GE Vernova - Senior Software Engineer - Backend Development

Job Description :Key Responsibilities :- Design, develop, and deploy scalable backend services for Generative AI applications.- Build intelligent applications using Large Language Models (LLMs) such as GPT, Claude, Llama, or similar foundation models.- Develop and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise AI use cases.- Integrate vector databases to enable semantic search, knowledge retrieval, and AI-driven recommendations.- Implement AI orchestration workflows using frameworks such as LangChain, LlamaIndex, or Semantic Kernel.- Design and develop RESTful APIs and microservices for AI-powered products.- Optimize AI inference performance, latency, scalability, and operational efficiency.- Deploy and manage AI applications using Docker, Kubernetes, and cloud platforms such as AWS, Azure, or Google Cloud.- Collaborate with product managers, data scientists, and frontend developers to deliver end-to-end AI solutions.- Ensure software quality through unit testing, code reviews, CI/CD pipelines, and DevOps best practices.- Monitor application performance, troubleshoot production issues, and continuously improve system reliability.- Stay updated with the latest advancements in Generative AI, LLMs, and emerging AI frameworks.Required Skills & Qualifications :- 5 - 9 years of experience in backend software development with strong expertise in Python.- Hands-on experience building production-grade applications using Large Language Models (LLMs).- Strong understanding and practical implementation of Retrieval-Augmented Generation (RAG).- Experience working with vector databases such as Pinecone, Weaviate, Milvus, Chroma, or FAISS.- Expertise in AI orchestration frameworks including LangChain, LlamaIndex, or Semantic Kernel.- Strong knowledge of SQL and database optimization.- Experience designing REST APIs and microservices using frameworks such as FastAPI, Flask, or Django.- Hands-on experience with Docker, Kubernetes, and containerized deployments.- Experience working with AWS, Microsoft Azure, or Google Cloud Platform.- Knowledge of distributed systems, scalable backend architecture, and cloud-native application development.- Experience with Git, CI/CD pipelines, and Agile software development methodologies.- Excellent analytical, debugging, communication, and problem-solving skills.Preferred Qualifications :- Experience deploying and monitoring LLM applications in production environments.- Knowledge of prompt engineering, AI agents, autonomous workflows, and function calling.- Familiarity with MLOps practices, model evaluation, observability, and AI governance.- Experience integrating third-party AI APIs and enterprise data sources.- AWS, Azure, or Google Cloud certifications are an added advantage.Education :- Bachelor's or Master's degree in Computer Science, Information Technology, Software Engineering, Artificial Intelligence, or a related discipline. (ref:hirist.tech)