Design, develop, and deploy RAG-based LLM applications for enterprise use cases
Build and manage scalable document ingestion, embedding, and retrieval pipelines
Implement LangChain components including chains, agents, prompt flows, and tools
Integrate and manage vector databases such as FAISS, Pinecone, Chroma, and Weaviate
Develop and maintain ETL/ELT pipelines using Python, Airflow, Kafka, and Spark
Deploy AI/ML solutions on AWS, Azure, or GCP with CI/CD pipelines
Collaborate with data engineers, architects, and product owners to deliver solutions
Required Skills & Experience
5-7+ years of experience in AI/ML, Data Engineering, or Software Development
Strong hands-on experience with RAG architectures and vector databases
Expertise in LangChain or LlamaIndex and LLM API integrations
Solid understanding of data pipelines, ETL/ELT processes, and cloud platforms
Proficiency in Python, REST APIs, SQL/NoSQL databases, Docker, and Kubernetes
Preferred Skills
Experience with LLM fine-tuning techniques such as LoRA
Knowledge of semantic search, embeddings, and MLOps/LLMOps practices
Exposure to enterprise domains such as Telecom, BFSI, Retail, or Healthcare
Job Type: Full-time
Work Location: Remote
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