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Job Description
Structured overview of role & requirementsAbout This Role
Design, implement, and optimize production-grade Retrieval-Augmented Generation (RAG) pipelines to enhance large language model accuracy.
Develop clean, modular, and efficient Python backend code using frameworks such as FastAPI or LangChain.
Deploy, secure, and scale GenAI applications on cloud infrastructure (AWS, GCP, or Azure) and manage vector databases to ensure fast semantic search retrieval.
Minimum Requirements
5-6+ years of cloud engineering and AI solution development experience.
Expert-level Python skills, including asynchronous programming and API development.
Practical experience with GenAI frameworks (e.g., LangChain, LlamaIndex, Hugging Face) and vector databases (e.g., Vespa, Pinecone, Milvus, Chroma).
Location requirement: Bangalore (Onsite). Bachelor’s degree in Computer Science, Software Engineering, or related technical field.
Ideal Candidate Profile
Operates effectively in cloud-native environments with containerization and serverless architectures (Docker, Kubernetes).
Experienced in building and optimizing GenAI systems, including prompt engineering and production monitoring.
Familiarity with advanced GenAI practices such as fine-tuning open-source LLMs and MLOps/LLMOps tools (e.g., LangSmith, Weights & Biases).