About the role
The Opportunity Adobe Express enables all users, whether individuals or large organizations, to effortlessly produce impressive content. The AI Foundations team constructs a flexible, scalable AI framework that drives creativity at scale in design, imaging, motion, and personalization. We're looking for a Principal Architect to build and implement the AI framework for Adobe Express, merging strong ML skills with proficiency in distributed systems, data architecture, and large-scale service development. You'll define and invent the end-to-end foundation that brings Agentic AI, Create AI, Imaging AI, Motion AI, and Personalization AI to life — spanning model orchestration, inference systems, data pipelines, caching and storage layers, session analytics, and continuous evaluation frameworks. This role blends applied research and engineering leadership — ideal for someone who can connect modeling innovation with production-grade systems that deliver real-time, customer-facing intelligence at scale. What You’ll Do Architect and evolve the complete AI stack for Adobe Express — covering Agentic AI, Construct AI, Imaging AI, Motion AI, and Personalization AI. Develop and operationalize end-to-end systems — integrating microservices, data pipelines, LLM orchestration layers, in-house and third-party models, databases, caches, session analytics, and evaluation systems into a cohesive architecture. Develop large-scale data and inference infrastructure to support model training, fine-tuning, evaluation, and deployment — employing Spark, Kafka, Flink, and other distributed frameworks. Develop high-performance runtime services for inference and orchestration with strong observability, fault tolerance, and latency guarantees. Apply strong caching and storage tactics to enhance efficiency and cost-effectiveness for various AI workloads. Lead development of experimentation and evaluation systems, encompassing session-level analytics, feedback loops, and quality metrics that drive continuous improvement. Work closely with applied research, product, and platform teams to implement LLMs and other AI models into customer-facing services. Drive architectural strategy for Express AI Foundations — connecting ML models, reasoning engines, and data streams into adaptive, intelligent systems. Mentor senior engineers and scientists, encouraging excellence across architecture, experimentation, and AI system composition. What You’ll Bring 10+ years of experience in large-scale distributed systems AI infrastructure, or ML platform engineering with exposure and experience on in-product AI application engineering Proficiency in Python, Java, C++, or Go, with an emphasis on distributed systems, cloud-native deployment, and performance tuning, agentic AI application building. Hands-on experience with LLM orchestration frameworks, model routing, and multi-model inference. Deep understanding of ML and LLM fundamentals — training, fine-tuning, deployment, and evaluation workflows. Familiarity with Agentic AI patterns — reasoning loops, memory persistence, task decomposition, and multi-agent coordination. Skill to merge engineering precision with practical research understanding, connecting prototyping and production. Strong communication and collaboration skills, with experience influencing cross-functional technical direction. Proven expertise in building and scaling data pipelines, real-time streaming systems, and event-driven architectures (Kafka, Spark, Flink, etc.). Strong background in caching strategies, database development, and performance optimization for large-scale serving systems Preferred
