Senior / Information Retrieval Engineer (AI/ML), Brand Concierge

Adobe Systems
San Jose
Workplace: OnsiteFull timeFunction: Hospitality & Food ServiceExperience: 4+ yearsSkills: ["Vector databases","Semantic search","Embedding models","Python","Machine learning","Information retrieval","Data engineering","Mlops","Airflow","Dbt","Docker","Elasticsearch","Milvus","LangChain","Haystack","Weaviate","Pinecone","Qdrant","OpenAI","Cohere"]

Lead development of Retrieval-Augmented Generation (RAG) pipelines and retrieval systems for enterprise-grade AI. Design scalable, vector-based retrieval architectures, integrate semantic/keyword search, and optimize retrieval quality. Collaborate with prompt and model teams to improve LLM reasoning, accuracy, and system performance in real-world AI applications.

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FursaFursa
Adobe Systems
Adobe Systems
7 months ago

Senior / Information Retrieval Engineer (AI/ML), Brand Concierge

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Source: Company careers pageValidated by: Fursa AI
Last checked: 34 minutes agoStatus: Live

Job Summary

Lead development of Retrieval-Augmented Generation (RAG) pipelines and retrieval systems for enterprise-grade AI. Design scalable, vector-based retrieval architectures, integrate semantic/keyword search, and optimize retrieval quality. Collaborate with prompt and model teams to improve LLM reasoning, accuracy, and system performance in real-world AI applications.
Location: San Jose
Workplace: Onsite
Employment Type: Full time
Job Function: Hospitality & Food Service

Key Responsibilities

  • •Lead the design and deployment of scalable retrieval pipelines and RAG systems for LLMs
  • •Develop ingestion pipelines for structured and unstructured data sources and implement embedding generation and metadata tagging
  • •Tune relevance scoring, reranking, and query understanding to improve precision/recall across domains
  • •Create and maintain knowledge graphs and manage data freshness/versioning for reliable retrieval results
  • •Collaborate with prompt engineers and model developers to align retrieval outputs with downstream model behavior and monitor performance metrics

Key Requirements

  • •4+ years in data engineering, ML infrastructure, or information retrieval
  • •Experience building and deploying RAG pipelines or semantic search systems
  • •Strong ML and Python skills with familiarity with retrieval libraries (e.g., Haystack, LangChain, Elasticsearch, Milvus)
  • •Proficiency with embedding models, vector similarity search, and document indexing
  • •Familiarity with cloud platforms and MLOps tooling (e.g., Airflow, dbt, Docker)
Experience:4+ years
Skills:Vector databasesSemantic searchEmbedding modelsPythonMachine learningInformation retrievalData engineeringMlopsAirflowDbtDockerElasticsearchMilvusLangChainHaystackWeaviatePineconeQdrantOpenAICohere
Languages:English
Tech Stack:PythonHaystackLangChainElasticsearchMilvusFAISSWeaviatePineconeQdrantOpenAICohereHuggingFaceAirflowDbtDockerNeo4jTigerGraphGraf-based knowledge graphs

Company Brief

Adobe Systems
Provides creative, marketing, and document management software and cloud services, including Photoshop, Illustrator, Acrobat, and the Adobe Experience Cloud, serving creative professionals, enterprises, and governments worldwide.
Industry: SaaS
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: San Jose, United States
Founded: 1982
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