GenAI Context Engineer

Job Description

Job Description

Job Title: GenAI Context Engineer Duration : Permanent Full Time Location : Strongsville, OH, Dallas, TX, or Pittsburgh, PA. Work Mode : 5 Days Onsite Looking to hire a Context Engineer who will be responsible for designing, building, and optimizing the enterprise knowledge and retrieval foundation that powers Generative AI applications. This role focuses on enabling high quality, grounded, and context aware AI experiences through Retrieval Augmented Generation (RAG), semantic search, metadata engineering, and enterprise knowledge orchestration. The Context Engineer ensures AI systems retrieve the right information, from the right sources, at the right time — securely, accurately, and in alignment with enterprise governance standards. Future duties and responsibilities

• Design and implement enterprise Retrieval Augmented Generation (RAG) architectures for GenAI platforms and applications.
• Build and optimize semantic retrieval pipelines, vector search implementations, and contextual grounding frameworks.
• Develop ingestion pipelines for enterprise knowledge sources including SharePoint, Confluence, Jira, APIs, databases, and document repositories.
• Define metadata, taxonomy, ontology, chunking, and embedding strategies to improve retrieval relevance and AI response quality.
• Implement permission aware retrieval and secure knowledge access aligned with enterprise governance and compliance requirements.
• Design and optimize hybrid search architectures combining vector search, keyword search, and knowledge graph capabilities.
• Collaborate with Value Engineers, architects, and business stakeholders to translate enterprise knowledge into scalable AI ready knowledge structures.
• Improve groundedness, citation accuracy, retrieval precision, and hallucination reduction across GenAI solutions.
• Maintain knowledge lineage, auditability, and contextual traceability for enterprise AI workflows.
• Support AI evaluation, observability, and continuous improvement initiatives for retrieval quality and search performance.
• Work closely with governance, security, and compliance teams to ensure responsible and secure enterprise AI knowledge access.
• Contribute to reusable enterprise knowledge engineering patterns and platform accelerators.