Principal Architect, Express AI Foundations

About the role

The AI Foundations team at Adobe Express is seeking a Principal Architect to lead the development of the AI framework that powers Adobe Express. This role involves architecting and evolving the complete AI stack, developing large-scale data and inference infrastructure, and driving architectural strategy for Express AI Foundations.

Responsibilities

• 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.

Requirements

• 10+ years of experience in large-scale distributed systems AI infrastructure, or ML platform engineering.
• Deep understanding of ML and LLM fundamentals — training, fine-tuning, deployment, and evaluation workflows.
• 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.
• Hands-on experience with LLM orchestration frameworks, model routing, and multi-model inference.
• Proficiency in Python, Java, C++, or Go, with an emphasis on distributed systems, cloud-native deployment, and performance tuning.
• Familiarity with Agentic AI patterns — reasoning loops, memory persistence, task decomposition, and multi-agent coordination.
• Ability to merge engineering precision with practical research understanding, connecting prototyping and production.
• Strong communication and collaboration skills, with experience influencing cross-functional technical direction.

Preferred Qualifications

• Bachelor's or equivalent experience in Computer Science, Data Science, Machine Learning, or a related technical field.
• Experience architecting AI assistants, build agents, or multimodal creative systems.
• Exposure to Generative AI (LLMs, diffusion, or multimodal architectures).
• Experience with MLOps pipelines, feature stores, and model registries.
• Track record of open-source contributions, publications, or conference presentations.