This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data / Search Specialist based in United States.
This role offers the opportunity to build the data foundations that power enterprise AI applications and make organizational knowledge more accessible.
You will design retrieval systems, knowledge bases, and data pipelines that help generative AI solutions deliver accurate and trusted results.
The position combines data engineering, search technologies, AI enablement, and hands-on technical implementation.
You will collaborate with architects, engineers, and customer teams to create secure and scalable information retrieval solutions.
The ideal candidate brings expertise in RAG systems, embeddings, vector search, and enterprise data governance.
This is a high-impact opportunity to help organizations unlock the value of their data while ensuring security, accuracy, and responsible AI adoption.
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data / Search Specialist based in United States.
This role offers the opportunity to build the data foundations that power enterprise AI applications and make organizational knowledge more accessible.
You will design retrieval systems, knowledge bases, and data pipelines that help generative AI solutions deliver accurate and trusted results.
The position combines data engineering, search technologies, AI enablement, and hands-on technical implementation.
You will collaborate with architects, engineers, and customer teams to create secure and scalable information retrieval solutions.
The ideal candidate brings expertise in RAG systems, embeddings, vector search, and enterprise data governance.
This is a high-impact opportunity to help organizations unlock the value of their data while ensuring security, accuracy, and responsible AI adoption.
Accountabilities
- Build and configure data connectors and ingestion pipelines to bring approved enterprise content into AI-ready knowledge bases, including sources such as SharePoint Online, Exchange/Outlook, OneDrive, and Teams.
- Design, configure, and maintain knowledge base structures using enterprise search and AI retrieval technologies, including indexing, metadata management, and content chunking strategies.
- Integrate structured data sources such as cloud databases, data warehouses, and storage platforms to support retrieval and analysis workflows.
- Generate and manage embeddings, configure vector stores, and optimize retrieval systems for AI applications.
- Develop retrieval evaluation frameworks to continuously improve relevance, accuracy, grounding, and citation quality.
- Implement secure data access controls, ensuring retrieval systems respect permissions, data classification policies, privacy requirements, and least-privilege principles.
- Partner with architects and engineering teams to align data strategies with overall solution designs and evaluation objectives.
- Transfer technical knowledge and best practices to customer teams, enabling long-term ownership and adoption.
- Document data flows, indexing approaches, retrieval configurations, connector capabilities, and implementation decisions for future reuse.
- Support the continuous improvement of AI knowledge systems by identifying data quality issues and optimization opportunities.
- 5+ years of professional experience, including at least 2 years working with relevant data, search, AI, or retrieval technologies.
- Hands-on experience with search platforms, knowledge bases, retrieval systems, or data pipelines supporting AI applications.
- Strong understanding of embeddings, vector databases, retrieval-augmented generation (RAG) patterns, and generative AI data workflows.
- Experience building data ingestion processes, connectors, indexing strategies, and content preparation workflows, ideally with enterprise collaboration platforms.
- Knowledge of data governance principles, including document-level and user-level permissions, data classification, privacy controls, and protection of sensitive information such as PHI/PII.
- Familiarity with AWS data and AI services, including Amazon Bedrock Knowledge Bases, OpenSearch, Athena, Redshift, RDS, and S3.
- Strong analytical and problem-solving skills with attention to data quality, accuracy, and system performance.
- Ability to collaborate effectively with technical teams and communicate complex concepts clearly to customers and stakeholders.
- Experience with enterprise search platforms such as Amazon OpenSearch, Kendra, Amazon Q Business, or similar technologies is preferred.
- Background in data engineering, information retrieval, or AI application development is a plus.
- Experience creating retrieval evaluation methods, quality monitoring processes, or working in regulated environments is preferred.
- AWS certifications related to data analytics or machine learning are a plus.
- Competitive contract opportunity with a fully remote work arrangement.
- Opportunity to work on advanced AI, search, and enterprise data projects.
- Exposure to modern cloud-based AI technologies and large-scale knowledge systems.
- Ability to collaborate with experienced architects, engineers, and customer teams.
- Opportunity to contribute to responsible AI adoption through secure and reliable data solutions.
- Flexible remote environment with occasional travel opportunities (up to 10%) for customer workshops and onsite sessions.
- Opportunity to expand expertise in AWS, retrieval systems, vector search, and generative AI technologies.