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Gen AI Engineer Oaks - PA - Pennsylvania

Sierra Business Solution LLCOaks, PA🇺🇸United StatesPosted Oct 12, 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Oaks, PA, United States
Posted
20 hours ago
SQLPython

Job Description

Role Name - Sr. Data & Knowledge Engineer

Skills: AI AgentsAI & Gen AI - Products & Tools Experience Required: 10 & Above

ROLE_DESCRIPTION -

The Senior Data and Knowledge Engineer will build the data and knowledge foundation required for reliable enterprise AI solutions, with particular emphasis on RAG, enterprise knowledge integration, content ingestion, embeddings, and AI-ready data pipelines.

Key Responsibilities

Design data and knowledge architectures for AI and GenAI applications.

Build ingestion and transformation pipelines for structured and unstructured enterprise information.

Design RAG pipelines and enterprise knowledge-retrieval solutions.

Implement chunking, metadata, embeddings, indexing, retrieval, and reranking strategies.

Build and optimize vector-search capabilities.

Integrate databases, documents, APIs, knowledge repositories, and other enterprise sources.

Develop processes for improving knowledge quality, freshness, lineage, and traceability.

Support structured data integration for AI agents and applications.

Work with AI engineers to improve grounding and retrieval quality.

Implement appropriate access controls for enterprise knowledge.

Develop reusable data and knowledge components that can support multiple AI use cases.

Required Skills

Strong data engineering background.

Advanced Python and SQL.

Experience with modern data platforms and cloud-native data services.

Hands-on knowledge of RAG, embeddings, vector databases, semantic search, and information retrieval.

Experience processing structured and unstructured data.

Understanding of data quality, metadata, lineage, security, and governance.

Preferred Experience

8+ years in data engineering, information management, or knowledge engineering.

Experience developing production RAG solutions.

Familiarity with knowledge graphs and semantic technologies is desirable.

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