Senior Data Scientist: GenAI, RAG & Enterprise Search

ecsfederal; Virginia (MN); On-site; USD 175,000 - 205,000; Full time

Job summary

Everforth ECS invites a Sr. Data Scientist to join our Arlington, VA team. The role focuses on designing and optimizing intelligent search and retrieval systems, applying GenAI and RAG techniques to enterprise datasets.

You will collaborate with customers and internal teams to shape search architectures, implement embeddings and vector search, and guide best practices in LLM tooling. U.S. citizenship and an active Secret clearance are required.

Qualifications

• Bachelor's degree in CS/Data Science or related field.
• Experience with Elasticsearch, vector search, and RAG.
• Strong knowledge of GenAI and large language models.
• Ability to translate business needs into AI search solutions.
• Experience with cloud data platforms (AWS/Azure/GCP).
• Excellent communication and collaboration skills.
• Willingness to travel to customer sites.
• U.S. Citizenship and active Secret clearance.

Responsibilities

• Design and optimize intelligent search solutions.
• Apply RAG patterns to improve LLM-driven apps.
• Consult with customers to understand objectives and data.
• Build embeddings, indexing, and query workflows.
• Evaluate LLMs and GenAI capabilities for use cases.
• Collaborate with data, AI, and platform teams.
• Deliver strategic recommendations to improve search.
• Lead knowledge-sharing sessions on GenAI and RAG.
• Stay current with Elasticsearch and GenAI trends.

Skills

Elasticsearch

Vector search

RAG

GenAI

LLMs

Search relevance

Embeddings

Query optimization

Cloud platforms

Data science

Education

Bachelor's degree in CS/Data Science or related field

Tools

LLM tooling

ELK stack

Job description

Everforth ECS invites a Sr. Data Scientist to join our Arlington, VA team. The role focuses on designing and optimizing intelligent search and retrieval systems, applying GenAI and RAG techniques to enterprise datasets.

You will collaborate with customers and internal teams to shape search architectures, implement embeddings and vector search, and guide best practices in LLM tooling. U.S. citizenship and an active Secret clearance are required.