Solutions Architect, Search Specialist

Elastic

Confirmed live yesterday High trust

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Work type: On-site
Location: —
Posted: 4 days ago
Freshness: Confirmed live yesterday

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How this pay compares to similar roles

Similar $196k

$132k most similar roles pay here $253k

This listing doesn't post a salary. Most similar roles pay $155,690–$235,750.

Based on 240 similar postings.

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About Elastic

Elastic is the company behind Elasticsearch and the Elastic Stack (Elasticsearch, Kibana, Beats, and Logstash). It sells search, observability, and security products built on that search engine, primarily through its Elastic Cloud managed service.

Elastic currently has 240 open roles on FindRole.

Listed pay typically runs $133,100–$210,600 across 91 roles with salary data.

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At a glance

TL;DR · Solutions Architect, Search Specialist

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As a Solutions Architect - Search Specialist, you will join the Solutions Architecture team to design and deploy innovative search solutions using advanced AI technologies. You will be responsible for architecting next-generation systems that utilize RAG, vector databases, and high-dimensional vector representations of data to improve search relevance and user experience. Your daily work involves building proof-of-concept projects, evangelizing the company's vision through presentations and blog posts, and collaborating with engineers and data scientists. You will leverage specific technologies including ELSER, Hugging Face models, LangChain, and various NLP tools to solve complex problems in semantic search and data retrieval. The role focuses on the technical challenge of integrating generative AI and vector search into enterprise-level systems to help organizations unlock insights from both structured and unstructured data.

What does a Solutions Architect earn?

Median $207500 from 131 postings across 29 companies.

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Skills

Semantic Search Vector Search RAG ELSER Hugging Face LangChain NLP Vector Databases Data Analytics

What you'll do

Design and implement next-generation search solutions using AI, semantic search, and vector databases.
Implement high-dimensional vector representations to enable accurate data retrieval from imprecise queries.
Utilize the Elastic Learned Sparse Encoder (ELSER) to improve accuracy in search and data retrieval processes.
Deliver proof-of-concept projects to demonstrate the value of RAG and other emerging technologies.
Act as a thought leader by creating presentations and blog posts about AI-powered search.
Communicate complex technical concepts effectively to developers, architects, and executive buyers.
Stay current on evolving landscapes in NLP, Hugging Face, Langchain, and related ecosystem technologies.

What we're looking for

10+ years of experience in designing and architecting enterprise-level search solutions.
Deep understanding of AI, semantic search technologies, RAG, vector search, and NLP.
Knowledge of ELSER architecture and other models within the Hugging Face ecosystem.
Experience with vector databases and emerging data storage solutions.
Familiarity with ecosystem technologies such as Hugging Face and Langchain.
Excellent communication and presentation skills for technical, architectural, and executive audiences.
Fluency in Spanish (preferred).
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