Generative Ai Architect

Job description

We are seeking a highly experienced Generative AI Architect to lead the design, architecture, and solutioning of enterprise-grade GenAI platforms and applications. The ideal candidate will have deep expertise in AI/ML, LLMs, prompt engineering, vector databases, and cloud-native architectures, with proven experience delivering scalable AI solutions across complex environments. Key Responsibilities 1. Architecture & Solution Design • Architect end-to-end GenAI solutions, including data pipelines, model selection, LLM fine-tuning, RAG frameworks, orchestration, and deployment. • Design scalable, secure, and cost-optimized GenAI reference architectures on Azure/AWS/GCP. • Define solution blueprints integrating LLMs, vector DBs, data lakes, enterprise APIs, and microservices. • Evaluate and select appropriate foundation models (OpenAI, Anthropic, Meta, Google, etc.) based on business needs. 2. Technical Leadership • Provide architectural governance and best practices across multiple GenAI initiatives. • Guide engineering teams on model integration, optimization, evaluation, and MLOps/LLMOps. • Drive PoCs, feasibility studies, and technology assessments. 3. RAG & LLM Engineering • Architect Retrieval-Augmented Generation (RAG) systems using vector stores (Pinecone, FAISS, Weaviate, etc.). • Optimize prompt engineering, model evaluation, grounding, hallucination reduction, and response accuracy. • Implement model fine-tuning, domain adaptation, and performance monitoring. 4. Data Engineering & Security • Design data ingestion, governance, and preprocessing pipelines for structured, unstructured, and multimodal data. • Ensure compliance with enterprise security, privacy, model safety, and responsible AI frameworks. • Collaborate with data engineering teams to integrate with enterprise data platforms. 5. Stakeholder Engagement & Delivery • Work with business leaders to identify GenAI use cases, define roadmaps, and build ROI-driven solutions. • Prepare and deliver solution proposals, architecture documents, technical presentations, and cost estimates. • Collaborate with product, engineering, data science, and cloud teams for end-to-end delivery. Required Skills & Experience Core Technical Skills • 8-14 years of experience in AI/ML, cloud architecture, or enterprise software engineering. • 35+ years hands-on experience in LLMs / GenAI platforms. • Strong expertise in: • LLMs (OpenAI, GPT, Claude, Gemini, Llama, etc.) • GenAI frameworks: LangChain, LlamaIndex, HuggingFace • RAG architecture, vector databases, embeddings • Cloud platforms: AWS (Bedrock/SageMaker), Azure (OpenAI/ML), GCP (Vertex AI) • Python, PyTorch, TensorFlow, REST, GraphQL • CI/CD, MLOps/LLMOps, containerization (Docker, Kubernetes) Architecture & Solutioning Skills • Enterprise architecture (TOGAF is a plus). • Building scalable, distributed microservices. • Design of secure AI systems with RBAC, encryption, data masking, model governance. Soft Skills • Strong communication and executive-level presentation skills. • Ability to translate complex technical concepts into business-friendly language. • Proven leadership in multi-functional teams. Preferred Qualifications • Master’s degree in Computer Science, Engineering, AI/ML, or related field. • Certification in cloud architecture (AWS/Azure/GCP). • Experience in multimodal AI, agents, or advanced model fine-tuning. • Prior experience as an AI architect or lead ML engineer. Why Join Us • Lead strategic AI transformation initiatives for global clients. • Work with cutting-edge GenAI tools, models, and frameworks. • Opportunity to influence AI strategy and enterprise roadmaps.