Principal Data & AI Engineer

Adobe Adobe · Enterprise · San Jose, CA +6

This role focuses on building agent-based automation and autonomous AI systems, specifically LLM agents and multi-agent orchestration, for data integration and workflow automation within an enterprise customer solutions context. It involves significant data engineering work to prepare and integrate customer data sources with Adobe solutions, leveraging AWS AI/ML and agentic services.

What you'd actually do

  1. Collaborate with Data architects, Enterprise architects, Solution consultants and Product engineering teams to capture customer data integration requirements, conceptualize solutions & build required technology stack
  2. Collaborate with enterprise customer's engineering team to identify data sources, profile and quantify quality of data sources, develop tools to prepare data and build data pipelines for integrating customer data sources and third party data sources with Adobe solutions
  3. Develop new features and improve existing data integrations with customer data ecosystem
  4. Encourage team to think out-of-the-box and overcome engineering obstacles while incorporating new innovative design principles.
  5. Work with Project Managers to scope, bill, and forecast time for customer solutions, demonstrating agent-based AI and automation strategies.

Skills

Required

  • Experience as an enterprise Data Engineer from a consulting background
  • AWS Certified Data Engineer – Associate or AWS Certified Cloud Practitioner
  • 10+ years experience in building/operating/maintaining fault tolerant and scalable data processing integrations using AWS
  • 10+ years experience in Python programming language preferably using PySpark
  • Software development experience working with Apache Airflow, DynamoDB, MySQL
  • 2+ years working with AWS AI/ML and agentic services such as SageMaker, Bedrock, Vector databases (OpenSearch, Pinecone)
  • Demonstrated experience (or significant exposure) designing, integrating, and scaling agentic AI systems—such as LLM agents, multi-agent frameworks (LangChain, LangGraph, LangSmith, MLFlow), autonomous orchestration, or decision-making pipelines. Capable of evolving data engineering solutions into intelligent, agent-based offerings.
  • Strong capacity to manage numerous projects are a must
  • Ability to identify and resolve problems associated with production grade large scale data processing workflows
  • Excellent communication skills

Nice to have

  • Experience using Docker or Kubernetes is a plus
  • BS/MS degree in Computer Science or equivalent industry experience
  • Experience creating and maintaining unit tests and continuous integration.
  • Experience & knowledge with Web Analytics or Digital Marketing
  • Experience & knowledge with Customer Data Platform (CDP) or Data Management Platform (DMP)
  • Experience & knowledge with Adobe Experience Cloud solutions

What the JD emphasized

  • building scalable API based integrations
  • architecting autonomous AI systems
  • LLM agents
  • intelligent automation
  • agent-based automation
  • LLM agents
  • multi-agent orchestration
  • dynamic data integration
  • workflow automation
  • agentic AI systems
  • LLM agents
  • multi-agent frameworks
  • autonomous orchestration
  • decision-making pipelines
  • evolving data engineering solutions into intelligent, agent-based offerings
  • manage numerous projects are a must

Other signals

  • LLM agents
  • multi-agent orchestration
  • autonomous AI systems
  • data integration