Stop guessing from resumes. Start reviewing automated analysis: test coverage metrics, security scans, code complexity scores, and quality progression over time. See technical indicators before the first interview.
Resume screening provides no objective way to verify claimed technical skills
"Can't verify if 'Node.js expert' means 3 years production or 3 tutorial projects"
"Receive 200+ applications with no objective way to compare technical quality"
"Spend days reviewing portfolios trying to assess code quality and best practices"
"Discover in interviews that 'scalable architecture' has major code quality issues"
Analyze actual Node.js repositories for complexity, patterns, test coverage over time
Automated code quality scoring ranks candidates by measurable technical indicators
Pre-analyzed profiles show code quality metrics, security issues, and test coverage upfront
Surface code duplication, complexity metrics, and anti-patterns before first contact
Professional static analysis tools and security scanners run on every repository. These are the same tools engineering teams use in CI/CD pipelines.
Quality progression shows learning and professional growth better than any resume claim
JavaScript with any types
Strict TypeScript with proper interfaces
Shows progression toward type safety
Empty catch blocks, crashes on null
Consistent error boundaries, proper logging
Production-ready code patterns
No tests or minimal coverage
70%+ coverage with integration tests
Professional quality standards
5000-line files, mixed concerns
Feature-based structure, SRP adherence
Understanding of architecture
Pre-analyzed developer profiles with concrete technical measurements
Professional static analysis tools measure objective quality
Identify security practices and potential vulnerabilities
Measure testing discipline and reliability practices
Identify production-ready backend development patterns
Track how code quality improves over time
Understand development activity and collaboration
Objective measurements beat subjective resume claims
We use the same static analyzers, linters, and security scanners that professional teams use in CI/CD. ESLint for JavaScript, Pylint for Python, RuboCop for Ruby - industry-standard tools measuring objective quality metrics.
We analyze commits over time to see if code quality improves. A developer whose test coverage went from 0% to 70% over 2 years shows learning and growth. Static metrics at a single point miss this crucial signal.
Not subjective opinions - we measure cyclomatic complexity, code duplication percentage, test coverage ratios, security vulnerability counts. These numbers tell a story about code quality that resumes can't capture.
Does their Express.js code follow middleware patterns? Are database queries parameterized? Do they implement proper connection pooling? We detect production-ready patterns versus tutorial-level implementations through code structure analysis.
We believe in transparency about what automated analysis provides
Our analysis requires public repositories. Developers with primarily private work will have limited profiles.
Code metrics show technical patterns but can't measure problem-solving ability, communication, or team fit.
Use our analysis to filter candidates efficiently, then validate cultural fit and soft skills through interviews.
Use TalentProfile to efficiently filter candidates by objective technical indicators, saving hours of manual screening. Then conduct interviews to assess problem-solving, communication, and cultural fit. We're a powerful first-pass filter, not a replacement for human judgment.
We analyze code quality across all major backend technologies
Node.js, Python, Java, Go, Ruby, PHP, .NET, Rust, Elixir
Most developers specialize in 1-2 of these
PostgreSQL, MySQL, MongoDB, Redis, Elasticsearch, Cassandra, DynamoDB
Typically expertise in 2-3 database systems
AWS, GCP, Azure, Docker, Kubernetes, Terraform, Serverless
Usually focused on one primary cloud platform
REST, GraphQL, gRPC, WebSockets, Message Queues (RabbitMQ, Kafka)
Experience varies by project requirements
Looking for Rust microservices experts? Elixir/Phoenix developers? GraphQL specialists? Our analysis adapts to different tech stacks - we measure quality indicators specific to each technology.
Post Your RequirementsSearch LinkedIn for 'backend developer' keywords
Filter by measurable code quality metrics: test coverage >60%, security score >8/10, complexity under threshold
Read through 200 generic resumes claiming '5 years Node.js experience'
See actual Node.js projects with analysis: 4.2 avg complexity, 73% test coverage, 12 security issues resolved over time
Guess technical ability from job titles and company names
Review automated analysis summary: static analyzer score, code duplication %, error handling patterns
Hope their claimed 'database optimization expertise' is real
See PostgreSQL usage patterns: parameterized queries, proper indexing in migrations, connection pooling implemented
Spend hours manually reviewing portfolios for code quality
Pre-analyzed profiles show key metrics upfront: complexity trends, test coverage growth, security practices
Unclear seniority - inflated titles mask actual experience
See technical progression: code quality improved 40% over 3 years, test coverage 0% → 75%, complexity reduced
Stop chasing invoices. Glopay ensures every contractor sends proper, tax-compliant documentation.
Typical compensation for backend developers by region (2025-2025)
Ranges vary by city, company size, and tech stack specialization. Remote positions typically offer 70-90% of local rates.
We run automated analysis on public repositories using professional tooling - static analyzers, security scanners, and code quality metrics. We measure test coverage, error handling patterns, code complexity, security practices, and track how these metrics evolve over time. This gives us concrete indicators of code quality and best practices adherence.
Most companies receive their first batch of 3-8 matched backend developers within 24-48 hours of posting a job description. For specialized tech stacks, it may take slightly longer. We prioritize developers with measurable indicators of experience in your specific technologies.
Yes. Every backend developer profile includes links to their analyzed GitHub repositories. You can review the actual code, our analysis summary showing code quality metrics, and specific examples of their work with your tech stack before making contact.
We analyze contribution timeline (years of active development), code quality progression over time, project complexity, architectural patterns, and best practices adherence. These are indicators, not guarantees - we recommend using our analysis as a strong filter, then validating fit through interviews.
Our analysis works best for developers with active public GitHub presence. For candidates with primarily private repository experience, we recommend supplementing our analysis with traditional resume review and technical interviews. We're transparent about this limitation.
No limits. We send you all candidates meeting your criteria with measurable technical indicators. For popular tech stacks like Node.js or Python, you might receive 15-25 matches. For specialized requirements, you'll get 3-8 more precisely matched candidates.
Post your job description. Get pre-analyzed developer profiles with code quality metrics, test coverage scores, and security assessments within 24-48 hours. Free forever.
No subscription fees • No per-hire charges • No hidden costs