So you have found a PM or leadership job at FAANG on LinkedIn that you like? Here’s what to do next.
When most people see a job posting on LinkedIn, they click on Easy Apply and hope for recruiters to reach out.
That’s a recipe for your application to disappear into a black hole.
Because at the leadership level, hiring doesn’t work like that.
When companies like Google or Amazon fill PM and leadership roles, they’re not just looking for someone with the right skills.
They’re looking for someone who stands out before they even step into the interview.
So before you hit apply, do this instead:
Find the hiring manager or key decision-makers.
Merely an optimized resume isn’t enough. Hiring managers need to see you before they see your application.
Search LinkedIn for people with titles like “Director of Product” or “VP of Engineering” at the company.
Check who’s posting about hiring for that team.
See if you have mutual connections who can introduce you.
Send a targeted, high-value cold outreach.
Most people send weak messages like: “Hi, I applied for this leadership role. Can you refer me?”
Instead, try: “Hi [Name], I saw the [Role] opening on your team and was excited because of my experience leading [X projects]. Would love to hear what success looks like for this role and see if I’d be a strong fit.”
You need to position yourself as a high-value candidate before they even open your application.
Make your LinkedIn work for you.
Before you apply, make sure your profile proves you’re the right candidate.
Use a clear, value-driven headline (not just “Senior Product Manager”).
Highlight major wins in your About section (with numbers!).
Make sure your Skills and Experience match the job description.
Hyper tailor your resume using functional and domain keywords.
Hiring managers aren’t reading your resume - they’re scanning for proof of impact.
Show impact, not tasks. (“Launched a product that grew revenue by 20%” is better than “Managed a product launch.”)
Use keywords from the job description. Cut the fluff - keep it clear, relevant, and results-driven.
Found value?