Senior Software Quality Engineer, AI Automation, Customer Decision Hub

Senior Software Quality Engineer, AI Automation, Customer Decision Hub

At Pega, we’re reshaping how the world’s largest enterprises connect with their customers, one intelligent decision at a time. Our flagship 1:1 engagement solution, Customer Decision Hub (CDH), is changing the way businesses respond to customer needs across every channel with precision and agility.

At the core of this innovation is our runtime engine. It’s designed to process massive volumes of data, apply advanced analytical models, and orchestrate actions at scale in both real‑time and batch environments. This is where you come in.

Are you ready to redefine how the world approaches software testing? In this role, you’ll be a driving force in transforming quality engineering through cutting‑edge AI technologies. You’ll work at the intersection of artificial intelligence and software validation, using advanced prompting techniques and customer‑focused testing strategies to build intelligent systems that uphold the highest standards of software quality.

• Design and implement intelligent testing systems powered by AI models to autonomously explore and validate both frontend and backend components.
• Develop advanced prompting strategies that translate manual test strategies into automated test scenarios.
• Create automated solutions that analyze customer escalations and incident data to detect patterns, identify gaps in test coverage, and utilize feedback loops to generate new test cases and validation flows.
• Collaborate closely with product managers and engineers to translate their visions into scalable, AI‑driven validation strategies.

• An engineer who is passionate about quality‑first solutions and thrives on understanding end‑user behavior.
• A results‑oriented technologist who is passionate about leveraging AI in fast‑paced, collaborative, and cross‑functional environments.
• A strong communicator with a demonstrated ability to engage successfully across internal teams.
• An individual who can rapidly pick up new skills and is passionate about software development and adopting new technologies, particularly in the GenAI domain.
• An engineer with the ability to synthesize user feedback into actionable AI prompts and testing strategies.

• Bachelor’s degree in software engineering, computer science, or a related technical field.
• Minimum of 5‑7 years of experience in software quality engineering, including at least 2 years focused on AI‑driven automation, intelligent testing frameworks, or machine learning validation.
• Strong background in software engineering and proven experience applying AI/ML models (e.g., LLMs, computer vision, NLP) to software testing and validation.
• Proven ability to navigate Agile and Scrum development life cycles, with a clear understanding of how quality engineering contributes to iterative planning, continuous integration, and collaborative delivery in AI‑driven automation environments.
• Experience using the following:
  Test automation frameworks (Java, Selenium, Playwright, TestNG, Cucumber, etc.), Dev Ops technologies (Git, Docker, Gradle, Jenkins, etc.), Cloud Platforms (AWS, Azure, GCP).
• Demonstrated success in testing systems that operate across full‑stack architectures.
• Integrated AI agent frameworks into complex workflows and rapidly prototyped in GenAI environments, resulting in accelerated iteration cycles and improved system adaptability through early‑stage “vibe testing.”
• Highly collaborative environment for designing and developing new ideas and features.
• A culture where employees engage deeply, own outcomes and lead from the front.
• Continuous learning and career opportunities – internal and external training, area for own initiatives, Rotation Program.
• An inclusive, agile, and flexible work environment.

Base salary range for this role is 94,900 – 141,900 USD annually. This role may also be eligible for annual bonus or commission, as well as benefits and other incentives.

The final compensation will be determined during the offer process based on the candidate’s education, experience, skills, and qualifications, as…