SDET

Responsibilities

• Build automation frameworks, reusable test utilities, and quality tooling for scalable testing, validation, and release confidence across integrations, connectors, and agent workflows.
• Design and execute tests for complex integration workflows involving APIs, contracts, compatibility, authentication, webhooks, retries, idempotency, asynchronous workflows, and third-party dependencies.
• Build and maintain automated functional, API, integration, contract, and regression test suites, quality gates, and CI/CD checks.
• Analyze quality signals and engineering metrics to identify risks, prevent regressions, and support release decisions.
• Build AI-powered validation systems, agents, and automated workflows to validate integrations, detect regressions, investigate failures, and scale quality.
• Improve testing strategies, coverage, testing patterns, and validation practices across integration, API, contract, and end-to-end layers.
• Develop testing and evaluation approaches for AI-powered workflows, tool-calling agents, and systems with variable outputs.
• Investigate production issues, contribute to root-cause analysis, improve test observability, and implement preventive reliability improvements.
• Partner with engineers to improve testability, influence design decisions, and promote quality practices.

Requirements

Automation and Quality Engineering

• Build automation frameworks, quality platforms, and developer tooling.
• Write clean, maintainable automation and validation code.
• Apply appropriate quality strategies across API, integration, contract, and end-to-end testing.
• Use CI/CD quality gates and release-confidence practices while reducing flaky tests.

Complex Systems and Integrations

• Reason about API behavior, authentication, retries, idempotency, eventual consistency, and distributed systems.
• Test, validate, and debug integration-heavy systems involving multiple services and external dependencies.
• Use logs, traces, metrics, and production signals to investigate failures and improve reliability.

AI-Native Systems

• Use AI to accelerate testing, debugging, automation, and engineering workflows with validation and critical thinking.
• Understand AI agents, MCP/tool-calling systems, and LLM-powered workflows.
• Evaluate and validate non-deterministic systems.

Product Judgment and Collaboration

• Make risk-based engineering decisions balancing customer impact, reliability, delivery speed, and validation depth.
• Understand user workflows and business impact, prioritize high-risk areas, and focus effort on customer confidence.
• Take ownership of issues through resolution and continuously improve quality outcomes.
• Communicate clearly, explain technical trade-offs, and collaborate across engineering teams.
• Learn proactively, seek context, and independently solve ambiguous problems in a fast-moving environment.