2025 started off well for Dror Avrilingi. The Israel-based industry veteran, who has been with software development firm Amdocs for nearly two decades, was recently promoted within the company’s new studio-based organizational structure, becoming head of Quality Engineering (QE), Data & AI Studios at the end of last year.
The appointment builds on Avrilingi’s 25-year track record in quality engineering. His previous role as Head of Amdocs Quality Engineering (AQE) International saw him develop the company’s global strategy and establish the NextGen QE consortium, which brings together industry experts to explore emerging trends.
Now, his focus has moved to expanding AQE’s generative AI capabilities.
In a conversation with QA Financial, Avrilingi outlined Amdocs’ priorities for the year ahead, including expanding its QE capabilities while promoting closer coordination between the QE and Data & AI studios to enhance customer outcomes.
This organisational structure is part of Amdocs’ recent reorganization of its Global Services division to streamline its SI practice.
The company now operates four key studios: QE, Data & AI, Cloud, and Digital Experience. Avrilingi is overseeing two of these pillars, with a particular focus on integrating data management with quality engineering practices.
Going forward, he will look to deliver AI and GenAI solutions that enhance data accuracy, streamline compliance processes, and provide predictive analytics for risk management and customer insights.
This will help financial institutions make more informed decisions, improve operational efficiency, and offer personalized customer experiences.
“We’re moving very quickly into a new phase, where we are combining the strengths of different studios,” reflected Avrilingi.
Discussing the central role of data, he observed, “Data is at the heart of everything we do now, whether it’s for optimizing financial operations, creating screens with Generative AI, or running testing procedures. Each studio relies on high-quality data to realize their potential.”
Synergies between QE and data & AI
Avrilingi emphasizes the importance of synergy between the different studios, particularly in ensuring that data is both prepared and used effectively. A key part of his role is managing the intersection of AI, analytics, and testing, ensuring that each process is aligned with organizational goals.
According to Avrilingi, “The integration of data scientists’ sandboxes with testing frameworks is crucial. It’s not just about generating data quickly – it’s about making sure the right data is accessible and used responsibly.”
He pointed out that Amdocs has streamlined these processes by having one Head of R&D for technology management across both studios.
“This ensures that the two areas are aligned and can collaborate efficiently, sharing tools, methodologies, and best practices.”
“Two years ago, banks were federating their testing teams, but now there’s a shift toward centralized governance.”
– Dror Avrilingi
As quality engineering becomes increasingly data-dependent, Avrilingi shares his philosophy on test data, focusing on two approaches: production and synthetic data.
“Production data can be expensive and hard to manage, especially in fast-paced environments with short DevOps cycles,” he emphasized.
“That’s why synthetic data is becoming so important. We use a micro-strategy approach to generate data on demand for specific testing purposes, allowing us to scale testing quickly and efficiently.”
Challenges in the financial services space

As Amdocs deepens its focus on the financial services sector, Avrilingi and his team have identified several key challenges facing banking institutions today.
Banks are increasingly shifting toward hybrid models, combining centralized testing and automation capabilities with the flexibility to allow decentralized teams to leverage shared resources.
Avrilingi described how banks are implementing these changes to improve testing efficiency and manage the challenges of legacy systems in a streamlined process.
“Two years ago, banks were federating their testing teams, but now there’s a shift toward centralized governance and enabling others to use testing frameworks effectively. This helps banks automate testing and improve efficiency,” he said.
“Additionally, legacy systems in banks create significant challenges in testing, requiring careful management to balance old and new systems in a streamlined process.”
“We’re at the beginning of a new era in quality engineering, where skill sets will shift.”
– Dror Avrilingi
Speaking on the company’s innovative approach, Avrilingi is keen to elaborate on Amdocs’ ‘Center for Enablement’ model, which contrasts with traditional centers of excellence that focus solely on execution.
“The Center for Enablement is about creating robust, reusable artifacts and enabling teams to use them efficiently, rather than being the sole executor of all tasks. This is a key shift in how we approach testing and operational efficiency,” he stressed.
Looking ahead
When asked to give his take on 2025 and beyond, Avrilingi predicts significant changes in the landscape of quality engineering.
He believes that AI will increasingly play a central role in transforming the field, with the rise of AI-augmented test engineers.
These professionals will leverage advanced prompts and AI-driven insights to conduct smarter, more efficient testing.
On the future of the industry, Avrilingi envisioned that “we’re at the beginning of a new era in quality engineering, where the skill sets will shift from traditional test engineers to those who are capable of using AI to enhance the testing process.”
“As Amdocs continues to innovate and expand its capabilities, it’s clear that the integration of AI, data, and quality engineering will be key to driving efficiency and creating value for its customers in the rapidly evolving technology landscape,” he concluded.
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