Enterprise AI Architect

Tiger Analytics looking for an experienced Enterprise AI Architect to lead the design and implementation of enterprise-scale AI platforms and intelligent applications. In this role, you will define the AI technology strategy, architect production-grade AI solutions, and partner with business and engineering leaders to accelerate AI adoption across the organization.

You will work on cutting-edge technologies including Generative AI, Agentic AI, Large Language Models (LLMs), cloud platforms, and modern data architectures while establishing scalable, secure, and responsible AI solutions.

Key Responsibilities

• Define enterprise AI architecture, standards, and technology roadmap.
• Design and deliver production-ready Generative AI and Agentic AI solutions.
• Architect scalable AI platforms leveraging cloud-native technologies and modern data ecosystems.
• Lead AI solution design, technical reviews, and architecture governance.
• Partner with engineering, data, security, and business teams to deliver enterprise AI initiatives.
• Evaluate emerging AI technologies and recommend architecture best practices.
• Ensure AI solutions meet security, governance, compliance, and performance requirements.
• Mentor engineering teams and drive AI adoption across the organization.

Requirements

• 12+ years of experience in enterprise architecture, solution architecture, or cloud architecture.
• Hands-on experience designing and implementing enterprise AI or Generative AI solutions.
• Strong understanding of LLMs, Agentic AI concepts, and modern AI application architectures.
• Experience building cloud-native solutions on AWS, Azure, or Google Cloud.
• Strong software engineering background with Python and API-based architectures.
• Experience with modern data platforms such as Snowflake, Databricks, or similar cloud data technologies.
• Experience in one or more of the following is highly desirable:
• Generative AI, Agentic AI, RAG, AI Agents
• AI orchestration frameworks (such as LangChain or LangGraph)
• Vector databases and knowledge retrieval
• AI governance, security, and Responsible AI
• Cloud AI services (AWS Bedrock, Azure OpenAI, Vertex AI)
• MLOps, CI/CD, Kubernetes, or containerized deployments
• Excellent stakeholder management and executive communication skills.
• Experience leading cross-functional technical teams and enterprise-scale initiatives.