AI Architect (LLMs, RAG, Vertex AI)

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/