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Create ResumeA FAANG software engineer resume is not just a stronger version of a regular tech resume. It is evaluated differently. Recruiters and hiring managers at Google, Amazon, Meta, and other Big Tech companies screen for evidence of scale, engineering complexity, measurable impact, system design exposure, and high ownership. Generic “built APIs” or “improved performance” bullet points rarely survive screening.
The resumes that consistently get interviews at top tech companies show three things clearly within seconds:
Technical depth
Business or engineering impact at scale
Signals of strong problem-solving and execution
The biggest mistake candidates make is writing a resume focused on tasks instead of engineering outcomes. FAANG recruiters are looking for proof that you can solve difficult technical problems in production environments, collaborate across teams, and operate in high-scale systems.
This guide breaks down exactly how FAANG recruiters evaluate software engineer resumes, what top-performing resumes include, what gets rejected, and how to optimize your resume for Big Tech ATS systems and human reviewers.
Most software engineering resumes are written for general hiring markets. FAANG resumes are written for highly competitive engineering environments where thousands of technically qualified candidates compete for the same role.
That changes the evaluation criteria.
At Big Tech companies, recruiters are not only asking:
“Can this person code?”
They are asking:
Can this engineer handle complexity at scale?
Can they operate in distributed systems?
Do they understand performance tradeoffs?
Can they influence architecture or reliability?
Have they solved meaningful engineering problems?
Would senior engineers trust this person in production systems?
Most first-pass resume screens are fast. Extremely fast.
A recruiter or sourcer often spends under 20 seconds deciding whether a software engineer moves forward.
Here is what they scan immediately.
They look for:
Programming languages
Cloud platforms
Distributed systems exposure
Backend architecture
CI/CD pipelines
Infrastructure technologies
A FAANG software engineer resume should be concise, dense with relevant information, and optimized for both ATS systems and human reviewers.
For most candidates:
1 page for under 8 years of experience
2 pages only if experience depth justifies it
Recommended structure:
Include:
Name
Location
GitHub
That is why FAANG resumes prioritize:
Scalability
Distributed systems
Performance optimization
Reliability engineering
Infrastructure impact
System design exposure
Technical leadership
Metrics and measurable outcomes
A strong startup or mid-market engineering resume may still fail FAANG screening if it lacks evidence of engineering depth.
Scalability tooling
Databases and system design experience
The stronger the alignment with the target team, the higher the chance of recruiter engagement.
This is where many resumes fail.
Big Tech hiring teams care deeply about scale because their systems operate under massive load.
Strong resumes quantify:
Requests per second
Number of users supported
Latency reduction
Cost savings
Throughput improvements
Infrastructure scale
Reliability improvements
Data processing volume
Even for mid-level engineers, FAANG companies value ownership.
Recruiters look for:
Technical decision-making
Cross-functional collaboration
Mentorship
Architectural contributions
Leading migrations or redesigns
Driving reliability initiatives
Influencing engineering standards
Strong resumes show engineers who think beyond implementation.
Signals include:
Algorithms optimization
System design involvement
Reliability engineering
Performance tuning
Fault tolerance
Scalability improvements
Infrastructure automation
Monitoring and observability
Portfolio or personal site if relevant
Avoid:
Full mailing address
Photos
Multiple phone numbers
Unprofessional email addresses
Optional, but useful when transitioning between:
Companies
Industries
Seniority levels
Technical stacks
Good summaries are short and technically specific.
Weak Example
“Experienced software engineer with a passion for coding and problem solving.”
Good Example
“Backend software engineer with 6+ years building distributed systems and cloud-native infrastructure supporting 40M+ monthly users across AWS and Kubernetes environments.”
The second version immediately communicates scale and relevance.
This section matters more for Big Tech than many candidates realize because recruiters often keyword-match quickly during sourcing.
Organize skills clearly.
Example categories:
Languages
Frameworks
Cloud Platforms
Databases
Infrastructure & DevOps
Monitoring & Observability
System Design & Architecture
Avoid massive keyword dumping.
This hurts readability and sometimes ATS relevance scoring.
This is the core of the resume.
Every bullet should demonstrate:
Technical contribution
Engineering complexity
Measurable outcome
Your bullets should answer:
“What changed because of your work?”
Not:
“What tasks did you perform?”
This is the biggest differentiator between average and elite software engineering resumes.
Top-performing bullets usually contain:
Technical action
System or engineering context
Scale or complexity
Quantified impact
Strong structure:
Action + Technical Context + Scale + Result
Weak Example
“Worked on backend APIs for customer platform.”
Problems:
No scale
No metrics
No technical depth
No outcome
No engineering complexity
Good Example
“Designed and optimized backend APIs handling 12M+ daily requests, reducing average response latency by 38% through query optimization and Redis-based caching.”
Why this works:
Shows scale
Shows measurable impact
Demonstrates engineering decisions
Includes relevant technologies
Indicates performance optimization
Many candidates add random percentages without context.
FAANG recruiters look for metrics tied to engineering value.
Strong metrics include:
Latency reduction
Uptime improvement
Reliability gains
Deployment speed
Infrastructure cost reduction
Throughput increases
Database optimization
Query performance
Error reduction
User scale
Traffic scale
Availability improvements
Reduced API latency from 450ms to 120ms
Improved service uptime from 99.1% to 99.95%
Scaled Kubernetes infrastructure supporting 80M monthly requests
Reduced cloud infrastructure costs by $420K annually
Increased CI/CD deployment frequency from weekly to hourly releases
Specificity matters.
Generic statements like “improved system performance” are significantly weaker.
Big Tech recruiters search resumes using highly targeted technical keywords.
Relevant keywords improve discoverability during sourcing and ATS matching.
Important FAANG resume keywords include:
Distributed systems
Scalability
Microservices
CI/CD
System design
Cloud infrastructure
Kubernetes
AWS
GCP
Performance optimization
Fault tolerance
Reliability engineering
Infrastructure automation
Algorithms
Data structures
Event-driven architecture
Service-oriented architecture
Observability
Monitoring
High availability
But keyword stuffing is a major mistake.
Recruiters can instantly spot resumes artificially overloaded with technologies.
Keywords should appear naturally inside accomplishments and technical context.
Google hiring tends to prioritize:
Strong computer science fundamentals
Algorithms and data structures
Distributed systems
Performance optimization
Technical problem-solving depth
Scalable backend engineering
Google recruiters also pay attention to engineering precision.
Strong Google-oriented resumes often include:
Infrastructure scale
Latency improvements
Query optimization
Machine learning infrastructure
Backend architecture
Large-scale systems
Google tends to favor resumes showing strong engineering rigor over flashy wording.
Amazon resumes are heavily evaluated through the lens of ownership and measurable impact.
Hiring managers often screen for:
Operational excellence
Reliability
Scalability
Cost optimization
Ownership
System resilience
Customer impact
Amazon also values:
Fast execution
Large-scale systems
Infrastructure automation
Cloud-native engineering
Strong Amazon bullets frequently combine technical depth with operational impact.
Good Example
“Redesigned distributed event-processing pipeline reducing processing failures by 72% and improving system recovery time from 45 minutes to under 5 minutes.”
This demonstrates:
Reliability
Scale
Operational thinking
Engineering ownership
Meta often prioritizes:
Product engineering impact
Speed of execution
Scalability
User growth support
Backend optimization
Data-intensive systems
Strong Meta-aligned resumes commonly include:
Feed optimization
Recommendation systems
Real-time systems
High-throughput services
Large-scale experimentation infrastructure
Meta also values engineers who move quickly and influence product outcomes.
This is the most common issue.
Weak resumes describe responsibilities instead of impact.
Recruiters care about outcomes.
Many strong engineers undersell themselves.
If you worked on:
Distributed systems
Caching
Reliability engineering
Scaling infrastructure
System migrations
Kubernetes orchestration
You should say so explicitly.
Bad metrics look inflated or meaningless.
Avoid:
“Improved efficiency by 200%”
“Worked on scalable systems”
“Enhanced performance significantly”
Specific engineering metrics are more credible.
Large skill dumps often hurt credibility.
Recruiters prefer depth over random breadth.
Common formatting problems:
Dense walls of text
Tiny fonts
Excessive bolding
Long paragraphs
Inconsistent spacing
FAANG recruiters want fast readability.
Senior software engineers are evaluated differently from junior and mid-level candidates.
Senior-level resumes should demonstrate:
Architectural ownership
Technical leadership
Cross-team influence
Scalability strategy
Reliability decision-making
Mentorship
Infrastructure design
Senior candidates who only describe coding tasks often fail leveling calibration.
Led migration to microservices architecture
Defined system reliability standards
Designed infrastructure scaling strategy
Reduced incident frequency across critical services
Mentored engineering teams
Influenced platform architecture decisions
The higher the level, the more your resume must demonstrate influence, not just execution.
ATS optimization matters, but many candidates misunderstand how it works.
Modern ATS systems do not simply count keywords.
They evaluate:
Contextual relevance
Role alignment
Skills matching
Resume structure
Parsing quality
That means:
Good:
“Designed distributed microservices architecture on Kubernetes supporting 15M daily requests.”
Bad:
“Kubernetes, scalability, cloud, microservices, distributed systems, CI/CD.”
Natural context performs better.
Use:
Standard section headings
Simple formatting
Clear chronological order
Standard fonts
Plain text-friendly layouts
Avoid:
Tables
Graphics
Columns that break parsing
Fancy icons
Overdesigned templates
Good Example
“Architected distributed backend services processing 4B+ monthly events with 99.98% uptime across Kubernetes and AWS infrastructure.”
Good Example
“Reduced database query latency by 61% through indexing optimization and query refactoring, improving checkout response times during peak traffic.”
Good Example
“Implemented automated failover and observability tooling reducing Sev-1 incidents by 43% across mission-critical production services.”
Good Example
“Built CI/CD pipelines reducing deployment times from 2 hours to 14 minutes while increasing deployment frequency by 5x.”
Good Example
“Scaled real-time messaging infrastructure from 500K to 8M concurrent users through distributed event streaming architecture.”
Projects matter most when candidates lack:
Big Tech experience
Brand-name employers
High-scale production systems
Strong projects demonstrate:
Engineering complexity
Scalability
Distributed systems
Infrastructure knowledge
Real-world architecture
Weak portfolio projects:
Basic CRUD apps
Tutorial clones
Generic dashboards
Strong projects:
Distributed systems simulators
Real-time applications
Event-driven architectures
Large-scale scraping systems
Cloud-native deployments
Kubernetes orchestration projects
Performance-focused backend systems
The project should show engineering thinking, not just framework familiarity.
Most candidates assume rejection means “not technical enough.”
Often, that is not true.
Many technically qualified candidates are rejected because the resume fails to communicate impact clearly.
Recruiters usually ask:
Is this candidate operating at the expected level?
Does the experience match the complexity of our environment?
Is the resume easy to trust quickly?
Does this person show evidence of strong engineering judgment?
Are there measurable outcomes?
Is there enough signal density to justify an interview?
Strong resumes reduce uncertainty.
Weak resumes create ambiguity.
At FAANG scale, ambiguity kills interview conversion.
Before applying to Google, Amazon, Meta, or other Big Tech companies, verify your resume includes:
Measurable engineering impact
Scale metrics
Distributed systems exposure
Performance optimization examples
System reliability improvements
Cloud infrastructure experience
CI/CD and automation signals
Strong technical keywords used naturally
Clear formatting
Evidence of ownership
Architecture or system design involvement
Technical leadership signals when applicable
Most importantly:
Your resume should show how you think as an engineer, not just what tools you used.
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