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Test Automation Engineer
3 weeks ago
This is not just a QA role — you'll be writing production-grade code, contributing to continuous integration and delivery pipelines, and building automated testing solutions that help us ship faster without compromising stability.
Key Responsibilities:- Automation Development: Design, implement, and maintain automated test frameworks for backend, frontend, APIs, and blockchain interactions.
- Blockchain Testing: Simulate on-chain transactions, wallet interactions, and smart contract behavior for EVM-compatible chains and/or Solana.
- Ai System Validation: Test AI-driven decision-making flows, ensuring correctness, performance, and resilience in production environments.
- Performance & Load Testing: Stress-test systems handling large datasets, market data feeds, and high-throughput API calls.
- Security & Reliability: Implement tests for authentication, data integrity, rate-limiting, and vulnerability detection.
- Collaboration: Work closely with developers to ensure testability, participate in code reviews, and advocate for best engineering practices.
- CI/CD Integration: Maintain test suites in the build pipeline, ensuring automated regression testing on every commit.
- Programming Skills: Proficiency in Python and/or JavaScript/TypeScript for automation.
- Test Frameworks: Experience with PyTest, Playwright, Cypress, Jest, or equivalent.
- Api Testing: Strong experience testing REST and WebSocket APIs; familiarity with tools like Postman, Newman, or k6.
- Blockchain Knowledge: Understanding of crypto wallets, blockchain transactions, RPC calls, and smart contract testing (e.g., Hardhat, Foundry, Anchor).
- Ci/Cd: Hands-on with GitHub Actions, GitLab CI, or similar pipelines.
- Databases: Experience with SQL/NoSQL databases, preferably PostgreSQL and/or Redis.
- Performance Testing: Familiarity with load testing and benchmarking tools.
- Version Control: Proficient with Git and collaborative workflows.
Nice to Have:
- Experience with DeFi protocols, tokenomics, and blockchain analytics.
- Exposure to ML model testing, dataset validation, and AI explainability checks.
- Knowledge of Docker and Kubernetes for environment management.
- Security testing tools (e.g., OWASP ZAP, MythX, Slither).
- Familiarity with event-driven systems and real-time data pipelines.
Benefits of this opportunity include:
- Contribution to cutting-edge technology projects.
- Opportunities for professional growth and development.
- A dynamic and supportive team environment.