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Generative AI -Software Engineer-Senior Associate

PwC
Bengaluru, IND
Full-time
Senior · 4+ years experience
Onsite
Discovered 3 days ago

Full Job Posting

Responsibilities

  • 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.
  • What You Must Have
  • At least a Bachelor's & Master's degree
  • At least 4 years of experience
  • Oral and written proficiency in English required
  • What Sets You Apart
  • 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.

Qualifications

  • Skilled in setting up data pipelines for both model training and real-time inference to support AI workloads efficiently.
  • Experience with additional OOP languages (Java, C++, C#) and familiarity with WebSocket implementations for real-time application functionality.

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