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# Senior AI Engineer

- **Company:** Affinity, Inc.
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $160,000.0 - $235,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Continuous Integration, Information Engineering, Data Security, Computer Data Storage, Graph Database, Information Extraction, Information Retrieval, Python (Programming Language), Machine Learning, Named Entity Recognition, Recommender Systems, Software Engineering, Unstructured Data, Management of Software Versions, Data Processing, Delivery Pipeline, Large Language Models, Model Validation, Machine Learning Operations
- **Published:** July 17, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=fb2ec4b5b64be8b8

## About the Role

* 5+ years of experience in software engineering and/or Machine Learning experience in applying machine learning in production.
 * Hands-on experience with LLM applications in production, including prompt engineering and utilizing frameworks for online and offline evaluation
 * Experience with LLM-assisted search, such as query understanding and augmentation, text2sql, and entity extraction
 * Experience with vector or graph databases
 * Experience with document chunking, embedding models, and context window optimization
 * Familiarity with metadata-based retrieval and re-ranking strategies
 * Hands-on experiences with model evaluation metrics (e.g. perplexity, hallucination rate, factual consistency)
 * Familiarity with data security, versioning, and MLOps principles

Nice to Have:

 * Experience with enterprise AI applications with strict compliance, audit, or legal requirements
 * Experience with dataset engineering, including data curation, augmentation, and synthesis, to assist ML model improvements.
 * Experience with multi-modal search
 * Experience with graph-based recommendation systems, such as graph NN.
 * Experience with developing AI applications powered by agent-based systems
 * Experience with packaging, CI/CD and pipeline automation.

## Description

* Build RAG systems: Architect, prototype, and deploy RAG pipelines, combining vector search, hybrid retrieval, reranking and contextual compression techniques.
 * Build LLM-powered agent systems: Contribute to design and orchestration of multi-agent LLM systems using community frameworks and custom orchestration layers.
 * Solve complex problems: Work on a variety of information extraction, information storage and information retrieval problems for both structured and unstructured data.
 * Collaborate cross-functionally: Partner with cross-functional (product, infra, data engineering, and software engineering) teams to build robust, high-scale systems that underlie all of our data processing and ML Operations.


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