BLS projects strong software engineer demand as monday.com leans into AI
Software jobs still look durable, but the winning skill set is shifting toward product, systems, QA and AI tooling as monday.com rebuilds around agents.
The labor market is still signaling that strong software people matter, even as AI anxiety keeps reshuffling what companies say they need. The U.S. Bureau of Labor Statistics projects 15 percent growth for software developers, quality assurance analysts, and testers from 2024 to 2034, with about 129,200 openings a year on average. For monday.com, that is a reminder that engineering talent remains valuable, but the edge now belongs to people who can ship across product, infrastructure, data, and AI-driven systems.
Why the BLS outlook matters inside monday.com
The most useful part of the BLS forecast is not just that software hiring stays healthy. It is that demand is broad, with replacement openings playing a major role as workers switch occupations or retire, which means the market keeps recycling opportunity even when headline hiring cools. Across the wider computer and information technology group, the BLS projects about 317,700 openings each year on average, and it pegs the group’s median annual wage at $105,990 in May 2024.
That matters inside a company like monday.com because the work is no longer just about building features quickly. It is about building the right kind of software organization: one that can ship reliably, maintain complex systems, and translate customer needs into products that do more than automate a checkbox. Engineers who understand product constraints, data flows, and customer use cases are in the strongest position, both for internal mobility and for the broader market.
The practical takeaway for managers is blunt: retention and technical depth are now strategic, not cosmetic. If the talent market still rewards software people, the companies that keep them are the ones that give them growth paths, meaningful ownership, and problems worth solving. If you work as an engineer, the message is just as direct: your skills still have durable market value, but the market is favoring range, not narrow specialization.
What kind of software work is still in demand
The old story was that software hiring was mostly about adding heads to keep pace with product demand. That story has aged out. At monday.com, and across SaaS, the work that stands out now is the work that sits close to the seams: systems engineering, product engineering, QA, automation, and the tooling that makes AI useful instead of theatrical.
That means the engineers most likely to create leverage are the ones who can do more than write code in isolation. They can design for reliability, reason about permissions and connectors, and build workflows that hold up when customers start scaling from a handful of users to thousands. They can also work with QA as a real part of product quality rather than an afterthought, which matters more when products are expected to orchestrate work across multiple systems.
- product thinking, so you can connect code to actual customer behavior
- systems design, so you can handle scale, latency, and failure modes
- QA discipline, so releases are dependable instead of just fast
- data fluency, so workflows can be measured and improved
- AI-adjacent tooling, so models, agents, and automation can be embedded into products with guardrails
For aspiring developers, the skills to build now are the ones that survive platform shifts:
That mix is especially relevant in SaaS, where the job is less about one feature and more about the chain of work that feature triggers across a customer’s business. The companies that win are the ones that make software feel like part of an operating system for work, not a separate place employees have to visit.
monday.com’s business scale is the backdrop for its hiring logic
monday.com is not making these decisions from a small base. The company says more than 250,000 customers worldwide use its platform, which gives its product and engineering teams a broad set of use cases to support. It reported fourth-quarter 2024 revenue of $268.0 million, up 32 percent year over year, and full-year 2024 revenue of $972.0 million, up 33 percent year over year.
Those numbers matter because they show a company still operating at scale while trying to change the shape of its product. monday.com also said it reached a record non-GAAP operating income in fiscal 2024 and posted net dollar retention of 112 percent, a sign that customers were expanding even as the company kept pushing into new categories. In SaaS terms, that is the kind of backdrop that lets leadership keep investing in product changes without pretending the execution risk is small.
The 2024 cadence also shows where the company’s platform strategy was heading. In the first quarter, monday.com reported revenue of $216.9 million, up 34 percent year over year, and said monday sales CRM and monday dev were accessible to all customers. In the second quarter, revenue rose to $236.1 million, also up 34 percent year over year, and the company said it had closed an 80,000-seat agreement, the largest deal in its history at the time.
For employees, those details are not just investor-relations color. They point to a product organization that is moving from a general work-management pitch toward a broader platform conversation, where sales, product, and engineering all have to support larger deployments and more complicated customer environments.
The AI shift is changing the engineering brief
monday.com’s roots matter here too. The company was founded in 2012 in Tel Aviv and went public on Nasdaq in 2021, which means it has already made the transition from startup speed to public-company discipline. The current shift is sharper: in March 2026, it launched Agentalent.ai, a managed marketplace where enterprises can discover, evaluate, and hire AI agents for defined business roles, in collaboration with AWS, Anthropic, and Wix. The company also said it was welcoming AI agents to its platform with dedicated onboarding and purpose-built infrastructure.
Then in April 2026, monday.com said it was going all in on AI and reframing itself as an AI work platform. That is not just a branding move. It suggests a product architecture where AI is supposed to execute work, not merely suggest it, which raises the stakes for engineers working on agentic systems, workflow automation, permissions, and platform reliability.
For a monday.com engineer, this is the key career signal: the company is not simply adding AI features on top of the old product. It is rebuilding the product story around AI-enabled execution. That makes platform engineering, governance, and integration work more important, because agents only matter when they can safely touch the systems where real work happens.
What to build if you want staying power
If you are deciding where to invest your time now, the answer is not to chase every new AI headline. It is to become the person who can make AI useful inside production software. That means understanding the plumbing underneath the feature, not just the feature itself.
- get comfortable with workflow automation and orchestration
- learn how permissions and connectors shape what AI can actually do
- treat QA as a core engineering skill, especially in agent-driven products
- deepen your product sense so you can judge whether a feature solves a real problem
- build enough infrastructure literacy to understand failure, scale, and reliability
The strongest bets are straightforward:
That is the real intersection of the BLS outlook and monday.com’s strategy. The labor market still wants software people, but it wants the ones who can bridge product and systems, not just deliver code. At monday.com, where the product is moving toward AI execution and the customer base keeps growing, that kind of engineer has more leverage than ever.
This article was produced by Prism’s automated news system from verified source data, official records, and press releases, then run through automated quality and moderation checks before publishing. The system is built and supervised by the people who set the standards it runs under. Read our full AI policy.
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