Sr. AI Systems Architect (AI/ML), Brand Concierge
Adobe · San Jose, CA · Engineering and Product
About this role
Adobe is hiring a senior-level AI Infrastructure Engineer in the machine learning function based in San Jose, CA. The posting calls out experience with Express, AWS, GCP, Azure and roughly 10+ years of relevant work. Listed education preference: a bachelor's degree or equivalent. Compensation is listed at $172,500–$306,625 per year.
- Role
- AI Infrastructure Engineer
- Function
- machine learning
- Level
- senior
- Track
- Individual contributor
- Employment
- Full-time
- Location
- San Jose, CA
- Experience
- 10+ years
- Education
- Bachelor's degree
- Department
- Engineering and Product
- Posted
- Apr 30, 2026
More roles at Adobe
Job description
from Adobe careersThe Opportunity
We are seeking a strategic and technically skilled Senior AI Systems Architect to bridge the gap between complex business needs and advanced AI system design. You will play a pivotal role in translating use cases into scalable, intelligent solutions—leading the design of agent-based workflows, data pipelines, and orchestration systems tailored to enterprise applications.
What you'll Do
- Translate business goals into AI architecture: Collaborate with customers and team members to understand needs, assess feasibility, and define system scope.
- Design AI agents and orchestration workflows: Create end-to-end blueprints for multi-agent systems to support real-time, multi-turn interactions across business functions.
- Define data and RAG architecture: Specify data requirements and retrieval-augmented generation (RAG) configurations to ensure context-aware, grounded responses.
- Author technical specifications: Produce clear, detailed documentation for LLM-based solutions, including APIs, tools, prompt logic, and agent capabilities.
- Collaborate across teams: Work with ML engineers, product teams, and customer collaborators to align implementation with technical and business strategy.
- Ensure scalability and reliability: Design solutions that are modular, maintainable, and resilient across enterprise environments.
- Lead POCs and solution validation: Guide prototype development, performance tuning, and feedback loops for continuous improvement.
What you need to succeed
- 10+ years in software architecture, enterprise AI engineering