Job Title

AI Architect (LLMs, RAG, Vertex AI) Position: AI Architect Experience Required: 12–15 Years Location: Noida(Work from Office) Employment Type: Full-Time Shift: US Shift ________________________________________ About the Role We 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: