Hire Performance & SRE Engineers

A performance engineer specialises in measuring and improving the speed, scalability, and efficiency of software systems. This spans frontend (Core Web Vitals, bundle size, rendering), backend (API latency, database query time, concurrency), and infrastructure (cache hit rates, load balancer configuration, auto-scaling). Unlike a generalist developer who addresses performance reactively, a performance engineer proactively hunts bottlenecks and designs systems that stay fast under load.

Most engagements start within 48 hours of contract signing. For combined frontend and backend performance work, we often pair two specialists — a frontend performance engineer and a backend/infrastructure engineer — and one week is typical to assemble the right team.

Core Web Vitals measure three user-facing aspects of page experience: Largest Contentful Paint (how fast the main content appears), Cumulative Layout Shift (how stable the layout is while loading), and Interaction to Next Paint (how quickly the page responds to input). Google uses these scores as a ranking signal in search results, so poor scores directly impact organic traffic. They also correlate strongly with conversion rate — faster pages convert better.

We start with measurement, not assumptions. On the frontend we use Lighthouse, WebPageTest, and real-user monitoring data from CrUX or your RUM tool to identify the highest-impact issues. On the backend we profile with APM tracing, database slow query logs, and load test results. Every recommendation is backed by data showing the before/after impact, and we validate fixes with the same tools we used to diagnose.

Yes. Performance work is inherently stack-specific. Our engineers have worked with React, Next.js, Vue.js, and plain HTML on the frontend, and Node.js, Python (Django, FastAPI), Go, and Ruby on Rails on the backend. We profile within your existing codebase and recommend changes that fit your architecture rather than proposing wholesale rewrites.

Load testing simulates many concurrent users hitting your system to find the point at which it degrades or fails. If you are preparing for a product launch, a marketing campaign, or a seasonal traffic spike, load testing before the event is significantly cheaper than diagnosing a production outage after it. We design scenarios that reflect your actual traffic patterns, not synthetic uniform load that misses real-world behaviour.

We start with slow query logs and EXPLAIN ANALYZE to find the queries consuming the most time. Common fixes include adding missing indexes, rewriting queries to avoid sequential scans, eliminating N+1 query patterns with eager loading or DataLoader, implementing read replicas for analytical queries, and configuring connection pool sizing to match concurrency requirements. For extreme scale, we evaluate caching computed results in Redis to reduce database read pressure entirely.

Google classifies scores above 90 as "Good," 50–89 as "Needs Improvement," and below 50 as "Poor." A score above 90 on both mobile and desktop is a reasonable target for most products. Mobile is typically harder to optimise and more impactful — mobile users are on slower connections with less processing power, and Google uses the mobile score for search ranking. Kultrix performance engagements typically target a score of 90+ on mobile as the primary objective.

Image optimisation is one of the highest-ROI performance interventions. We convert images to WebP or AVIF formats, implement responsive srcset attributes for different viewport sizes, configure lazy loading for below-the-fold images, set explicit width and height to eliminate layout shift, and leverage CDN edge caching with appropriate cache headers. For Next.js projects, next/image handles most of this automatically when configured correctly.

Yes. Bundle size reduction is a standard part of frontend performance work. We analyse the bundle with webpack-bundle-analyzer or Rollup Visualizer, identify heavy libraries that can be replaced with lighter alternatives, implement tree shaking for unused code, split vendor and application code for better cache utilisation, and introduce dynamic imports for code paths that are not needed on initial load.

We offer three modes: a fixed-scope performance audit (one to two weeks, delivers a prioritised report), a sprint-based remediation engagement (four to eight weeks, fixes the identified issues), and an ongoing retainer for continuous performance monitoring and improvement. Most clients start with an audit and proceed to remediation based on the findings.

Results depend on the starting point and stack, but typical outcomes from Kultrix performance engagements include a 20–50 point improvement in mobile PageSpeed score, 30–60% reduction in JavaScript bundle size, 50%+ reduction in Time to First Byte through caching improvements, and meaningful improvements in conversion rate and bounce rate. We share specific case study data during the scoping call.