shippable unit.

Designs, tests, and maintains prompt suites and evals.

The 2026 successor to the Prompt Engineer.

The pre-agentic AI Builder.

The LLM-native engineer.

Designs the AI system around the model, orchestration, retrieval, evals, guardrails, security boundary, observability.

Pushes the model frontier: novel architectures, evals, fine-tuning research.

Builds the data layer AI runs on: ingestion, feature stores, embeddings, retrieval.

Gets AI from proof of concept into production at the customer.

Builds the shared platform every other AI builder builds on: model serving, orchestration infrastructure, evals, guardrails as a service.

Secures the AI layer: prompt injection, model supply chain, agent permissions and data boundaries.

Runs models in production: pipelines, monitoring, retraining, rollback.

The pre-sales and post-sales engineer for AI products: runs the demo, builds the pilot on the customer's data, and carries the integration through onboarding.

Brand-new role. CAIO emerged as a corporate title in 2023-2024 and is being appointed at most Fortune 500s now, the named workforce underneath is what Nuvepro builds.

Function-level AI leader (Head of AI for Marketing, Head of AI Enablement, Head of International Applied AI).

Enterprise AI leadership at the VP/SVP level, typically running the AI platform, AI product, or AI-X function (AI Security, AI Strategy, AI Innovation).

Operational AI ownership, often the role accountable for shipping AI features and AI-touching products in a specific business unit.

The HR-equivalent for AI.

Cross-functional AI ambassador.

Non-engineer who ships software via AI.

Owns the layer between agents and people.

The assurance layer for AI work.

Owns the AI product. Decides what the model or agent should do, scopes the human-in-the-loop, and ships AI features. The market has named this one; it sits between the AI Builders and the business.

Sets the AI agenda for a function or the enterprise: where to deploy agents first, what to buy versus build, how the operating model changes.

Runs AI initiatives to delivery: coordinates the build, the change, the rollout, and the measurement across teams.

The advisory AI expert brought in to scope, design, and de-risk AI adoption.

Owns getting AI actually used, not just deployed.

Runs the agents once they are deployed: watches queues, quality, and escalations day to day.