Senior Information Retrieval Engineer AIML Brand Concierge

Adobe; San Jose (CA); On-site; USD 162,000 - 301,200; Full time

Job summary

Adobe is seeking a skilled Information Retrieval Engineer in San Jose, California, to develop and optimize retrieval systems for context-aware large language models. This role involves architecting scalable retrieval pipelines, building ingestion systems, and enhancing knowledge graphs. Ideal candidates will have over 4 years of experience in data engineering and machine learning, strong Python skills, and familiarity with relevant libraries. The job offers a competitive salary range of $162,000 to $301,200 annually, commensurate with experience and location.

Qualifications

• 4+ years in data engineering, ML infrastructure, or information retrieval.
• Experience building and deploying RAG pipelines or semantic search systems.
• Proficiency with embedding models, vector similarity search, and document indexing.
• Familiarity with cloud platforms and MLOps tooling.

Responsibilities

• Architect and deploy scalable retrieval pipelines using vector databases.
• Implement semantic search infrastructure and hybrid retrieval systems.
• Build ingestion pipelines for structured and unstructured data sources.
• Fine-tune relevance scoring and develop techniques to improve precision and recall.

Skills

Data Engineering

Machine Learning Infrastructure

Information Retrieval

Python

Retrieval Libraries

Education

Degree in Computer Science, Information Systems, or a related field

Tools

FAISS

Weaviate

Pinecone

Qdrant

Haystack

LangChain

Elasticsearch

Milvus

Airflow

dbt

Docker

Job description

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

We are seeking a highly skilled Information Retrieval Engineer to lead the development and optimization of retrieval systems that power context-aware large language models (LLMs). This role focuses on building robust Retrieval-Augmented Generation (RAG) pipelines to ensure AI agents and applications have access to the most relevant, timely, and high-quality information.

You’ll work at the intersection of data engineering, machine learning, and knowledge management—enabling better reasoning, accuracy, and performance for enterprise-grade AI systems.

What you'll Do

RAG System Design

• Architect and deploy scalable retrieval pipelines using vector databases (e.g., FAISS, Weaviate, Pinecone, Qdrant)
• Implement semantic search infrastructure and hybrid retrieval systems (semantic + keyword)

Data Processing & Ingestion

• Build ingestion pipelines for both structured and unstructured data sources
• Implement document chunking strategies, embedding generation (e.g., OpenAI, Cohere, HuggingFace), and metadata tagging

Retrieval Optimization

• Fine-tune relevance scoring, reranking algorithms, and query understanding mechanisms
• Develop techniques to improve precision/recall for specific business domains or user tasks

Knowledge Enhancement

• Create and maintain knowledge graphs to support context linking and disambiguation
• Manage data freshness and version control to ensure consistency and reliability of retrieved content

Reasoning Support

• Design and iterate on context window strategies that improve LLM reasoning (e.g., adaptive injection, task-based retrieval)
• Collaborate with prompt engineers and model developers to align retrieval outputs with downstream model behavior

Performance Monitoring

• Track key retrieval metrics such as accuracy, latency, and fallback rate
• Implement caching, prefetching, and deduplication strategies to optimize system responsiveness

What you need to succeed

• 4+ years in data engineering, ML infrastructure, or information retrieval
• Experience building and deploying RAG pipelines or semantic search systems
• Strong Python skills and 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)

Preferred Qualifications

• Knowledge of graph databases (e.g., Neo4j, TigerGraph) or knowledge graph design
• Experience optimizing retrieval for LLMs (e.g., OpenAI, Anthropic, Mistral)
• Background in IR/NLP, Search Engineering, or Cognitive Computing
• Degree in Computer Science, Information Systems, or a related field

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 $162,000 -- $301,200 annually. Pay within this range varies by work location and 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.

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.

State-Specific Notices

California

Fair Chance Ordinances
Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances.

Colorado

Application Window Notice
There is no deadline to apply to this job posting because Adobe accepts applications for this role on an ongoing basis. The posting will remain open based on hiring needs and position availability.

Massachusetts

Massachusetts Legal Notice
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more.

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