Generative AI -Software Engineer-Senior Associate

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.

Skills

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.
  
  

• When you join PwC Acceleration Centers (ACs), you step into a pivotal role focused on actively supporting various Acceleration Center services, from Advisory to Assurance, Tax and Business Services. In our innovative hubs, you’ll engage in challenging projects and provide distinctive services to support client engagements through enhanced quality and innovation. You’ll also participate in dynamic and digitally enabled training that is designed to grow your technical and professional skills.
• As part of the Data and Analytics team you will develop and implement innovative software solutions for GenAI projects. As a Senior Associate, you will partner with product, ML, and DevOps teams to translate business goals into impactful GenAI software solutions while leveraging your knowledge in programming and system architecture. This position provides an exciting opportunity to make a significant impact in a collaborative and innovative environment, advancing your career in cutting-edge technologies.
  
  

• Collaborate with cross-functional teams to understand business needs and translate them into backend functionalities for GenAI and Agentic AI projects.
• Design, develop, and maintain scalable backend solutions, including event-driven architectures and integration with external systems/APIs.
• Manage data storage solutions using relational (PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB) databases to support AI applications in production.
• Utilize containerization (Kubernetes) and implement DevOps practices, including CI/CD pipelines (Azure DevOps, GitHub Actions), for efficient deployment and scalability.
• Build and integrate APIs using Python frameworks (Flask, FastAPI) and collaborate with data scientists, engineers, and DevOps teams for seamless AI model deployment.
  
  

• Bachelors & Masters Degree
• 4 years of experience
• Oral and written proficiency in English required
  
  

• Proficient with LLM interaction frameworks like LangChain, Semantic Kernel, and LlamaIndex, and experienced in integrating, scaling, and deploying GenAI and agentic applications in production.
• Skilled in setting up data pipelines for both model training and real-time inference to support AI workloads efficiently.
• Advanced Python expertise including OOP, asynchronous programming (asyncio), concurrency (multithreading, multiprocessing), design patterns, memory management, and performance optimization for scalable GenAI systems.
• Strong foundation in data structures, algorithms, software design principles (SOLID, clean architecture), and hands-on experience with cloud-native development on Azure/AWS, including serverless, microservices, and container orchestration (Kubernetes, Docker).
• Experience with additional OOP languages (Java, C++, C#) and familiarity with WebSocket implementations for real-time application functionality.