Industry/Sector
Not Applicable
Specialism
Data, Analytics & AI
Management Level
Manager
Job Description & Summary
At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals.
In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems.
Job Title
Manager - Generative AI-Software Engineering
Experience
8+ years
PwC US - Acceleration Center is seeking a seasoned GenAI Software Engineer to join our team as a Manager. This role is pivotal in leading the development and implementation of innovative software solutions for our GenAI projects. The ideal candidate should have a robust background in software engineering, with a deep focus on GenAI technologies, and possess expert knowledge of programming, event-driven architectures, containerization, and data lakes.
Responsibilities
- Lead and manage a team of software engineers in developing, implementing, and maintaining advanced software solutions for GenAI projects.
- Engage with senior leadership and cross-functional teams to gather business requirements, identify opportunities for technological enhancements, and ensure alignment with organizational goals.
- Design and implement sophisticated event-driven architectures to support real-time data processing and analysis.
- Oversee the use of containerization technologies such as Kubernetes to promote efficient deployment and scalability of software applications.
- Supervise the development and management of extensive data lakes, ensuring effective storage and handling of large volumes of structured and unstructured data.
- Champion the use of Python OR Java as the primary programming language, setting high standards for software development within the team.
- Facilitate close collaboration between software engineers, data scientists, data engineers, and DevOps teams to ensure seamless integration and deployment of GenAI models.
- Maintain a cutting-edge knowledge base in GenAI technologies to drive innovation and enhance software engineering processes continually.
- Translate complex business needs into robust technical solutions, contributing to strategic decision-making processes.
- Establish and document software engineering processes, methodologies, and best practices, promoting a culture of excellence.
- Ensure continuous professional development of the team by maintaining and acquiring new solution architecture certificates and adhering to industry best practices.
Requirements
- Python OR Java Proficiency: Minimum 3 years of hands-on experience building applications with Python OR Java.
- Scalable System Design: Solid understanding of designing and architecting scalable Python OR Java applications, particularly for Gen AI use cases, with a strong understanding of various components and systems architecture patterns to make cohesive and decoupled, scalable applications.
- Web Frameworks: Familiarity with Python OR Java web frameworks (Flask, FastAPI) for building web applications around AI models.
- Modular Design & Security: Demonstrated ability to design applications with modularity, reusability, and security best practices in mind (session management, vulnerability prevention, etc.).
- Cloud-Native Development: Familiarity with cloud-native development patterns and tools (e.g., REST APIs, microservices, serverless functions).
- Cloud Deployments: Experience deploying and managing containerized applications on Azure/AWS (Azure Kubernetes Service, Azure Container Instances, or similar).
- Version Control (Git): Strong proficiency in Git for effective code collaboration and management.
- CI/CD: Knowledge of continuous integration and deployment (CI/CD) practices on cloud platforms.
Preferred Skills
- Gen AI Frameworks: Experience with LLM frameworks or tools for interacting with LLMs such as LangChain, Semantic Kernel, LlamaIndex.
- Data Pipelines: Experience in setting up data pipelines for model training and real-time inference.
- Current solution architecture certifications and a commitment to ongoing professional development.
Educational Background
- BE / B.Tech / MCA / M.Sc / M.E / M.Tech / Master’s Degree / MBA / Any degree
Travel Requirements
0%
