AI Engineer 4
Backend Developer
Agentic Ai
AI
Ai Agent
Ai Agent Platform
Ai Orchestration
Application Security
Artificial Intelligence
Automation
Big Data
Bigdata
Cloud
Cloud Data Engineering
Cloud Data Platform
Cloud Infrastructure
Cloud Native
Cloud Platform
Cloud Platforms
Cloud Platforms Cloud Platforms
Cloud Technology
Data Analysis
Data Analytics
Data Architecture
Data Engineer
Data Engineering
Data Integration
Data Lakehouse
Data Pipeline
Data Pipelines
Data Platform
Data Processing
Data Warehouse
Database
Databases
Databricks
DevOps
DevSecOps
Engineering
Engineering Software
Generative AI
Graph Database
Information Technology (IT)
Infrastructure As Code
Integration
Kafka
Kubernetes
Open Source Ai
Pgvector
Platform Engineering
Programming
Programming Language
Programming Languages
Security Automation
Software Security
Spark
SQL
Streaming Data
Vector Databases
Job Description
Join Adobe to design and deliver autonomous, agentic AI capabilities inside the OneAI platform, from prototype through production.
Responsibilities
- Build and productionize reusable agentic components including skills, orchestration workflows, and tool-calling integrations for Adobe OneAI’s intelligence layer (Neo4j + pgvector + Databricks + Claude)
- Own AI model and agent work end to end: move solutions from prototype to production and keep deployed systems healthy
- Improve agent reasoning through prompt design, memory and context management, retrieval quality, and multi-step tool use
- Optimize for latency, reliability, and cost as usage grows across teams
- Collaborate with product managers and data engineers to influence what gets built and to share learnings with the broader team
- Raise the quality bar via evaluation: track solve rates and accuracy, then use results to iterate on agents
Requirements
- 3+ years experience building AI/ML or backend systems, including running LLM-powered services in production
- Strong fundamentals in Python and REST APIs
- Working familiarity with modern AI tooling such as LangChain or LlamaIndex, plus experience with vector databases
- Demonstrated habit of measuring quality and iterating based on results
- Comfort with cloud platforms (AWS, GCP, or Azure) and containers (Docker, Kubernetes)
Technologies
- OneAI, Neo4j, pgvector, Databricks, Claude
- Python, REST APIs
- LangChain, LlamaIndex, vector databases
- AWS, GCP, Azure, Docker, Kubernetes
- Kafka, Flink, Kinesis, Spark
- CI/CD, monitoring, alerting, incident response
Nice to Have
- Experience with event streaming (Kafka, Flink, or Kinesis) and data pipelines (Spark or Databricks)
- Exposure to production operations such as CI/CD, monitoring, alerting, and incident response
- Interest in AI governance, safety, or evaluation
Location: San Jose, CA (onsite)
Compensation: USD 139,000 - 257,550 per yearly
Experience: Minimum 3 years
Similar Jobs
