Ai Architect

AI Architect (LLMs, RAG, Vertex AI)Position : AI ArchitectExperience Required : 12–15 YearsLocation : Noida(Work from Office)Employment Type : Full-TimeShift : US Shift________________________________________About the RoleWe are seeking a highly skilled AI Architect with deep expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Vertex AI platform to design, build, and deploy enterprise-grade AI solutions. The ideal candidate will have hands-on experience in building and fine-tuning open-source foundation models, integrating AI / ML pipelines within cloud ecosystems, and defining scalable AI architectures aligned to business needs.This role requires a balance of technical innovation, architectural leadership, and practical implementation to accelerate enterprise AI adoption.________________________________________Key Responsibilities- Architect and lead the development of LLM-based solutions using open-source and proprietary models (Llama, Falcon, Mistral, GPT-J, etc.).- Design and implement RAG frameworks for enterprise use cases combining vector databases, embeddings, and document stores.- Leverage Vertex AI for model training, fine-tuning, monitoring, and lifecycle management.- Build scalable AI pipelines and inference architectures using Python, TensorFlow, PyTorch, and LangChain frameworks.- Develop prompt engineering and optimization strategies for model reliability and contextual accuracy.- Collaborate with data engineers to design data pipelines for model training and evaluation.- Integrate AI models with enterprise systems via APIs and microservices architectures.- Define AI governance, ethical AI practices, and model performance KPIs.- Mentor cross-functional teams in AI / ML model development, deployment, and MLOps practices.- Evaluate new technologies, foundation models, and research to enhance AI platform capabilities.________________________________________Required Skills & Experience- 12–15 years of overall experience in software / AI engineering, with at least 5+ years in AI architecture and applied ML.- Proven expertise in LLM development, fine-tuning, and RAG implementation using open-source frameworks.- Strong experience with Google Vertex AI (Model Registry, Pipelines, Workbench, and Model Deployment).- Proficiency in Python, TensorFlow, PyTorch, LangChain, Hugging Face Transformers.- Hands-on experience with Vector Databases (Pinecone, Weaviate, Milvus, pgvector, FAISS).- Familiarity with retrieval, embeddings (OpenAI, Vertex, Cohere, Hugging Face), and knowledge graphs.- Deep understanding of MLOps pipelines, CI / CD for AI, and cloud-based ML lifecycle management.- Experience integrating models with APIs, RESTful services, and microservices architectures.- Strong grounding in AI model governance, bias detection, and ethical AI frameworks.________________________________________Preferred Qualifications- Experience with multi-cloud AI architectures (AWS Sagemaker, Azure ML, GCP Vertex AI).- Familiarity with GenAI orchestration frameworks (LangChain, LlamaIndex, DSPy).- Contributions to open-source AI / ML repositories or model development communities.- Certifications in AI / ML Engineering, Cloud AI Architecture (GCP Professional ML Engineer).- Exposure to RAG-based enterprise chatbots or domain-specific LLM deployments.Think global. Think BIG.Visit us : https : / / biglanguage.ComLinkedin : https : / / www.Linkedin.Com / company / big-language-solutions / mycompany /