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Mid-level GenAI role across metros with broad required skills increases candidate competition.
Specialized GenAI and LLM engineering skills moderately limit cross-industry transferability.
Explicit 6-8 years and many mandatory GenAI, backend, and deployment skills imply strict screening.
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Develop and deploy scalable Python-based backend applications and APIs integrating Large Language Models (LLMs) to enable AI-powered services.
Build and optimize backend services handling LLM API integration, session management, prompt engineering, and Retrieval-Augmented Generation (RAG) pipelines.
Package and deploy GenAI services using containerization (Docker, Kubernetes) or AWS Lambda; collaborate on CI/CD, logging, and monitoring integration.
5+ years of hands-on Python development experience focusing on backend/API design.
Experience integrating Generative AI or NLP models using platforms like OpenAI, Hugging Face Transformers, or Cohere.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Notice Period: Immediate required.
Experienced in building AI-driven backend systems that leverage LLMs and advanced NLP frameworks such as LangChain, LlamaIndex, or Haystack.
Proficient in managing vector embeddings and vector database integrations (FAISS, Pinecone, Weaviate, ChromaDB) for semantic search and document retrieval.
Skilled in deployment and operationalizing AI services with container platforms and cloud functions, collaborating effectively with DevOps teams for CI/CD pipelines.