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Adobe is seeking a Senior AI Platform Engineer for its Media and Data Science Research Laboratory to help evolve its data platform into a self-healing, streaming-first lakehouse. The ideal candidate will have extensive experience in data platform engineering, distributed systems, and AI integration, focusing on building foundational infrastructure for analytics and autonomous agents.
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Job Summary
The role focuses on building the foundational infrastructure that enables AI, analytics, and autonomous agents at scale rather than building ML models directly.
Engineers are expected to default to an agentic-first approach, automating manual workflows and collapsing pipeline latency from hours to real-time.
The team prioritizes shipping fast as a discipline while maintaining extreme ownership over mission-critical platform reliability and incident response.
Matching Summary
Match Score: 75
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Adobe is seeking a Senior AI Platform Engineer for its Media and Data Science Research Laboratory to help evolve its data platform into a self-healing, streaming-first lakehouse. The ideal candidate will have extensive experience in data platform engineering, distributed systems, and AI integration, focusing on building foundational infrastructure for analytics and autonomous agents.
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Salary
Base: $159,200 - $301,600 annually (US); Base: $208,300 - $301,600 annually (California); Short-term incentives via Annual Incentive Plan; Equity awards may be eligible
Skills & Requirements
Must-have
6+ years distributed systems experience
Apache Spark Databricks Delta Lake expertise
Streaming systems Kafka Flink Kinesis
Python Scala SQL fluency
AWS or Azure cloud platform proficiency
Docker Kubernetes containerization CI/CD
LLM integration prompt engineering tool-use
Nice-to-have
Agentic-first mindset and challenger mentality
Experience with LangChain LangGraph AutoGen
Familiarity with RAG architectures vector databases
Knowledge of semantic layers knowledge graphs
Use of AI-powered developer tools like Cursor
Open-source contributions to data/AI infrastructure
Experience migrating batch to streaming architectures
Key Requirements
6+ years in data platform engineering or distributed systems
BS/MS in Computer Science or equivalent practical experience
Production experience integrating LLMs into engineering workflows