Senior Software Development Engineer 5

Adobe Adobe · Enterprise · San Jose, CA

Senior Software Engineer 5 at Adobe focused on architecting and developing scalable backend systems for AI-native applications, specifically in Retrieval-Augmented Generation (RAG) and Multi-Agent Collaboration Platform (MCP) environments. The role involves leading the design and implementation of backend services, integrating AI/ML models and agents, and ensuring data platform integration, with a strong emphasis on technical leadership and mentorship.

What you'd actually do

  1. Lead the design and implementation of robust, scalable backend services using Java and Python.
  2. Own end-to-end system architecture for AI-native applications, including RAG/MCP multi-agent environments.
  3. Build and optimize backend components that support AI/ML workflows, including data ingestion, orchestration, and inference pipelines.
  4. Collaborate with data scientists and AI engineers to integrate advanced models and agents into production systems.
  5. Design and maintain data pipelines and APIs employing AEP’s XDM schemas and real-time data services.

Skills

Required

  • 10+ years of experience in backend software engineering
  • architecting and delivering large-scale, distributed systems
  • Advanced proficiency in Java and Python
  • cloud-native development
  • containerization (Kubernetes, Docker)
  • building AI-native applications
  • RAG/MCP multi-agent environments
  • data modeling
  • API design
  • integration with data platforms
  • distributed data frameworks
  • real-time data processing
  • leading technical teams
  • mentoring engineers
  • driving cross-team initiatives

Nice to have

  • XDM schemas
  • data lake architectures
  • real-time customer intelligence systems
  • AI/ML model deployment
  • orchestration
  • monitoring in production environments
  • Contributions to technical publications, open-source projects, or conference presentations

What the JD emphasized

  • AI-native applications
  • RAG/MCP multi-agent environments
  • backend systems
  • AI/ML workflows
  • data pipelines

Other signals

  • AI-native applications
  • RAG/MCP multi-agent environments
  • backend services for AI/ML workflows