Do you want to play a key role in ensuring systems perform under pressure? We are currently looking for an experienced Performance Test Engineer with strong analytical and problem-solving skills and an eye for details, for our client in the telecommunications industry. As a Performance Test Engineer, you will be part of a QA team, but work closely with our development teams, team leaders and architects to evaluate and optimize system performance. You will design and execute performance tests, analyse results, and provide actionable insights to improve system reliability and efficiency. You will help ensure that applications are scalable, stable, and ready to handle real-world demands.

Responsibilities

· Design and execute performance, load, stress, and scalability tests (API, E2E, and infra)

· Integrate performance testing into CI/CD pipelines

· Define and track performance baselines, SLAs and SLOs, and build dashboards to visualize performance trends and bottlenecks and analyse system behaviour under different load conditions

· Identify bottlenecks and performance issues, and collaborate with our development teams to optimize our services and infrastructure

· Conduct capacity planning & scalability analysis

· Produce actionable reports and performance insights

Requirements

· Several years of experience in Cloud infrastructure and tooling (AWS)

· Strong experience with tools like JMeter, k6, Taurus DLT

· Strong documentation skills (writing Post-Mortems, Performance Briefs, etc).

· Proven ability to automate non-functional checks (performance, accessibility, visual regression, DAST, etc.)

· Experience integrating tests into CI/CD (e.g. GitHub Actions, Jenkins)

· Ability to analyse metrics: latency, throughput, error rates

· Scripting skills (Java, JavaScript, Python, or similar)

· Understanding of:

-Distributed systems & microservices

-REST APIs and async communication patterns

-Observability tools (e.g. Elastic Stack / Kibana, CloudWatch)

Nice to have

· Experience with real user monitoring (RUM) and synthetic testing

· Security/performance overlap knowledge

· Experience with autoscaling validation in Kubernetes (EKS)

· Ability to read and modify Terraform configurations to provision test environments and tune infrastructure parameters (e.g., instance types, scaling policies) during performance bottlenecks analysis.

Tech stack

· Backend: Java (Spring Boot microservices)

· Frontend: Vue 3

· Databases: Postgres (incl. Amazon Aurora), Redis

· Cloud infra: AWS (EKS, ECS, EC2, S3), Kubernetes, Terraform

· CICD: Jenkins, GitHub Action

AI Workflow Nice-to-have

· Daily, working use of at least one AI coding assistant (Claude Code, Cursor, GitHub Copilot, or similar) on real production work

· Ability to critically review AI-generated code for correctness, security, performance, and maintainability and to recognize when not to delegate to an agent

· A practical, perspective on where AI assistants help and where they don't

· Comfort iterating on prompts and context (e.g., project-level context files, structured instructions) to get reliable output