AI Architect (QA Automation) - 251

We're looking for an AI Architect to lead how our testing organization uses AI to improve quality, speed, coverage, and insight across the software delivery lifecycle.

• This person will define the AI strategy for QA and testing, design AI-enabled testing solutions, guide tool selection and integration, and help teams adopt AI responsibly in day-to-day testing activities.

Typical task breakdown:

• Define the AI vision and architecture for the testing function.

• Identify testing activities that can be improved with AI, including: test case generation, test data creation, automated test maintenance, defect prediction, root cause analysis, log and failure analysis, requirements-to-test traceability, risk-based test prioritization, intelligent regression selection

• Design and implement AI-enabled frameworks for: functional testing, API testing, UI automation, performance testing, security testing support, exploratory testing augmentation

• Partner with QA, developers, DevOps, product managers, and data teams to embed AI into CI/CD and quality engineering workflows.

• Evaluate and recommend AI/ML, GenAI, and test automation tools.

• Establish standards for AI governance, privacy, security, explainability, and responsible usage in testing.

• Create architecture for integrating LLMs, test repositories, defect systems, observability tools, and CI platforms.

• Define metrics to measure the effectiveness of AI in testing, such as:defect leakage, automation coverage, test execution efficiency, flaky test reduction

• mean time to diagnose failures, release quality trends

• Mentor QA engineers and SDETs on AI-assisted testing practices.

• Lead pilots, proofs of concept, and scaled rollout of AI testing capabilities.

• Ensure compliance with enterprise policies for data handling and model usage.

Years of experience: 8-10 yrs experience

• Degree requirement: Bachelor's degree and 8+ years of experience

Required Technical Skills

(Required)

• 8+ years in software testing, QA automation, quality engineering, or test architecture.

• 3+ years designing or implementing AI/ML or GenAI-based solutions in enterprise environments.

• Strong understanding of: software testing methodologies, test automation frameworks

• SDLC/STLC

• CI/CD pipelines

• quality engineering practices

• Experience with AI technologies such as: machine learning models, NLP, LLMs, prompt engineering, retrieval-augmented generation concepts

• AI agents/workflow automation

• Hands-on experience with tools/languages such as Python, Java, JavaScript, SQL, and test tools like Selenium, Playwright, Cypress, Appium, JUnit, TestNG, PyTest, or similar.

• Experience integrating with platforms such as Jira, Azure DevOps, GitHub, Jenkins, GitLab, or cloud test platforms.

• Knowledge of test analytics, data pipelines, and observability/log analysis tools.

• Strong architecture and design skills for scalable, secure enterprise solution

(Desired)

• Experience building AI copilots or assistants for QA teams.

• Familiarity with vector databases, model evaluation, and MLOps/LLMOps concepts.

• Experience with cloud platforms such as AWS, Azure, or GCP.

• Understanding of regulated environments and compliance requirements.

• Certifications in test architecture, cloud, AI/ML, or enterprise architecture.

• Hands on experience with Python

• development experience in AWS Cloud technology

• Experience in TDD, continuous integration, code review practice is strongly desired

• Experience with Apigee or other API gateways is a plus

• Experience with DevOps concepts and tools (e.g., CI/CD, Jenkins, Git)

• At least 2 years working on an Agile team with a solid understanding of Agile/Lean practices.

• Understanding of a micro service Architecture

• Experience load and performance testing

• Strong documentation skills

Key skills

• AI strategy for testing

• test architecture

• quality engineering leadership

• GenAI and LLM application design

• automation framework design

• data-driven decision making

• stakeholder communication

• governance and risk management

• Team enablement

Soft Skills

(Required)

• Ability to adapt quickly to a complex environment

• Pro-active, flexible and creative

• Very strong communication skills and the ability to collaborate with developers and business users.