Oracle cuts over 150 cloud-unit jobs in Seattle amid cost control and AI data-centre investment
Company still hiring in Tennessee after headquarters move to Nashville
AI infrastructure buildout, including a 4.5 GW data-centre deal with OpenAI, strains free cash flow
Layoffs follow broader big-tech trend as firms balance AI growth with operational efficiency
Oracle Corp. has cut jobs in its cloud unit as the company tries to rein in costs while it invests heavily in AI data-centre capacity, Bloomberg reported.
As per the report, impacted employees were told this week that their roles were eliminated, with more than 150 positions cut in the Seattle area, long a hub for the unit.
While some reductions were tied to performance reviews, the cloud unit is still recruiting for other roles, particularly in Tennessee, where Oracle has shifted focus after moving its headquarters to Nashville.
The full scope of the job reductions was not disclosed; industry site DatacenterDynamics first reported the layoffs.
AI-Powered Job Cuts
Executives at many tech firms are trimming staff in parts of their businesses to offset rising capital costs for building and powering AI infrastructure. Oracle’s cloud business has fuelled investor optimism and the stock sits near record highs, but the company faces multibillion-dollar commitments to build large server farms.
In June, it signed a landmark deal with OpenAI for roughly 4.5 gigawatts of U.S. data-centre power, a move that underscores both demand and the scale of Oracle’s spend.
Heavy infrastructure spending has weighed on free cash flow: Oracle reported negative free cash flow for the fiscal year ended in May. Company filings note periodic workforce adjustments “due to strategy changes, reorganizations or performance issues,” and warn that restructurings can temporarily reduce productivity.
The cuts mirror cost-control measures across big tech: Microsoft has cut roughly 15,000 roles this year, while Amazon and Meta have also pared staff. For Oracle, the challenge will be balancing ongoing investment to capture AI demand with maintaining operational efficiency as it scales data-centre commitments.
