senior machine learning AI Infrastructure Engineer ic 10+ yrs Bachelor's · Posted Apr 30, 2026
$172,500 – $306,625
USD per year

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
AI Summary
Senior AI Systems Architect translating business requirements into scalable AI solutions. Designs multi-agent workflows, data pipelines, and RAG architectures for enterprise applications. Requires 10+ years software architecture experience, expertise in LLM systems, conversational AI, and cloud platforms.

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Job description

from Adobe careers

The 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
    • This is an excerpt. Read the full job description on Adobe careers →
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