Senior AI Engineer for QA and SDLC

Job Location

WARSAW PLANT & GOJob Description

As the Senior AI Engineer for QA and SDLC at P&G, you will lead the transformation of software quality assurrance across critical IT products and transformations around Digital Marketing and Commerce.

You will define and build the next generation of quality engineering capabilities by combining AI engineering, agentic automation, intelligent testing, DevOps, software engineering, and product management.

You will explore and implement AI agents and automation capabilities that improve how software is validated, released, monitored, and continuously optimized. Your work will help teams move from manual and reactive testing toward AI-enabled, continuously learning quality engineering.

You will operate at the center of a large-scale P&G transformation, partnering with engineering, architecture, product, and DevOps teams. The role offers an opportunity to work with cutting-edge technologies, shape enterprise-wide engineering standards, and establish reusable AI capabilities that can improve software quality at scale as well as speed to market.

Job ResponsibilitiesLead AI-driven quality transformation

• Define and execute the vision and roadmap for AI-enabled Quality Engineering across IT products and platforms.
• Transform traditional quality assurance into a proactive, automated, and engineering-led discipline embedded throughout the software development lifecycle.
• Identify high-value opportunities for AI agents, generative AI, machine learning, and intelligent automation to improve test design, execution, analysis, and defect prevention.
• Collaborate with P&G Horizontal DevOps and QA Communities of Practice to apply best practices and contribute to company wide practices and tools.

Build agentic QA capabilities

• Re-apply, design and implement AI-assisted and agentic capabilities for QA activities across SDLC - in particular: orchestration for test scope definition, test execution, test data generation, regression impact assessment, release readiness evaluation.

Engineer automation at scale

• Define and lead implementation of scalable test-automation strategies covering functional, integration, API, performance, security, accessibility, and end-to-end testing.
• Lead the modernization of test frameworks and integrate automated quality controls directly into CI/CD pipelines.
• Reduce manual testing through risk-based automation, intelligent test selection, reusable frameworks, and self-service engineering capabilities.
• Drive quality earlier in the lifecycle through shift-left practices, automated design validation, contract testing, static analysis, and continuous verification.