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AI Architect (LLMs, RAG, Vertex AI)

AI Architect (LLMs, RAG, Vertex AI)

BIG Language SolutionsDelhi, India
14 days ago
Job description

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 : https : / / biglanguage.com

    Linkedin : https : / / www.linkedin.com / company / big-language-solutions / mycompany /

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