Boolean search LinkedIn: 15 examples for recruiters [2026 cheat sheet]

You open LinkedIn Recruiter. You type a boolean search. Enter. 800 profiles.

Now the real work begins: scrolling, opening profiles, googling employers, evaluating. 3 hours later you have 80 relevant candidates.

Boolean search is your #1 skill as a recruiter. But it’s only half the job. The other half: figuring out whether work experience is relevant. And boolean can’t do that.

This guide gives you 15 concrete boolean examples per domain. Plus: why you still have to manually filter on employer context.

What is Boolean search?

Boolean search combines search terms with operators to find exactly what you’re looking for.

The 5 basic operators:

LinkedIn Recruiter supports all operators. LinkedIn Basic supports OR and quotes, but not AND/NOT (those are implicit).

15 Boolean search examples for LinkedIn

IT & tech

1. Java Developer (mid-senior)

(Java OR J2EE OR Spring) AND (Developer OR Engineer) NOT (Junior OR Trainee OR Intern)

2. DevOps Engineer

(DevOps OR "Site Reliability" OR SRE) AND (Kubernetes OR Docker OR AWS OR Azure)

3. Data Engineer (with Python)

"Data Engineer" AND (Python OR Spark OR Airflow) AND (ETL OR Pipeline)

4. Frontend Developer (React)

(React OR ReactJS OR "React.js") AND (Frontend OR "Front-end" OR UI) NOT Backend

5. Security Specialist

(Security OR Cybersecurity OR InfoSec) AND (Penetration OR SOC OR SIEM) NOT Manager

Sales & commercial

6. Enterprise Sales (SaaS)

(Enterprise OR "Large Account") AND (Sales OR "Account Executive") AND (SaaS OR Software OR Cloud)

7. Inside Sales Rep

("Inside Sales" OR "Sales Development" OR SDR OR BDR) NOT Manager

8. Channel Sales Manager

(Channel OR Partner OR Reseller) AND Sales AND Manager

9. Business Development (B2B)

("Business Development" OR BD OR "New Business") AND B2B NOT Junior

Finance & control

10. Financial Controller (industry)

("Financial Controller" OR Controller) AND (Manufacturing OR Production OR Industry)

11. Finance Manager (consolidation experience)

"Finance Manager" AND (Consolidation OR "Financial Reporting" OR IFRS)

Marketing

12. Demand Generation Specialist

("Demand Generation" OR "Demand Gen") AND (Marketing OR Campaigns) AND (B2B OR SaaS)

13. Growth Marketing Manager

(Growth OR "Growth Hacking") AND Marketing AND (Analytics OR Experimentation)

Operations & logistics

14. Supply Chain Manager

"Supply Chain" AND Manager AND (Planning OR Procurement OR Logistics)

15. Operations Manager (manufacturing)

"Operations Manager" AND (Manufacturing OR Production OR Plant)

Why Boolean is NOT enough

Your boolean search gives you 800 profiles. Congratulations. Now the real work begins.

The problem: Boolean filters on keywords. Not on context.

Example: Account manager (SaaS OR Software)

You’re looking for an Enterprise Account Manager for a mid-market SaaS company. Consultative selling, 6-12 month sales cycles, EUR 50K-250K deals.

Your boolean search:

"Account Manager" AND (SaaS OR Software) AND Enterprise

You get 600 profiles. They all look relevant. Title checks out. Keywords check out.

But:

• Candidate A: Account Manager at an inside sales company. Transactional deals, 1-2 week cycle, EUR 5K average.
• Candidate B: Account Manager at a channel sales organization. No direct selling, partner relationships.
• Candidate C: Account Manager at a consultative enterprise SaaS vendor. Multi-stakeholder selling, 9-month cycle, EUR 100K deals.

Which one fits your vacancy?

LinkedIn can’t see the difference. You have to google each profile yourself.

What Boolean can’t see

Boolean matches on:

• Job title
• Profile keywords
• Skills

Boolean does NOT match on:

• Type of employer (consultative vs transactional)
• Sales model (inside, field, channel)
• Deal complexity (EUR 5K vs EUR 250K)
• Customer segment (SMB vs enterprise)
• Sales cycle length (weeks vs months)

And it’s precisely that context that determines whether work experience is relevant.

The 3 layers of LinkedIn sourcing

Layer 1: Boolean search (narrow down)

Boolean narrows your search results from 50,000 to 800 profiles. It filters on title, keywords, location. This is essential but it’s only layer 1.

Layer 2: Manual scan (visual filtering)

You scroll through the 800 profiles. You open profiles. You read job titles, look at employers, try to evaluate. This layer costs 3+ hours. You google company names. You hesitate.

Layer 3: Employer-context analysis (relevance check)

You analyze per candidate: where have they worked and what does that employer do? With 800 profiles, that’s impossible to do manually. That’s why you miss relevant candidates and include irrelevant ones.

How SourceLens adds the missing layer

SourceLens automatically adds layer 3. For each profile, SourceLens analyzes the last 8 employers across 18 dimensions:

• Sector & organization type
• Customer segment (B2B/B2C, enterprise/SMB)
• Sales model (inside/field/consultative)
• Deal complexity & sales cycle
• Growth stage (startup/scale-up/corporate)

Then SourceLens matches candidates against your selection criteria.

Result: From 800 profiles to 80-100 relevant candidates. Automatically.

Example: The SaaS account manager search

You define criteria in SourceLens:

• Consultative sales experience (35%)
• Enterprise customer segment experience (30%)
• SaaS background (25%)
• Deal size EUR 50K+ (10%)

SourceLens analyzes each candidate:

• Candidate A: inside sales, transactional — Score: 32/100
• Candidate B: channel sales — Score: 28/100
• Candidate C: consultative enterprise SaaS — Score: 91/100

Your shortlist now only contains candidates with a score of 75+. From 600 to 73 candidates. In 45 minutes.

Common Boolean search mistakes

Mistake 1: Boolean too narrow. "Senior Java Developer" AND Spring AND Microservices AND Kubernetes AND AWS gives you 12 profiles. You miss candidates with “Java Engineer” in their title. Start broader, then filter on context.

Mistake 2: Boolean too broad. Developer OR Engineer gives 40,000 profiles. At minimum, add a technology or seniority level.

Mistake 3: Assuming keywords = experience. Many candidates add keywords without having the actual experience. Check the employer context.

Mistake 4: Ignoring job title variations. In the Netherlands: “Accountmanager”, “Account Manager”, “Account Executive”, “Sales Manager”. Use OR for variations.

Mistake 5: Forgetting negative filters. Looking for an IC? Add: NOT (Manager OR Lead OR Director).

Conclusion: Boolean is essential, context is the other 50%

Boolean search is your foundation. It’s the skill every recruiter must master. But it’s only half the equation.

You don’t know 90% of the employers in your search. For that 90%, you’re guessing whether work experience fits. That costs time. And you miss candidates.

SourceLens gives you the employer context you’re missing. Automatically. For every candidate. In seconds. From 800 profiles to 80 relevant ones. Without guesswork.

Try SourceLens free for 14 days — no credit card, works with any LinkedIn (even free).

Related articles:

• How SourceLens Works — see how employer-context analysis works
• Pricing — starting at EUR 89/month (launch offer)