Data AI Solutions Architect

6 days ago

bangalore, India beBeeArtificialintelligence Full time

Job Title: AI Solutions ArchitectAbout the Role:We are seeking an AI Solutions Architect to join our team. As an AI Solutions Architect, you will be responsible for designing and implementing end-to-end generative AI solutions.Key Responsibilities:Design and implement AI solutions including RAG chatbots, LLM-powered BI systems, and coding agents.Develop and deploy AI agents using frameworks like LangGraph and similar orchestration tools.Build robust data processing pipelines using LlamaIndex and related libraries for document ingestion and retrieval.Implement and optimize vector databases for semantic search and retrieval systems.Integrate multiple LLM providers (OpenAI, Gemini, Anthropic) and evaluate model performance.Set up comprehensive observability and monitoring using tools like LangSmith.Collaborate with engineering teams to productionize ML models and AI applications.Required Skills and Qualifications:Generative AI:Strong programming skills in Python.Hands-on experience with Temporal, LangGraph or similar AI agent frameworks.Proficiency with LlamaIndex, LangChain, or equivalent data processing libraries.Experience with vector databases (Pinecone, Weaviate, Chroma, etc.).Working knowledge of multiple LLMs and their APIs (OpenAI GPT, Gemini, Claude).Experience with LLM observability tools (LangSmith, Weights & Biases, etc.).Proven track record in building LLM BI solutions (natural language to SQL).Experience developing RAG (Retrieval-Augmented Generation) chatbots.Experience with coding agents and code generation systems.Good to Have:Fine-tuning experience with LLMs, rerankers, or embedding models.Self-hosting and deployment of open-source LLMs.Experience with BERT, transformer architectures, or computer vision models (YOLO).MLOps experience with MLflow, Weights & Biases, or TensorBoard.Cloud platform certifications (AWS, GCP, Azure).Strong foundation in clustering, regression, classification, and forecasting.Proficiency with scikit-learn, PyTorch, TensorFlow.Experience with statistical analysis and experimental design.Knowledge of feature engineering and data preprocessing techniques.Additional Requirements:Experience with containerization (Docker, Kubernetes).Knowledge of API development and microservices architecture.Understanding of prompt engineering and prompt optimization techniques.Experience with evaluation frameworks for LLM applications.Familiarity with data privacy and security best practices for AI applications.Benefits:This is a unique opportunity to work on cutting-edge AI projects and develop your skills in a collaborative environment.How to Apply:Please submit your application through the website.

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