Software engineers can still rake in big bucks by working for fast-growing companies

A Levels.fyi review finds US software engineer (SWE) pay is correlated with headcount growth: firms paying the most are generally still hiring, with senior offers cited around ~$810k at Anthropic and ~$605k at OpenAI. However, other AI-investing majors (Meta, Amazon, Google, Coinbase) are described as high-paying but cutting staff, while companies with heavier AI compute spending show more ambiguous layoff-to-compensation tradeoffs. In Australia, Adaca reports software/application programmer employment rising to 216k from 189k, suggesting displacement from big tech is being absorbed by broader demand elsewhere.

Analysis

The market is likely underestimating how much this labor bifurcation favors the largest platforms and penalizes everyone trying to bolt on AI without a clear productivity payback. In the next 1-3 quarters, the key variable is not headcount itself but whether AI spend is translating into faster product shipping and better unit economics; if not, margin pressure will show up first in software names with slower growth and weaker pricing power, especially MSFT, ORCL, and CRM.

A second-order effect is talent concentration: the highest-paying firms are effectively buying option value on future model quality and developer velocity. That creates a widening gap between companies that can absorb expensive senior engineers and those forced to cut mid-level staff, which should intensify competitive divergence in cloud, ads, and enterprise software over 6-18 months.

The contrarian read is that layoffs are not automatically bearish if they are reallocating spend from low-return labor to high-return AI infrastructure. The more important falsifier is evidence of productivity lift: if next earnings cycles show stable or improving gross margin and operating margin despite lower headcount, the 'AI destroys software jobs' narrative will fade quickly; if not, the market will keep compressing multiples on firms with visible AI opex and unclear monetization.

Key Decisions for Investors

• Over the next 1-3 months, favor a relative-value short basket of MSFT/ORCL/CRM versus long GOOGL/META/AMZN, on the thesis that scale winners can absorb AI talent inflation while slower enterprise vendors face margin drag and weaker hiring leverage. Falsify if the short basket prints accelerating operating margin or materially better AI monetization commentary.
• Use earnings into the next 1-2 quarters to buy CRM put spreads only on strength if the stock rallies on AI narrative without clear headcount or margin proof; the setup is better for a fade than a momentum long. Risk/reward improves if implied volatility is cheap and guidance still depends on efficiency savings.
• Set a 6-18 month alert on ORCL and MSFT for operating margin inflection versus capex growth. If AI-related spend keeps rising while headcount stays flat/down and revenue growth does not re-accelerate, expect multiple compression to persist.
• Stay long the firms that can pay up for senior AI talent and still grow headcount selectively; if you want a cleaner expression, pair long META or GOOGL against a software laggard basket rather than buying broad tech beta. The thesis breaks if talent costs rise without corresponding product velocity.