DevOps/LLMOps -Engineer

The Opportunity

Join our Acceleration Center India and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. Youll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll help you grow your skills so you can go further. With hands-on learning, cutting-edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a difference—every day.

As a DevOps/LLMOps Engineer - Senior Associate, you will play a pivotal role in advancing our AI-driven automation and cognitive solutions. Within our Data and Analytics Engineering practice, you will focus on developing and deploying innovative data science solutions that meet client needs. As a Senior Associate, you will leverage your skills to analyze complex problems, mentor junior team members, and maintain professional standards. You will build meaningful client relationships and navigate complex situations to deliver quality work and grow your personal brand.

In this role at PwC Acceleration Center India, you will collaborate within our Cloud Engineering, Data & Analytics network to drive impactful solutions. You will be exposed to diverse perspectives, using critical thinking to break down complex concepts and anticipate client needs. Your work will contribute to the broader objectives of our AI-Driven Automation & Cognitive Solutions practice, where you will develop a deeper understanding of the business context and how it is evolving. Embrace the opportunity to grow your technical skills and personal development while guiding others and interpreting data to inform insights and recommendations.

Responsibilities

• Developing and implementing data science workflows to support AI-driven automation solutions
• Utilizing machine learning and deep learning techniques to enhance data analysis and predictive modeling
• Building and maintaining data pipelines and data lakes to facilitate efficient data processing and storage
• Applying data engineering skills to optimize data quality and integrity across various platforms
• Leveraging programming languages such as C++, R, and MATLAB for complex data analysis and modeling
• Collaborating with cross-functional teams to integrate artificial intelligence and natural language processing into client solutions
• Conducting statistical analysis to inform data-driven decision-making processes
• Troubleshooting data science algorithms and workflows to improve performance and accuracy
• Engaging in continuous learning to stay updated with the latest advancements in data science and AI technologies

What You Must Have

• At least a Bachelor's degree
• At least 4 years of experience
• Oral and written proficiency in English required

What Sets You Apart

• Preference for at least one of the following fields of study: Artificial Intelligence and Robotics, Business Analytics, Computer and Information Science, Computer Engineering, Computer Programming, Data Processing/Analytics/Science, Engineering, Information Technology, Machine Learning, Management Information Systems, Mathematics, Statistics, Systems Engineering

Hands-on experience operationalizing ML or LLM systems in production environments.

Strong programming skills in Python and/or Bash. Familiarity with TypeScript or Java is a plus.

Experience building and managing CI/CD pipelines using GitHub Actions or Azure DevOps Pipelines.

Proficiency in containerization and orchestration technologies such as Docker and Kubernetes (AKS preferred).

Strong understanding of cloud networking concepts including VNET/VPC architecture, subnetting, routing, DNS, load balancing, firewalls, and private connectivity.

• Utilizing advanced data science algorithms and workflows
• Developing predictive modeling and complex data analysis skills
• Navigating AI-driven automation and cognitive solutions
• Excelling in data-driven decision making and analytical thinking
• Managing data pipelines and data quality processes
• Embracing change and intellectual curiosity in dynamic environments