Principal Architect, Express AI Foundations

In this Principal Scientist role, you will architect and drive the AI foundations stack for Adobe Express, merging ML innovation with scalable systems. You'll shape end-to-end AI infrastructure, spanning model orchestration, data pipelines, and real-time services that deliver customer-facing intelligence. You'll bridge research and production, influencing cross-functional teams and guiding architectural strategy. This is a high-impact role at scale, enabling creative AI across Agentic, Imaging, Motion, and Personalization domains.

• competitive compensation across US markets
• base pay with short-term incentives
• potential for long-term incentives/equity
• inclusive employment practices
• opportunity to work on cutting-edge AI for millions of creators

• 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 by integrating microservices, data pipelines, LLM orchestration, and models into a cohesive architecture
• Build and scale data and inference infrastructure to support training, fine-tuning, evaluation, and deployment using distributed frameworks
• Create high-performance runtime services for inference and orchestration with strong observability, fault tolerance, and low latency
• Apply caching and storage strategies to optimize AI workloads for cost and efficiency
• Lead development of experimentation and evaluation systems with session analytics and quality metrics
• Collaborate with applied research, product, and platform teams to implement AI models in customer-facing services
• Drive architectural strategy for Express AI Foundations, connecting models, reasoning, and data streams
• Mentor senior engineers and scientists to uphold excellence in architecture, experimentation, and AI systems

• 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, evaluation workflows
• Proven experience building and scaling data pipelines, real-time streaming, event-driven architectures (Kafka, Spark, Flink)
• Strong background in caching, database development, and performance optimization for large-scale serving
• Hands-on experience with LLM orchestration frameworks, model routing, and multi-model inference
• Proficiency in Python, Java, C++, or Go with focus on distributed systems and cloud-native deployment
• Familiarity with Agentic AI patterns: reasoning loops, memory persistence, task decomposition, multi-agent coordination
• Ability to merge engineering precision with practical research to connect prototyping and production
• Strong communication and collaboration skills with cross-functional influence

• strong communication
• collaboration across teams
• mentorship and leadership
• Spark
• Kafka
• Flink