Principal Architect, Express AI Foundations

Adobe

Confirmed live 2 days ago High trust

Quick summary

Work type
On-site
Location
San Jose, CASan Francisco, CA
Salary
$261,800–$379,100 / yr
Posted
51 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $235k
This role $320k
$159k most similar roles pay here $403k

This role pays more than 91% of similar roles. Most pay $196,750–$272,795 — the shaded band above. At the midpoint, this role pays about $320k versus about $235k for comparable roles.

Based on 239 similar postings.

Employer

About Adobe

Adobe Inc. is a global software company known for creative and multimedia software products including Photoshop, Illustrator, Acrobat, and its cloud-based Creative Cloud and Document Cloud suites. Industry: Creative & Digital Experience Software

Adobe currently has 218 open roles on FindRole.

Listed pay typically runs $187,100–$270,950 across 216 roles with salary data.

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At a glance

TL;DR · Principal Architect, Express AI Foundations

Principal Architect, Express AI Foundations joins the AI Foundations team to build and implement a scalable framework for Adobe Express. This role involves architecting the complete AI stack, including Agentic, Construct, Imaging, Motion, and Personalization AI. You will develop end-to-end systems by integrating microservices, data pipelines, LLM orchestration layers, and high-performance runtime services with robust observability and fault tolerance. The work focuses on creating infrastructure for model training, fine-tuning, and deployment using Spark, Kafka, Flink, and other distributed frameworks. Key responsibilities include designing caching strategies, session analytics, and evaluation systems to improve quality metrics. Candidates should possess expertise in Python, Java, C++, or Go, along with deep knowledge of LLM fundamentals, multi-model inference, and Agentic AI patterns like reasoning loops and task decomposition to deliver real-time, customer-facing intelligence at scale.

What does a Architect earn?

Median $235750 from 31 postings across 17 companies.

See salary data

What you'll do

  • Architect and evolve the comprehensive AI stack for Adobe Express including Agentic, Imaging, Motion, and Personalization AI.
  • Develop end-to-end systems integrating microservices, data pipelines, LLM orchestration layers, and various storage components.
  • Build large-scale data and inference infrastructure using distributed frameworks like Spark, Kafka, and Flink for model training and deployment.
  • Create high-performance runtime services with strict requirements for observability, fault tolerance, and low latency.
  • Implement advanced caching and storage strategies to optimize efficiency and cost-effectiveness for diverse AI workloads.
  • Lead the development of experimentation and evaluation systems featuring session analytics and feedback loops for continuous improvement.
  • Drive architectural strategy by connecting ML models and reasoning engines into adaptive, intelligent systems.
  • Mentor senior engineers and scientists on architecture, experimentation, and complex AI system composition.

What we're looking for

  • 10+ years of experience in large-scale distributed systems AI infrastructure or ML platform engineering.
  • Proficiency in Python, Java, C++, or Go with a focus on cloud-native deployment and performance tuning.
  • Hands-on experience with LLM orchestration frameworks, model routing, and multi-model inference.
  • Deep understanding of ML and LLM fundamentals including training, fine-tuning, and evaluation workflows.
  • Familiarity with Agentic AI patterns such as reasoning loops, memory persistence, and multi-agent coordination.
  • Proven expertise in building data pipelines and real-time streaming systems using Kafka, Spark, or Flink.
  • Strong background in caching strategies, database development, and performance optimization for large-scale serving.
  • Bachelor's degree or equivalent experience in Computer Science, Data Science, Machine Learning, or a related technical field.

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