• Customer Embedding & Delivery: Work directly in customer environments to understand their business, workflows, and technical constraints firsthand. Contribute to the end-to-end delivery of solutions from scoping through implementation, verification, and deployment building trust as a reliable partner for both features and quality. Bring clarity to evolving problem spaces.
• Agentic Quality: Apply an agent-first methodology using Generative AI. Create structured, behavior-oriented prompts and specifications that guide AI agents to generate implementation code and the tests that verify it. Confirm that AI-generated code actually conforms to intent closing the gap between what was asked for and what was built.
• Test Strategy & Automation: Design and build test frameworks and automation across the stack; unit, integration, contract, end-to-end, performance, and load testing. Help establish quality gates, test orchestration, and coverage standards that scale across polyglot codebases and customer teams.
• Feature Development: Build production-grade features alongside your quality work. Contribute to scalable, resilient systems and translate business requirements into technical specifications that AI agents and engineering teams use as the foundation for development.
• AI-Assisted Engineering: Integrate AI tools like Claude Code, Kiro and Cursor into development and testing workflows. Evolve your engineering practice from manual coding and test-writing to auditing, validating, and refining AI-generated solutions. Apply the judgment to catch coverage theater, AI-generated tests that pass but prove nothing. Follow repeatable AI-driven development patterns.
• Design for Quality: Build with testability, resilience, and observability in mind from the outset. Participate in implementation reviews to ensure alignment with patterns, performance, and security expectations.
• Polyglot Development: Write and test production-grade code across multiple languages and paradigms (e.g., TypeScript, Python, Go, .NET, Java) based on specific problem domains. Ramp into unfamiliar stacks or codebases.
• Enablement & Knowledge Transfer: Help raise the engineering and quality bar within customer teams through pairing, code reviews, and mentoring. Support customer engineers in adopting agentic development, AI-assisted workflows, shift-left testing, and modern architectural practices so solutions remain sustainable long-term.

Requirements

• 5-7 Years of Experience: Proven experience as a Senior SDET, Test Architect, Test Engineer, or Software Engineer delivering distributed systems with a strong quality focus.
• Customer-Facing Aptitude: Ability to work directly with customers and stakeholders communicating clearly with both technical and non-technical audiences, managing expectations, and building trust.
• Test Strategy & Automation: Strong experience designing test frameworks and automation across the stack; unit, integration, contract, E2E, performance, and load. Hands-on with tools such as Playwright, Cypress, Selenium, Jest/Vitest, pytest, JUnit, and k6.
• Full-Stack Development: Solid ability to build production features, not just test them.
• Frontend: Proficiency with modern JavaScript/TypeScript frameworks (e.g., React, Next.js, Vue, Svelte) and their testing ecosystems
• Backend: Experience building and testing APIs (REST, GraphQL, gRPC) and server-side architecture using languages such as Node.js, Go, or Python.
• Polyglot Proficiency: Proficiency in at least two distinct programming languages (e.g., TypeScript, Python, Go, .NET, Java).
• Generative AI & Agentic Development Experience: Experience using agentic development tools and workflows where AI agents drive code and test generation. Ability to write effective prompts and specifications and manage the lifecycle of AI-generated artifacts, including verifying their correctness.
• CI/CD & Quality Gates: Experience with CI/CD pipelines (GitHub Actions, GitLab CI, or similar), quality gates, and test orchestration in automated delivery flows.
• Observability & Reliability: Familiarity with monitoring, tracing, SLOs, and resilience/chaos testing to validate systems under real-world conditions.
• Business-Aligned Engineering: Ability to align quality strategy and feature development with customer business goals.
• Rapid Skill Acquisition: Ability to acquire proficiency in unknown codebases or new languages.
• System Design: Familiarity with microservices, event-driven architecture, cloud-native patterns (Kubernetes, Docker), and databases (SQL & NoSQL).
• Cloud Providers: AWS or Azure.
• Willingness to Travel: Comfort with occasional travel to customer sites as needed.
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