Generative AI Architect

Job Title: Generative AI Architect

Location:

Gurgaon (Hybrid) Experience:

8+ Years (3 Years in Generative AI) Employment Type:

Full-Time Role Overview We are seeking a highly experienced

Generative AI Architect

to lead the design and implementation of enterprise-grade AI solutions powered by Large Language Models (LLMs), Transformer architectures, and advanced retrieval systems. The ideal candidate will be responsible for defining AI architecture strategy, building scalable GenAI platforms, and driving innovation in areas such as RAG systems, semantic search, intelligent automation, and AI-driven personalization. This is a high-impact leadership role requiring deep technical expertise, strong architectural vision, and stakeholder collaboration. Key Responsibilities AI & LLM Architecture Strategy Define and lead the enterprise architecture for Generative AI solutions. Design scalable, secure, and cost-efficient LLM-based systems. Evaluate and select foundation models (Open-source / Commercial APIs). Define governance, safety, and compliance standards for AI usage. Large Language Model & RAG Systems Architect and implement Retrieval-Augmented Generation (RAG) pipelines. Design vector search architecture using embedding models and vector databases. Lead fine-tuning strategies (LoRA, PEFT, full fine-tuning). Optimize inference performance using quantization and model distillation. Drive prompt engineering standards and reusable prompt frameworks. Intelligent Search & Recommendation Systems Architect semantic search, dense retrieval, and ranking pipelines. Improve personalization and contextual recommendation engines. Define evaluation metrics such as NDCG, Recall, CTR, Perplexity, and Latency. ⚙ AI Platform & MLOps Design end-to-end ML lifecycle pipelines (training, validation, deployment). Implement CI/CD for ML workflows. Establish model monitoring, observability, and retraining frameworks. Ensure scalability using Docker, Kubernetes, and distributed systems. ☁ Cloud & Infrastructure Architect AI solutions on AWS, GCP, or Azure. Design GPU infrastructure strategy and cost optimization models. Work with distributed training and inference architectures. Data Strategy & Governance Define data architecture for training and retrieval pipelines. Ensure data quality, compliance, and privacy standards. Collaborate with Data Engineering to build scalable feature stores. Leadership & Stakeholder Engagement Lead cross-functional AI initiatives across Engineering, Product, and Business. Present architectural designs to executive stakeholders. Mentor AI/ML engineers and drive best practices. Required Technical Qualifications 8+ years of experience in Software Engineering / ML / AI. 3+ years of hands-on experience in Generative AI and LLM systems. Strong expertise in Python and deep learning frameworks (PyTorch / TensorFlow). Deep experience with Transformer architectures (BERT, GPT-family, encoder/decoder models). Hands-on experience with: Hugging Face LangChain LlamaIndex Vector databases (FAISS, Pinecone, Milvus, Weaviate) Strong knowledge of RAG system design and dense retrieval architectures. Experience designing production-grade search or recommendation systems. Expertise in cloud platforms (AWS/GCP/Azure). Experience with MLOps tools (MLFlow, Kubeflow, Docker, Kubernetes). Strong understanding of system design, distributed computing, and scalable architecture. Preferred Qualifications Experience with model quantization and optimization (ONNX, TensorRT). Knowledge of Responsible AI, fairness, bias mitigation, and governance frameworks. Experience building multi-modal AI systems (text + vision). Exposure to enterprise AI adoption strategy. Key Skills Generative AI | LLM Architecture | RAG | Transformer Models | Vector Search | Prompt Engineering | LoRA | MLOps | Cloud AI | AI Governance | Semantic Search | AI System Design