About this role
At PwC Acceleration Center India’s Data and Analytics Engineering practice, this Senior Associate develops data and backend solutions for client Generative AI and agentic AI projects. The role also applies exploratory and descriptive analysis, statistical modeling and data visualization to turn large datasets into insights for business decisions. It is based in Bangalore, India, and lists 40 hours per week.
Responsibilities
- Work with cross-functional teams to translate business needs into backend functionality for GenAI and agentic applications. Design, develop and maintain scalable backend services, including event-driven architectures and integrations with external systems and APIs.
- Manage production AI application data in relational databases (PostgreSQL, MySQL) and NoSQL databases (MongoDB, DynamoDB). Build APIs with Python frameworks including Flask and FastAPI, and coordinate with data scientists, engineers and DevOps teams on AI model deployment.
- Use Kubernetes and DevOps practices, including CI/CD pipelines with Azure DevOps or GitHub Actions, to support deployment and scalability. Deliver quality work amid increasing complexity and ambiguity, anticipate client and team needs, and develop client relationships.
Required qualifications
The posting specifies “at least a Bachelor's & Master's degree,” at least 4 years of experience, and oral and written proficiency in English.
Qualifications that set candidates apart: Proficiency with LLM interaction frameworks such as LangChain, Semantic Kernel and LlamaIndex; experience integrating, scaling and deploying GenAI and agentic applications in production; and building data pipelines for model training and real-time inference. The posting also highlights advanced Python skills—including object-oriented programming, asyncio, multithreading, multiprocessing, design patterns, memory management and performance optimization—plus data structures, algorithms, SOLID principles and clean architecture. Other valued experience includes cloud-native development on Azure or AWS, serverless systems, microservices, Kubernetes, Docker, Java, C++, C# and WebSocket implementations.