The Opportunity
The GTM Agentic AI Operations team is leading the shift to an Agentic operating model for Adobe GTM and Sales. This function is the orchestration layer that operationalizes strategy into end to end Agentic AI workflows that compress planning cycles from months to weeks, launch more personalized campaigns across every route to market, and streamline manual tasks so sellers can focus on talking to customers. We are building an always-on Agentic operating layer that connects strategy, data, and frontline execution for the Digital Media business.
The Applied AI EngineeringPillar
As aSr.Applied AIEngineeryou willdriveefficiency and excellencein sales operationsbuilding scalableand robust AI agents and workflows tostreamline the sales cycle.You will partnerwithSales ops,Campaign specialists,Product managers,andData/Analytics engineersto solve problems and remove bottlenecksusing the latest tech in AI and agents.
What you'll do
Build, tune, and refine AI agents to drive the digitization and streamlining of sales operational tasks
Implement, strategize, and improve AI prompts and context to achieve efficient output, efficiency, and performance
Research, curate, and implement API/MCP integrations
Build orchestrated workflows within and across agents
Apply last-mile data transformations to marry source data with agents
Maintain logic documentation/diagrams, monitor performance, and (re)align agents to changing requirements and evolving technologies
What you need to succeed
BS/Advanced degree in quantitative fields: Computer Science, Data Science, AI/ML Engineering, Business Analytics, Math/Statistics, or a related field
7+ years of experience in applied AI engineering or a related role. At least 2 years in agentic development or with a combination of context and timely engineering.
Expert-level Python proficiency with emphasis on modular, object-oriented code, strict typing, and rigorous unit/integration testing for production
Experience with building real-time interactive agents and batch agentic workflow processes in production
Applied experience with multiple LLM stacks/frameworks (e.g., OpenAI, Claude, Gemini, RAG pipelines), and agent orchestration systems (e.g., LangGraph, AutoGen, CrewAI, or LangChain)
Demonstrated comfort with timely composition strategies (chain-of-thought, few-shot) and context window optimization to ensure high-quality LLM outputs
Familiarity with cloud platforms (AWS/Azure), REST APIs, and containerization (Docker, K8s)
Experience implementing and managing Vector Databases (e.g., Pinecone, Milvus, Weaviate) for RAG pipelines
Proficiency in Databricks and SQL (DDL/DML) driving scalable data architecture and holistically integrating timely builds, vector databases, and memory strategies to deliver advanced LLM solutions
Expected Pay Range:
Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this positionis $133,100 -- $236,400 annually. Paywithin this range varies by work locationand may also depend on job-related knowledge, skills,and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.
In California, the pay range for this position is $163,200 - $236,400
At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).
In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.
