Sr. Applied AI Engineer

Our Company Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours! 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 Adobe GTM and Sales 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 Engineering Pillar As a Sr. Applied AI Engineer you will drive efficiency and excellence in sales operations building and scaling robust AI agents and workflows to streamline the sales cycle and processes. You will partner with Sales operations, Campaign specialists, Product managers, and Data/Analytics engineers to tackle problems and bottlenecks using emerging technologies from the AI and agentic landscape. Key Responsibilities Build, tune, and refine AI agents to help the digitization and streamlining of sales operational tasks Implement, strategize, and improve AI prompts and context to achieve optimal output, throughput, and performance Determine, procure, and curate the necessary API/MCP integrations Build orchestrated workflows within and across agents Perform necessary data curation to bridge source data to agents Translate business requirements and ideas into working agents and agentic processes Maintain logic documentation/diagrams, monitor performance, and (re)align agents to changing requirements and evolving technologies Qualifications/Experience BS/Advanced degree in quantitative fields: Computer Science, Data Science, Engineering, Business Analytics, Math/Statistics, or a related field 7+ years of experience in an applied AI engineering or related role with 2+ years in agentic development, and/or with a combination of context/prompt engineering Expert-level Python proficiency with emphasis on modular, object-oriented code, strict typing, and rigorous unit/integration testing for production Experience with building both conversational agents and workflow agentic 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 building collaborative autonomous and complex AI workflows Demonstrated comfort with prompt design 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 (Retrieval-Augmented Generation) pipelines. Proficiency in Databricks and SQL (DDL/DML) driving scalable data architecture and holistically integrating prompt designs, vector databases, and memory strategies to deliver advanced LLM solutions 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 position is $133,100 -- $236,400 annually. Pay within this range varies by work location and may also depend ... (truncated, view full listing at source)