LinkedIn Recommendation Examples for a Coworker in Tech
Writing a LinkedIn recommendation for a tech coworker feels straightforward. You saw their work up close. Daily standups, code pushes, late-night deploys. Pick from these 13 examples across five categories. They fit software engineers, devs, PMs. Tweak for your situation. I added a framework, dos and don'ts, templates too. Makes it easy to sound genuine.
1
Technical Expertise
Tech roles thrive on hard skills. Highlight languages, frameworks, tools. Show impact on projects.
professional
short
01
52 words
backend developer
I worked alongside Jordan on our microservices team for 18 months. Jordan masters Go and Docker like few others. They optimized our deployment pipeline, slashing release times from hours to minutes. Clean code, always. Tech leads take note.
Go and Docker
slashing release times
Clean code
Why this works
Names specific tech stack. Quantifies improvement. Direct endorsement.
02
48 words
frontend engineer
Paired with Riley daily on frontend features. Riley's React and TypeScript skills shone. They refactored a messy component library, boosting performance by 35%. Code reviews from Riley always improved our output.
React and TypeScript
boosting performance by 35%
Why this works
Specific tools and metric. Shows consistent value.
03
42 words
data engineer
Teamed with Casey for a year on data pipelines. Casey's Python and Spark prowess handled massive datasets effortlessly. Reduced ETL jobs from 6 hours to 45 minutes. Reliable expert.
Python and Spark
Reduced ETL jobs
Why this works
Clear before/after metric. Concise.
2
Teamwork and Collaboration
Tech moves in teams. Praise communication, pair programming, cross-functional work.
collegial
medium
01
56 words
fullstack developer
Shared a scrum team with Morgan for two years. Morgan excels at bridging devs and designers. They facilitated smooth handoffs, ensuring pixel-perfect UIs without endless revisions. Always positive, even in crunch time. Great teammate.
bridging devs and designers
smooth handoffs
Why this works
Highlights soft skills in tech context. Specific process improvement.
02
50 words
cloud engineer
Collaborated with Taylor on cloud migrations. Taylor communicates complex AWS setups clearly to non-tech stakeholders. Kept everyone aligned, avoided scope creep. Their input in standups kept us on track.
communicates complex AWS
Kept everyone aligned
Why this works
Shows communication value in tech.
03
38 words
software engineer
Worked with Quinn in agile sprints over 12 months. Quinn jumps into pair sessions, shares knowledge freely. Helped juniors ramp up fast. Team velocity improved noticeably.
pair sessions
Team velocity improved
Why this works
Emphasizes knowledge sharing.
3
Problem-Solving
Tech problems demand quick fixes. Spotlight debugging, creative solutions.
enthusiastic
short
01
32 words
backend dev
Faced production outages with Alex. Alex traced elusive memory leaks in Node.js apps overnight. Fixed root cause, prevented repeats. Calm under fire.
memory leaks in Node.js
Calm under fire
Why this works
High-stakes example. Specific tech.
02
28 words
database specialist
Partnered with Sam on scalability issues. Sam redesigned database queries, cutting latency 60%. Thought through edge cases others missed.
database queries
cutting latency 60%
Why this works
Metric-driven solution.
03
30 words
integration engineer
Tackled integration bugs with Pat. Pat's systematic approach with logs and traces uncovered API mismatches. Rolled out fix in hours.
logs and traces
systematic approach
Why this works
Process-focused.
4
Reliability and Delivery
Deadlines matter. Note on-time delivery, quality code.
reliable
medium
01
28 words
devops
Sprinted with Jamie for a release cycle. Jamie commits clean, tested code daily. No hotfixes needed post-launch. Dependable delivery.
clean, tested code
No hotfixes
Why this works
Focuses on habits and results.
02
32 words
product engineer
Co-developed features with Lee over six months. Lee hits every milestone, anticipates blockers. Product shipped on schedule thanks to them.
hits every milestone
shipped on schedule
Why this works
Emphasizes predictability.
5
Leadership and Mentorship
Even peers lead. Call out guiding others, owning initiatives.
admiring
medium
01
30 words
senior dev
Observed Drew mentor new hires on CI/CD pipelines. Drew breaks down Jenkins configs patiently. Team productivity spiked after their sessions.
CI/CD pipelines
Team productivity spiked
Why this works
Quantifiable mentorship impact.
02
24 words
tech lead
Joined Drew leading a refactor sprint. Drew rallied the team, delegated smartly. Delivered ahead of plan.
leading a refactor
Delivered ahead
Why this works
Action-oriented leadership.
03
28 words
security engineer
Worked under Kim's informal lead on security audits. Kim spotted vulnerabilities early, trained us all. Safer codebase now.
security audits
Safer codebase
Why this works
Proactive leadership.
Tips for Recommending A Coworker In Tech
1
Start with your shared context
Mention the project or team. Readers want proof you know the person. Skip generic openers.
2
Add numbers where possible
Doubled speed. Cut bugs by 40%. Tech folks love metrics. They build credibility fast.
3
Keep it under 150 words
Short reads better on mobile. Punchy sentences hit harder. Aim for impact.
4
End with a call to action
Say you'd work with them again. Or hire them tomorrow. Makes it memorable.
5
Polish with a tool
Draft it. Then run through reangle.it for fresh phrasing. Saves time, sounds natural.
6
Match their profile
Echo keywords from their experience section. Helps LinkedIn algorithms too.
Helpful Resources
Frequently Asked Questions
How specific should I get in a tech recommendation?
Name tools like React or Kubernetes. Mention a bug you fixed together. Specifics sell better than vague praise.
Can I use these examples directly?
Tweak names, details, timeline. Make it yours. LinkedIn spots copies.
What's the ideal length?
100-150 words works. Short enough to read, detailed enough to convince.
Do recommendations matter for tech jobs?
Yes. They add social proof. Especially from peers who saw the grind.
Should I ask permission first?
Good idea. Share draft. They might suggest tweaks.
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