AI Architect

Overview

• What you'll build:
• In this role, you'll define the architecture for intelligent, enterprise-grade applications and platforms with AI built into the core design rather than added as an afterthought.
• You'll shape end-to-end solutions across application services, integration layers, data architecture, event-driven systems, security, and AI/ML components. That includes designing patterns for model integration, batch and real-time inference, feature and data pipelines, vector search, LLM orchestration, agent frameworks, evaluation services, and responsible AI controls.
• You ll guide teams on scalability, resilience, interoperability, observability, privacy, and compliance, and ensure architecture choices support both near-term delivery and long-term platform evolution.
• Your work will directly influence how quickly engineering teams can build, govern, and scale AI-enabled capabilities across products and customer scenarios.
• What you bring:
• You bring deep expertise in software architecture for large-scale distributed systems, including microservices, event-driven patterns, APIs, integration layers, and data platforms
• You have a strong understanding of AI and ML system architecture, including training pipelines, inference layers, model lifecycle design, and ML platform capabilities
• You have experience designing enterprise-grade generative AI solutions using LLMs, embeddings, vector databases, RAG patterns, tool use, and orchestration frameworks
• You are skilled at designing scalable and secure application architectures that integrate transactional systems, analytical platforms, and AI-powered services
• You have strong knowledge of cloud-native architecture, including containers, Kubernetes, infrastructure automation, observability, resilience, and performance engineering
• You have experience defining reference architectures, design standards, and reusable technical patterns for AI-enabled product development
• You bring a strong understanding of data architecture, governance, metadata, privacy, and access patterns required to support trustworthy AI solutions
• You evaluate build-versus-buy decisions across models, platforms, data services, and integration tooling, clearly articulating technical and business trade-offs
• You have knowledge of responsible AI, model governance, security controls, compliance requirements, and architectural guardrails for safe enterprise adoption
• You have experience leading architecture reviews, influencing engineering roadmaps, and aligning technical direction across multiple teams or product areas
• You communicate complex architectural decisions clearly to engineers, product leaders, and executive stakeholders