Senior Software Development Engineer in Test (SDET)

About the Role

We are building StartaleApp, a next-generation Web3 application that brings together a wide range of blockchain and DeFi functionality into a single user experience. The platform interacts with multiple blockchain networks, smart contracts, wallets, tokens, and on-chain protocols, creating complex flows that span frontend applications, backend services, blockchain infrastructure, and decentralized systems.

As a Senior Software Development Engineer in Test (SDET), you will own the engineering foundations of quality across the platform. Rather than simply writing automated tests, you will design and build the testing architecture, automation frameworks, developer tooling, CI/CD integrations, and AI-powered quality systems that enable the entire engineering organization to ship quickly and confidently.

You will work across frontend applications, backend services, blockchain integrations, smart contracts, and DeFi functionality to ensure correctness, reliability, and security across complex real-world Web3 flows.

This is a highly technical software engineering role focused on building quality systems, not performing manual testing. We are looking for engineers who enjoy building platforms, tooling, and automation that other engineers rely on every day.

Key Responsibilities

Quality Engineering Platform

- Design, build, and evolve the company’s quality engineering platform.

- Define testing architecture across unit, integration, contract, API, and end-to-end testing.

- Build and maintain reusable testing frameworks, shared libraries, fixtures, and developer tooling.

- Continuously improve developer experience around testing and quality engineering.

AI-powered Quality Engineering

- Design and implement AI-assisted quality engineering workflows throughout the software development lifecycle.

- Build systems that leverage LLMs for automated test generation, test maintenance, failure analysis, root cause identification, and regression detection.

- Develop internal tooling that combines traditional automation with AI to improve engineering productivity and software quality.

- Continuously evaluate emerging AI technologies and integrate them into the team’s quality engineering practices.

Test Automation & CI/CD

- Build comprehensive automated test suites covering APIs, backend services, frontend applications, blockchain interactions, and Web3 user flows.

- Integrate automated testing into CI/CD pipelines with fast feedback cycles and automated quality gates.

- Optimize test execution through parallelization, intelligent test selection, caching, and infrastructure improvements.

- Drive automation-first engineering practices across development teams.

Web3 & DeFi Validation

- Validate complex Web3 user flows involving wallets, authentication, token operations, smart contracts, and on-chain transactions.

- Test interactions between frontend applications, backend services, blockchain networks, RPC providers, indexers, and smart contracts.

- Validate transaction lifecycle and state transitions, including transaction submission, confirmation, failure, retries, reorgs, and delayed or inconsistent blockchain state.

- Design automated regression suites covering critical Web3 and DeFi functionality.

- Validate token transfers, swaps, liquidity operations, staking, lending, and other DeFi flows as applicable to the platform.

- Test edge cases involving gas estimation, transaction failures, insufficient balances, slippage, network conditions, and blockchain state changes.

Infrastructure, Performance & Reliability

- Build and maintain containerized testing environments using Docker and modern infrastructure tooling.

- Design contract, integration, and end-to-end testing strategies for distributed and blockchain-based systems.

- Develop automated load, stress, endurance, and resilience testing for backend services and Web3 infrastructure.

- Validate system behavior during degraded conditions, network failures, RPC failures, timeouts, blockchain congestion, transaction failures, and infrastructure outages.

- Collaborate with engineering teams to improve system observability and accelerate production issue investigation.

Qualifications

Required Experience

- 5+ years of experience in Software Development Engineer in Test (SDET), Quality Engineering, Test Automation, or Software Engineering roles.

- Strong software engineering skills with JavaScript or TypeScript.

- Experience designing testing architecture for complex distributed systems.

- Experience building scalable automation frameworks and reusable testing libraries from scratch.

- Strong experience with modern end-to-end testing frameworks such as Playwright or Cypress.

- Strong experience testing APIs (REST, JSON-RPC, GraphQL, WebSocket, or similar).

- Experience integrating automated testing into CI/CD pipelines.

- Experience working with Docker and containerized testing environments.

- Experience designing API, integration, contract, and end-to-end testing strategies.

- Experience debugging distributed systems across frontend, backend, APIs, databases, and infrastructure.

- Experience designing and implementing performance, load, and reliability testing.

- Strong understanding of observability practices and production debugging.

- Experience testing complex transactional, financial, distributed, or high-throughput systems.

- Strong communication skills and the ability to collaborate effectively across engineering disciplines.

Nice-to-Have

- Professional experience testing Web3 applications, blockchain infrastructure, or DeFi protocols.

- Strong understanding of blockchain fundamentals, smart contracts, wallets, tokens, RPCs, and on-chain transaction flows.

- Experience testing DeFi functionality such as swaps, liquidity provision, staking, lending, borrowing, or other on-chain financial protocols.

- Experience with blockchain testing frameworks, local networks, testnets, or smart contract development environments.

- Experience designing AI-assisted testing systems or integrating LLMs into QA workflows.

- Experience using AI for automated test generation, failure analysis, regression detection, code review, or test maintenance.

- Experience evaluating and integrating AI tools to improve engineering productivity.

- Experience with Kubernetes and cloud-native infrastructure.

- Experience with observability platforms such as OpenTelemetry, Prometheus, Grafana, or Datadog.