Software Development Engineer, Influencer Management

Adobe Adobe · Enterprise · San Jose, CA

Software Development Engineer to build and launch a new product within Adobe, focusing on a platform for enterprise brands and creators to collaborate on influencer marketing. A core part of the platform will involve Agentic AI systems to streamline workflows, integrating LLM-powered services and processes. The role involves full-stack development, backend services, AI-powered features, and scalable data pipelines.

What you'd actually do

  1. Compose, build, and scale full-stack product capabilities that power an enterprise platform for managing influencer projects end-to-end.
  2. Develop backend services and support workflows such as creator discovery, campaign planning, collaboration, contract management, performance tracking, and analytics.
  3. Implement AI-powered features that streamline influencer marketing operations, including creator matching, campaign optimization, content insights, and workflow automation.
  4. Integrate LLMs and agentic AI systems to support intelligent workflows across the platform, including task orchestration, recommendation systems, and automated campaign assistance.
  5. Build scalable data pipelines and integrations with external platforms and APIs such as social networks, analytics tools, and marketing systems.

Skills

Required

  • 5+ years of professional experience developing full-stack web applications.
  • Strong proficiency with JavaScript/TypeScript, React, and Node.js (or comparable frameworks).
  • Experience designing and building scalable APIs, backend services, and modern web architectures.
  • Experience integrating AI services, LLM APIs, or machine learning capabilities into production applications.
  • Familiarity with data modeling, integrations, and working with external platforms or third-party services.
  • Strong problem-solving and debugging skills, with the ability to work across frontend, backend, and system integrations.
  • Excellent communication and collaboration skills; thrives in fast-paced, multi-functional environments.
  • Familiarity with cloud platforms such as AWS, Azure, or GCP and modern deployment practices.

What the JD emphasized

  • Agentic AI systems
  • LLM-powered services
  • AI-native product experiences
  • integrating AI services, LLM APIs, or machine learning capabilities into production applications

Other signals

  • integrating LLM-powered services
  • agentic AI systems
  • AI-native product experiences
  • experiment with emerging AI capabilities