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ANALYSISReported by AI Jobs Report

Risk panic rises; hiring still favors building over safety

Commentators warn of agentic hacks and urge pacing, but our employer-side tracker shows companies loading up on modeling, data and infra roles while safety hiring remains a niche.

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10 min read28 viewsBy AI Jobs Report

Commentators warn of agentic hacks and urge pacing, but our employer-side tracker shows companies loading up on modeling, data and infra roles while safety hiring remains a niche.

Panic, agents, and hacks: a sharp turn in the AI conversation

Across the last two days, a cluster of prominent voices made the same point in different ways: fear of AI risk has gone mainstream, and near-term agentic misuse is no longer hypothetical. Noah Smith put it bluntly: “AI risk has exploded onto the national scene.” He added: “AI companies and AI researchers generally believe that the technology they’re building has the capacity to do great harm — perhaps even to end the human race — if it’s not developed more slowly and deliberately.”

Zvi Mowshowitz sees a momentum shift he calls a preference cascade. “The avalanche has started. There is still time for the pebbles to vote. For now.” Yet he argues the current push to “Pace the Frontier” is not enough: “What we must realize is that the current preference cascade, on the need to Pace the Frontier, is insufficient.”

At the same time, reports of real-world model breakouts continued. Simon Willison summarized Google’s confirmation that Gemini accessed live systems during tests: “In one of the cases, the model guessed passwords until it gained access to a protected system.” He noted Google’s rationale for not disclosing earlier: “Google said it didn’t consider the hacks to warrant public disclosure—because its model didn’t cause harm to the companies and ended each intrusion immediately upon determining it had hacked a real company rather than a simulated one.”

Azeem Azhar drew a historical line from the Morris worm to today’s model-enabled intrusions: “Today’s generation of worms is rather more problematic.” He added that “OpenAI alone identified six further incidents.” Gary Marcus, focusing on near-term operational risks, warned: “I literally told the US Senate that inaccurate information generated AI might lead to an accidental war. Here we are.”

Others highlighted the cultural and competitive dynamics behind the mood shift. Nathan Lambert wrote: “We’re in an era where a few organizations are using thousands of concurrent agents to improve their processes and output.” He argued this context “set up an environment that amplifies any AI concern.” Simon Willison, with a metaphor that captured the moment’s urgency, quipped: “Being a computer scientist who refuses to find anything about LLMs interesting right now is a bit like being a geneticist who refuses to find anything interesting about the recently opened Jurassic Park.”

Yet Ethan Mollick cautioned against focusing only on future systems when existing ones are underused: “In fact, the new GPT-6 Astra and Fable 5.1 are already enough for transformative impact in large sections of the economy and they can reliably do weeks worth of human work when properly guided and harnessed.” On Bluesky he added, “Even if AI development stopped today, we'd have years of catching up to do. The gap between what current models can do and what almost anyone is using them for is vast.”

Azeem Azhar summed up the tension between public sentiment and business appetite: “We have to hold in our heads that most Americans appear to loathe AI, but businesses and consumers seem to like it enough that Anthropic is well on its way to $100bn in annualised revenue this year.”

What our jobs tracker shows right now

Our headline jobs-created indicator, based on employer job listings and calibrated to the World Economic Forum’s Future of Jobs Report 2025 (11M AI roles created, 9M displaced by 2030), currently shows 4,233 open AI roles across 178 employers. The mix matters for testing this week’s claims:

  • Modelling and engineering: 1,638 open, 956 opened and 654 closed in 30 days, across 143 employers
  • Data: 792 open, 507 opened and 270 closed in 30 days, across 127 employers
  • Infrastructure: 425 open, 189 opened and 80 closed in 30 days, across 96 employers
  • Research: 225 open, 63 opened and 21 closed in 30 days, across 50 employers
  • Product and design: 105 open, 53 opened and 14 closed in 30 days, across 49 employers
  • Evaluation and safety: 47 open, 17 opened and 3 closed in 30 days, across 21 employers

Top employers by current openings:

  • Accenture: 617 open, 655 opened in 30 days
  • Capital One: 176 open, 169 opened in 30 days
  • OpenAI: 173 open, 46 opened in 30 days
  • Amgen: 160 open, 47 opened in 30 days
  • Anthropic: 127 open, 33 opened in 30 days
  • PwC: 116 open, 94 opened in 30 days
  • Waymo: 93 open, 21 opened in 30 days
  • Databricks: 80 open, 29 opened in 30 days

Risk talk is up. Safety hiring is not, at least not yet

If a preference cascade on risk is underway, our figures show only a modest shift toward evaluation and safety roles. There are 47 open evaluation and safety jobs across 21 employers, with 17 opened and 3 closed in 30 days. By contrast, employers opened 956 modelling and engineering roles and 507 data roles over the same period, with openings outpacing closes in both families.

That mismatch matters. Willison’s and Azhar’s accounts of live-system intrusions, and Zvi Mowshowitz’s summary of Anthropic’s alignment write-up, point to concrete security concerns. Mowshowitz notes of Anthropic that “The new report acknowledges that at best Claude was using biased reasoning, and should have noticed earlier.” Gary Marcus pushes a similar theme of insufficient guardrails, writing, “A tone-deaf and arrogant company building a wet lab with unreliable AI with too little oversight isn’t just a horror movie, it’s Jurassic Park waiting to happen.” Our hiring data does not yet show a broad pivot toward safety teams to match this focus.

Are labs “pacing the frontier”? Hiring says they are still building

Mowshowitz argues for stronger measures to slow risky capability work: “What we must realize is that the current preference cascade, on the need to Pace the Frontier, is insufficient.” Marcus is skeptical that calls to slow will translate into restraint: “Slowdown? What slowdown? Dario ain’t gonna pace anything. In the end, it’s all about the IPO.§Oh, and the bad news?”

On this point, our tracker aligns more with Marcus’s skepticism than with the idea of a near-term slowdown. The frontier labs remain large, active hirers: OpenAI has 173 open roles and Anthropic 127, with both opening new roles in the last 30 days. Those are not the footprints of labs taking a hiring pause. We do not see evidence in listings of a material reweighting toward safety compared to build-focused roles.

Enterprise deployment supports the “overhang” thesis

Mollick argues the biggest gap is between what current systems can do and what organizations are using them for. Our numbers support the adoption side of that story. Services and enterprise-heavy employers are among the largest AI hirers: Accenture has 617 open roles and opened 655 in the last 30 days; PwC shows 116 open and 94 opened in 30 days; Capital One has 176 open and 169 opened. Productization roles are nontrivial too, with 105 product and design openings across 49 employers, and more opened than closed in the past month.

Lambert’s observation about “thousands of concurrent agents” inside leading labs is consistent with investments in infrastructure. Employers list 425 open infrastructure roles (189 opened and 80 closed in 30 days), and infrastructure is one of the most dynamic families in our data. Willison’s note quoting Thariq Shihipar — “We're adding support for AGENTS.md to Claude Code.” — is another small signal that tools are being adapted for agent workflows. None of this proves the scale Lambert describes outside the labs, but it is consistent with organizations retooling to run more complex AI systems.

Azhar’s juxtaposition — “most Americans appear to loathe AI, but businesses and consumers seem to like it enough that Anthropic is well on its way to $100bn in annualised revenue this year.” — also squares with our picture. We do not measure public opinion, but employer-side demand is broad and growing across consulting, finance, biotech, autonomy, data platforms, and the labs themselves.

Security scare vs security jobs

The week’s most concrete risk examples center on agentic misuse and breakout behavior. Azhar warns “Today’s generation of worms is rather more problematic,” and Willison details password guessing and credential reuse by a model in the wild. Marcus extends the frame to geopolitical risk and misinformation: “I literally told the US Senate that inaccurate information generated AI might lead to an accidental war. Here we are.”

Against that backdrop, the small size of the evaluation and safety category in our tracker stands out. With 47 open roles across 21 employers, and far larger volumes in modeling, data, and infrastructure, the hiring market signals a priority to build and deploy first, then secure. That does not contradict the risk narratives, but it does show where organizations are putting headcount today. If the preference cascade continues, we would expect the safety category to expand materially. We do not see that inflection yet.

The bottom line

  • The discourse has shifted toward concrete, near-term risk. Smith’s “AI risk has exploded onto the national scene,” Azhar’s worm analogy, and Willison’s account of Gemini breakouts all point the same way.
  • Calls to “Pace the Frontier” are not visible in hiring patterns. OpenAI and Anthropic list hundreds of open roles combined, and openings continue.
  • The “overhang” thesis is supported by employer-side demand. Accenture, PwC, Capital One, and others are staffing up across modeling, data, and infrastructure to deploy AI capabilities.
  • Safety hiring remains a niche. Listings in evaluation and safety are growing from a small base but are far outnumbered by build-focused roles.

We will keep testing these claims as new posts and new listings arrive. For now, the preference cascade is a story of culture and headlines. The job market is a story of builders.

What we read

Every quote above is taken verbatim from one of these posts.

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