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 Engineering Pillar As a Sr. Applied AI Engineer you will drive efficiency and excellence in sales operations building scalable and robust AI agents and workflows to streamline the sales cycle. You will partner with Sales ops, Campaign specialists, Product managers, and Data/Analytics engineers to solve problems and remove bottlenecks using 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 About Adobe Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences.
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