How to Identify 'Open to Work' Engineers Before They Post It
By the time an engineer changes their LinkedIn headline to "Open to Work" or flips the green banner on, they've already been fielding offers for weeks. The best candidates get snapped up before they ever publicly signal availability.
The recruiters who consistently make great hires aren't waiting for that signal. They're reading the earlier ones.
Signal 1: The Tenure Clock
This is the single most reliable predictor of job change intent. Engineers change jobs in cycles, and those cycles are remarkably consistent.
The median tenure for software engineers is 2.2 years. But it varies by company type:
- Big tech (FAANG): 2.5-3.5 years (vest cliffs and refresher schedules drive timing)
- Series A-C startups: 1.5-2.5 years
- Enterprise/legacy companies: 3-5 years
- Agencies and consultancies: 1-1.5 years
If someone is approaching the end of their typical cycle, they're statistically more likely to be evaluating options. An engineer who's been at their Series B startup for 2.4 years is in the window. Not definitely leaving, but the probability is elevated.
Track tenure patterns across their last 2-3 roles. If they consistently move every 2 years and they're at 22 months, the clock is ticking.
Signal 2: Company-Level Events
Certain company events dramatically increase the likelihood that employees start looking:
- Layoffs - Even engineers who survived a round start looking. Post-layoff attrition at tech companies runs 15-25% in the following 6 months.
- Leadership changes - New CEO, new CTO, or new VP of Engineering. The roadmap is about to change, and not everyone will like the new direction.
- Missed fundraising targets - If a startup that should have raised a Series C hasn't announced one, employees notice. Runway anxiety is real.
- Public controversies or bad press - Product failures, security breaches, toxic culture reporting.
- Return-to-office mandates - Every RTO announcement creates a wave of departures among engineers who went remote. This is still happening in 2026.
When you see these events in the news, build a sourcing list from that company within 2-4 weeks. You'll catch people at exactly the right moment.
Signal 3: LinkedIn Activity Spikes
Engineers who are passively looking exhibit a specific pattern on LinkedIn:
- Profile updates - New headline, updated summary, fresh skills. Someone who hasn't touched their profile in 18 months suddenly rewrites their summary? They're getting ready.
- Connection spree - Accepting or sending a burst of connection requests, especially to recruiters or people at specific companies.
- Engagement increase - Liking, commenting, or posting more than usual. Especially on posts about hiring, culture, or specific technology topics.
- Recommendations - Asking for or writing recommendations. This is a strong signal. People only do this when they want their profile to look polished for someone specific.
Individually, none of these are conclusive. Together, they paint a clear picture.
Signal 4: GitHub and Open Source Patterns
This one is subtler but very real:
- Increased personal project activity - An engineer who hasn't pushed to their personal GitHub in months suddenly starts a new repo. They might be building a portfolio piece.
- README polish - Updating old repos with better documentation. Nobody does this for fun. They're making their work presentable.
- New contributions to trendy projects - Contributing to a hot open source project (especially in a new technology) can signal they're exploring a career pivot or skill expansion.
Signal 5: Conference and Community Activity
Engineers preparing for a job search often increase their public visibility:
- Speaking at meetups or conferences - Builds personal brand and creates networking opportunities
- Publishing technical blog posts - Establishes expertise and creates inbound interest
- Answering questions on Stack Overflow - Re-engaging with the community after a quiet period
Putting It All Together
You could track all of this manually. Set up Google Alerts for company layoff news. Check LinkedIn profiles weekly for updates. Monitor GitHub activity. Cross-reference tenure patterns. Some recruiters do this, and they're very good at their jobs. But it takes 5-10 hours per week of pure research to monitor even a modest candidate pool this way.
This is exactly what Candyfloss AI's Job Change Signals feature does. For every profile in the system, we track tenure relative to historical patterns, company event correlation, profile and activity changes, and GitHub activity shifts. You get a feed of engineers who are statistically likely to be open to a conversation, before they broadcast it to the world.
That timing advantage is the difference between being the first recruiter to reach out and being the fifteenth.