Inperson Interview_AI SDET_NY

Title:

AI SDET

Location:

New York, NY (Onsite) (F2F Interview required)

Work Arrangement:
Onsite

Employment Type:

Contract

Duration: 6 Months

Primary

Skills:

AI, SDET, Java/Python

The ideal candidate will have expert-level Java and/or Python, strong Playwright and API automation experience, hands-on expertise building automation frameworks from scratch, and a solid understanding of microservices, distributed systems, CI/CD, SQL, observability, and high-availability platforms.

The candidate will work closely with developers, architects, and engineering teams to ensure quality is designed in, automated, observable, and enforced throughout the SDLC. Experience leveraging AI/GenAI, Prompt Engineering, AI Evaluation, AI Agents, MCP, and Spec-Driven Development (SDD) is required.

• Design and build scalable automation frameworks from scratch across UI, API, integration, and event-driven layers.
• Develop robust automation using Java and/or Python, applying OOP, Data Structures, and Design Patterns.
• Build modern UI automation solutions using Playwright.
• Develop and maintain strong REST API, microservices, and integration testing frameworks.
• Implement practical and maintainable BDD solutions.
• Establish automated quality gates and integrate them into CI/CD pipelines.
• Act as a Quality Architect, influencing system design, testability, automation strategy, and release readiness.
• Engineer quality across microservices, distributed systems, and high-availability platforms.
• Drive continuous improvement in automation coverage, reliability, maintainability, and execution efficiency.

• Test and validate high-availability, low-latency, and mission-critical systems.
• Design and execute performance, load, stress, resilience, and reliability testing.
• Validate microservices and event-driven architectures across distributed environments.
• Troubleshoot application and test failures using logs, metrics, and distributed traces.
• Leverage production telemetry and observability data to identify quality risks and improve QE strategy.
• Participate in incident triage, root cause analysis, production validation, and release certification.

• Leverage AI/GenAI tools to accelerate test design, automation development, coding, debugging, and test analysis.
• Apply Prompt Engineering and context management techniques to improve AI-assisted engineering workflows.
• Design and execute AI evaluation frameworks to validate AI-generated code, tests, and outputs.
• Apply Spec-Driven Development (SDD) to align specifications, implementation, automation, and validation.
• Develop and integrate AI Agents, skills, and Model Context Protocol (MCP) integrations.
• Safely integrate AI-assisted quality engineering workflows into CI/CD pipelines.
• Establish verification practices for AI-generated outputs and ensure responsible use of AI in engineering processes.

• Own end-to-end production quality, from test strategy through release certification and production validation.
• Define and maintain effective regression testing strategies.
• Partner with developers and architects to identify defects and quality risks early in the SDLC.
• Support production releases and incident triage, including participation in on-call rotations.
• Perform root cause analysis and drive corrective and preventive actions.
• Ensure quality standards are consistently applied across development, testing, deployment, and production environments.

• Expert-level proficiency in Java and/or Python.
• Strong understanding of Object-Oriented Programming, Data Structures, and Design Patterns.
• Proven experience building test automation frameworks from scratch.
• Hands-on…