AI Engineer - AWS

Key Responsibilities: - Design and develop RAG-based pipelines using vector databases and LangChain for enterprise-scale applications. - Build, fine-tune, and optimize LLM-powered solutions, including prompt engineering and model evaluation for domain-specific tasks. - Integrate and deploy AI solutions on AWS Bedrock and Azure AI platforms. - Develop and maintain knowledge graphs to support intelligent querying and reasoning in GenAI solutions. - Implement agentic frameworks to enable autonomous AI workflows and decision-making. - Collaborate with cross-functional teams to align AI initiatives with business goals. - Ensure scalability, performance, security, and compliance of AI applications in enterprise environments. - Stay updated on the latest GenAI and LLM advancements to continuously improve solution capabilities. Required Skills & Experience: - 5–7 years of hands-on experience in AI/ML, with a focus on Generative AI. - Strong experience with LangChain or similar orchestration frameworks. - Proven experience with RAG pipelines and vector databases (Pinecone, FAISS, Weaviate, Milvus, ChromaDB). - Experience integrating and deploying solutions on AWS Bedrock and Azure AI services. - Working knowledge of Knowledge Graphs (Neo4j, RDF, Graph DBs) and semantic search. - Hands-on experience in LLM fine-tuning (OpenAI, Anthropic, HuggingFace models) for domain-specific use cases. - Proficiency in Python and modern AI development frameworks. - Experience building enterprise-grade GenAI or agentic applications. - Familiarity with CI/CD for ML/AI pipelines is a plus. Skills: Aws, Python Experience: 5.00-8.00 Years