Job Summary
We are seeking a Senior AI/ML Engineer with strong expertise in Retrieval-Augmented Generation (RAG), vector databases, multimodal AI, and prompt engineering. The role focuses on building enterprise-scale intelligent AI applications that leverage both structured and unstructured data, while optimizing solution quality, accuracy, performance, and latency.
Key Responsibilities
• Design and implement enterprise-scale Retrieval-Augmented Generation (RAG) pipelines.
• Build and optimize semantic search solutions using vector databases.
• Develop multimodal AI applications capable of processing text, images, documents, and other data formats.
• Create and optimize prompts to improve LLM performance and accuracy.
• Develop data ingestion, chunking, embedding, retrieval, and ranking strategies.
• Evaluate and improve AI solution quality, accuracy, and latency.
• Collaborate with cross-functional teams to integrate AI capabilities into enterprise applications.
Required Qualifications
• Strong proficiency in Python.
• Hands-on experience building RAG solutions.
• Experience with vector databases such as Pinecone, Weaviate, Milvus, Chroma, or OpenSearch.
• Strong understanding of embeddings, retrieval strategies, and semantic search.
• Expertise in prompt engineering.
• Experience building multimodal AI solutions.
• Strong knowledge of LLMs and foundation models.
Preferred Qualifications
• Experience with Amazon Bedrock and AWS AI services.
• Familiarity with LangChain for RAG implementations.
• Knowledge of AI evaluation frameworks and AI observability tools.
• Experience deploying AI/ML applications in production environments.
• Knowledge of Agentic AI concepts.
• Experience with LangGraph or multi-agent architectures.
• Exposure to MLOps and model deployment pipelines.
