Lead Forward Deployed Engineer

Adobe Adobe · Enterprise · San Jose, CA

Lead Forward Deployed Engineer at Adobe, focusing on integrating AI capabilities into customer applications and workflows. This role involves implementing A2A integration patterns, creating reusable SDKs, analyzing model behavior in production, designing evaluation pipelines, and instrumenting AI features with observability. The engineer will also design and implement AI-backed services using Python and PyTorch, and act as a bridge between customer needs and internal product/engineering teams to ensure AI features are usable, measurable, and scalable.

What you'd actually do

  1. Implement A2A integration patterns (APIs, webhooks, event streams, connectors) so customers can plug our AI capabilities into their existing applications and workflows.
  2. Create reusable SDKs, templates, and reference implementations that reduce friction for customers adopting our AI features.
  3. Act like a data analyst for model behavior: Query logs and metrics (SQL, notebooks, dashboards) to understand how models and prompts are performing in production.
  4. Design and maintain evaluation pipelines for AI features: Define success metrics and guardrails.
  5. Instrument AI features with strong observability and testing: Logging of inputs/outputs with privacy in mind.

Skills

Required

  • Python
  • PyTorch or similar frameworks
  • A2A integration patterns
  • SQL
  • data analysis
  • dashboarding
  • cloud platform (AWS/GCP/Azure)
  • Git
  • CI/CD
  • Docker
  • LLM applications (RAG, agents, prompt pipelines)
  • evaluation of LLM applications
  • logging/observability stacks
  • MLOps/LLMOps concepts
  • shipping production features
  • communication skills

Nice to have

  • Java/Scala
  • customer-facing technical roles
  • Marketing or CRM domain knowledge
  • Published technical writing
  • SaaS software background

What the JD emphasized

  • AI capabilities
  • model behavior
  • evaluation pipelines
  • AI features
  • AI-backed services
  • usable, measurable, and scalable
  • working with ML/AI or LLM-based applications
  • keeping up on the latest developments
  • LLM applications
  • shipping production features

Other signals

  • customer integration
  • model behavior analysis
  • evaluation pipelines
  • AI-backed services
  • production features