Nuvepro - Task Intelligence for the Enterprise
New AI Roles · Explore

Engineering has named its AI Builders. Business functions haven't.

Nuvepro is naming the layer ahead of the market, so you can hire for it, build readiness for it, and measure it.

Sourced from 179,570 real job postings · 1,812 AI-Builder postings · 1,374 distinct titles

11%
of all Anthropic openings

47 of 422 current Anthropic openings are Applied AI Architect or Forward Deployed Engineer variants. The frontier-AI labs are naming this layer first.

anthropic.com careers, May 2026
Levie
Box CEO, May 2026

“Akin to a forward deployed engineer for internal functions. This is why, at Box, we're starting to hire for AI automation engineering roles.”

x.com/levie
700%+
year-over-year growth in FDE postings

Indeed Hiring Lab tracked growth in Forward Deployed Engineer postings. Palantir-originated, now templated at OpenAI, Anthropic, AWS, Google. The same role is now pointing inward. See AI Accelerator in the engineering row.

Indeed Hiring Lab, 2026
The naming gap
91413
Engineering: 914 distinct titles across the market converge to ~13 canonical names. The market has named this layer.
237 → 0
Business functions: 237 distinct titles across Marketing, Finance, HR, Legal, Sales, Ops, CX → zero canonical names. Every posting invents the role from scratch. The work is happening; the title hasn't caught up.
After the reorg
Emerging

The roles that stay human

The market is naming who builds AI. Foundation Capital is naming who stays human when agents do the work. Four roles, emerging now.

Chief Accountability Officer

Owns the outcome. Signs the filing, stands behind what the agent shipped.

Not yet a posted title
Systems Architect

Designs how humans and agents divide the work. Steepest learning curve, most leverage.

Posting now as AI Architect
Relationship Expert

Holds the human-to-human trust no model closes.

Not yet a posted title
Validator

Reviews and signs off on what AI produces.

Posting now in model and risk validation

Two of these aren't job titles yet, with near-zero postings across the corpus behind this page. That's the naming gap above, one layer deeper: the work is here, the title hasn't caught up. And the validator is the catch. “The validator pool is a one-generation asset unless we deliberately replenish it.” If agents do all the junior work, how does the class of 2035 get expert enough to verify the senior work? That replenishment is what the Bootcamp builds.

Source: Foundation Capital, “The Great Reorg” (Joanne Chen) and the follow-up with Azeem Azhar.
Off the org chart

The AI trainer gig layer

Beneath every named AI role sits a contingent-labor layer: domain experts hired per-task to train, evaluate, and red-team models. Not employees, not headcount. A labor market parallel to the org chart. Scale AI's Outlier and Mercor are the largest platforms. Mercor reports ~30,000 contractors at an average billed rate near $95/hr; creative-writing trainers run $75-$150/hr. This layer shows up in /explore/new-roles as a footnote because it doesn't sit on the org chart, but it's where the judgment, taste, and domain expertise that tunes today's models actually comes from.

Sources: Mercor, TIME (2026), Business Insider (May 2026)

Build your AI Builders, name your layer.

Audit how many of these roles your org already needs. Run the Bootcamp to ship the first one in 14 days.

Methodology

Counts are computed from 179,570 job postings in Nuvepro's real-world JD corpus (jobscraper.db, snapshot 2026-06-28). Engineering buckets match by canonical title pattern. Business-function buckets match by function keyword AND any AI-flavor term (AI, GenAI, agentic, LLM, ML, prompt, applied AI). Operator buckets match canonical executive titles ("VP AI", "Head of AI", etc.). Strict to avoid over-counting.

"AI Builder" as a literal job title returns zero matches across the corpus. The category is Nuvepro's term; the market hasn't yet named it. Cross-row title overlap is removed by DISTINCT job ID at the row level.