What Companies Actually Hire For (2026)
5 min read
Eng Manager
You're hiring. Cut through the noise. Look for outcomes and adaptability.
Tech Lead
When you interview, you're the filter. Know what matters: ship + learn.
Tpm
Hiring managers want people who scope, build, and iterate. Not order-takers.
What Companies Actually Hire For (2026)
TL;DR
- Job posts are wish lists. Hiring managers compromise. Know what they won't compromise on.
- Top signals: shipped something, can learn fast, fits the team. AI literacy is a plus, not a replacement for fundamentals.
- "Years of experience" matters less. "What have you built?" matters more.
Job posts say "5 years Python, 3 years ML, PhD preferred." Reality: they hire the person who demonstrated they can do the job.
The Real Checklist
| What Posts Say | What Hiring Managers Want |
|---|---|
| X years experience | Evidence you've shipped similar things |
| Specific framework | Can pick up new tools quickly |
| "AI experience required" | Willing to learn, one project proves it |
| Perfect culture fit | Can communicate, doesn't blame, owns outcomes |
They're optimizing for: "Will this person ship and not be a problem?" Everything else is secondary.
What Actually Gets You Hired
- Proof you've shipped. Projects, side work, contributions. Something tangible.
- Relevant domain. If they build data pipelines, your ETL experience beats your React experience.
- Learning velocity. "I didn't know RAG; I built a doc Q&A in 2 weeks." That's a signal.
- Communication. Can you explain your choices? Handle ambiguity? Not everyone can.
The AI Filter
Companies want people who:
- Have used LLMs, RAG, or similar in a real project (not just tutorials)
- Understand trade-offs: cost, latency, quality
- Can talk about what worked and what didn't
They don't need AI PhDs for most roles. They need builders who can add AI to products.
Quick Check
A job post requires '5+ years of Python and AI/ML experience.' You have 3 years of Python and built one RAG project. Should you apply?
Do This Next
- Read 3 job posts for roles you want. Note the required vs preferred. What's often "preferred"? That's where you have leverage.
- List your proof — Projects, outcomes, metrics. Do you have 2–3 strong examples?
- Fill one gap — If "AI experience" is preferred, build one thing. Document it. Now you have it.