AI Full Stack Engineer - Senior Associate - Commercial Technology & Innovation

Industry/Sector

Not Applicable

Specialism

Data Science

Management Level

Senior Associate

Job Description & Summary

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems.

Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow.

Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:

• Respond effectively to the diverse perspectives, needs, and feelings of others.
• Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems.
• Use critical thinking to break down complex concepts.
• Understand the broader objectives of your project or role and how your work fits into the overall strategy.
• Develop a deeper understanding of the business context and how it is changing.
• Use reflection to develop self awareness, enhance strengths and address development areas.
• Interpret data to inform insights and recommendations.
• Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.

At Commercial Technology & Innovation (CT&I), we’re not just building technology—we’re reshaping the future of business. As the tech engine behind PwC’s Advisory platforms, we embed AI, automation, and cutting-edge engineering into everything we do, delivering smarter, faster, and bolder solutions that drive real-world impact. Our mission is to power possibility—partnering with bold thinkers to turn vision into reality and transform industries at scale. 

We’re looking for passionate, curious, and purpose-driven engineers who want to make a difference. If you’re ready to innovate with intent, drive business outcomes, and help lead the AI-enabled transformation of one of the world’s most trusted organizations, your journey starts here. 

The Opportunity

We’re seeking an innovative and versatile AI Engineer who combines strong machine learning expertise with modern application development skills. In this role, you’ll design and deploy AI-powered solutions that are scalable, user-friendly, and integrated within real-world applications. You’ll work cross-functionally with data scientists, ML engineers, backend/frontend developers, and product teams to deliver impactful AI products. As a Senior Associate, you will analyze complex problems, mentor others, and maintain elevated standards while navigating intricate situations to drive project success.

Responsibilities

- Uphold exceptional standards in deliverables

- Work with diverse teams to improve product development

- Navigate complex scenarios to secure project success

- Maintain remarkable quality and performance in tasks

- Foster a culture of continuous improvement and innovation

What You Must Have

- Bachelor's Degree

- 3 years of experience

What Sets You Apart

- Master's Degree in Computer Engineering, Computer Science, Artificial Intelligence and Robotics, Software Engineering, Data Processing/Analytics/Science preferred

- Designing and deploying machine learning models and LLMs

- Developing scalable, cloud-native microservices with Docker and Kubernetes

- Building end-to-end AI applications for web, mobile, or API-first platforms utilizing technolog