Applied AI Engineer

Adobe

Confirmed live today High trust

Quick summary

Work type: On-site
Location: San Jose, CA
Employment: Full-time
Posted: 39 days ago
Freshness: Confirmed live today
Closes: Nov 30, 2026
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $196k

$130k $254k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $150,000–$241,750.

Based on 240 similar postings.

Employer

About Adobe

Adobe Inc. is a global software company known for creative and multimedia software products including Photoshop, Illustrator, Acrobat, and its cloud-based Creative Cloud and Document Cloud suites. Industry: Creative & Digital Experience Software

Adobe currently has 282 open roles on FindRole.

Listed pay typically runs $148,100–$282,100 across 76 roles with salary data.

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At a glance

TL;DR · Applied AI Engineer

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The Applied AI Engineer will join the team to develop, build, and maintain intelligent agents that drive automation and business impact across the enterprise. This role involves the full lifecycle of agent development, including design, versioning, orchestration, and continuous learning. You will build scalable Agentic AI platforms, create reusable templates, and productionize AI models from prototypes to production-ready systems. Key responsibilities include developing autonomous agents for code generation and tool calling while optimizing model performance and latency. Required skills include Python, REST, and experience with LLM APIs, LangChain, LlamaIndex, and vector databases. You must also possess expertise in event streaming using Kafka or Flink, data pipelines with Spark or Databricks, and production operations involving Kubernetes, CI/CD, Docker, and cloud platforms like AWS, GCP, or Azure.

Skills

Python LLM APIs LangChain LlamaIndex Vector Databases REST APIs Kafka Flink Kinesis Spark Databricks Kubernetes Docker CI/CD AWS GCP Azure Prompt Engineering

What you'll do

Build and maintain scalable Agentic AI platforms to enhance engineering efficiency and AI adoption.
Create reusable agent templates and modular components to accelerate deployment across business units.
Productionize AI models by transitioning them from initial prototypes to production-ready systems.
Develop autonomous agents and specific skills for tasks like code generation and tool calling.
Optimize model performance to reduce latency and improve overall system reliability.
Implement prompt engineering strategies, memory handling, and resource management for AI agents.
Integrate tool-calling capabilities and manage data pipelines for agentic workflows.

What we're looking for

3–5+ years of experience in AI/ML engineering and backend development.
Prior exposure to LLM APIs or AI-powered services in production.
Experience with AI tools like LangChain, LlamaIndex, or vector databases.
Ability to measure and improve model solve rates and accuracy.
Strong engineering fundamentals in Python and REST.
Experience with event streaming (Kafka, Flink, Kinesis) and data pipelines (Spark, Databricks).
Familiarity with production operations including Kubernetes, CI/CD, monitoring, alerting, and incident response.
Familiarity with cloud platforms (AWS/GCP/Azure), REST APIs, Python, and containerization (Docker, K8s).

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