Software Engineer, AI Integrations & Backend

Adobe; San Jose (CA); On-site; USD 177,900 - 257,550; Full time

Job summary

Adobe Unified Platform is hiring a Software Engineer to build the integration layer that connects model providers and partner services. You will write API clients, routing logic, and abstraction layers while owning test plans.

This hands-on mid-level role focuses on reliable integrations, tooling, and secure development practices. You will work across modules to debug issues, monitor model quality and latency, and contribute to dashboards that track production performance.

Qualifications

• 5+ years of software engineering experience.
• Proficiency in Python, Go, or Java.
• Hands-on experience building API integrations and backend services.
• Experience with AI/ML systems or agentic frameworks.
• Ability to debug across modules and layers.
• Solid testing, observability, and secure programming foundations.
• Ownership of feature-level test plans.

Responsibilities

• Build and maintain integrations to model providers and partner services.
• Write API clients, routing, fallback logic, and abstraction layers.
• Own the test plan for the features you deliver.
• Debug issues across multiple modules and layers.
• Build tooling to measure model quality, latency, cost, and reliability.
• Create dashboards showing model and partner performance in production.
• Apply DevOps and secure programming practices.
• Use AI-assisted development tools and review outputs.
• Harden integrations against real-world failures.
• Share knowledge with peers and mentor junior engineers.

Skills

Python

Go

Java

APIs

Debugging

DevOps

LLM APIs

Job description

Adobe Unified Platform is hiring a Software Engineer to build the integration layer that connects model providers and partner services. You will write API clients, routing logic, and abstraction layers while owning test plans.

This hands-on mid-level role focuses on reliable integrations, tooling, and secure development practices. You will work across modules to debug issues, monitor model quality and latency, and contribute to dashboards that track production performance.