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Retrieval Augmented Generation Jobs in Pennsylvania

Design and implement enterprise Retrieval Augmented Generation (RAG) architectures for GenAI platforms and applications. * Build and optimize semantic retrieval pipelines, vector search ...

Design and implement enterprise Retrieval Augmented Generation (RAG) architectures for GenAI platforms and applications. * Build and optimize semantic retrieval pipelines, vector search ...

Design and implement enterprise Retrieval Augmented Generation (RAG) architectures for GenAI platforms and applications. * Build and optimize semantic retrieval pipelines, vector search ...

Python AI Developer

Malvern, PA · On-site

$49.25 - $68/hr

Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions * Hands-on experience with LangChain or similar AI orchestration frameworks * Experience with AWS services such as:

Computer/Data Scientist

West Mifflin, PA · On-site

$120K - $145K/yr

This position focuses on applying retrieval-augmented generation (RAG) and large language models (LLMs) to enhance information retrieval and enable the creation of detailed safety documents and ...

This position focuses on applying retrieval-augmented generation (RAG) and large language models (LLMs) to enhance information retrieval and enable the creation of detailed safety documents and ...

GenAI Ops Solution Architect

Pittsburgh, PA · On-site

$61.25 - $80.50/hr

... Retrieval Augmented Generation (RAG), Agentic AI, ModelOps, Evaluation, Observability, and AI Governance. Future duties and responsibilities Enterprise GenAI Architecture * Define and govern the ...

GenAI Ops Solution Architect

Pittsburgh, PA · On-site

$61.25 - $80.50/hr

... Retrieval Augmented Generation (RAG), Agentic AI, ModelOps, Evaluation, Observability, and AI Governance. Future duties and responsibilities Enterprise GenAI Architecture * Define and govern the ...

Computer/Data Scientist

West Mifflin, PA · On-site

$120K - $145K/yr

This position focuses on applying retrieval-augmented generation (RAG) and large language models (LLMs) to enhance information retrieval and enable the creation of detailed safety documents and ...

GenAI Ops Solution Architect

Pittsburgh, PA · On-site

$61.25 - $80.50/hr

... Retrieval Augmented Generation (RAG), Agentic AI, ModelOps, Evaluation, Observability, and AI Governance. Future duties and responsibilities Enterprise GenAI Architecture * Define and govern the ...

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Retrieval Augmented Generation information

What is a retrieval augmented generation?

A Retrieval Augmented Generation (RAG) job typically involves developing and optimizing AI systems that enhance text generation by incorporating external knowledge retrieved from relevant sources. Professionals in this field work on integrating retrieval mechanisms with large language models to improve the relevance, accuracy, and factual grounding of generated content. Common responsibilities include designing retrieval systems, fine-tuning language models, optimizing performance, and ensuring the seamless integration of factual data into AI-generated text. This role is highly interdisciplinary, involving expertise in natural language processing (NLP), machine learning, and information retrieval.

What does a retrieval augmented generation engineer do?

A Retrieval Augmented Generation engineer typically spends their day designing and implementing systems that combine information retrieval with advanced generative models, such as large language models. This includes fine-tuning models, integrating external data sources, developing vector search pipelines, and evaluating output quality. Collaboration with data scientists, machine learning engineers, and product teams is common to ensure the solutions meet user requirements and scale effectively. Additionally, RAG engineers often troubleshoot issues, monitor model performance in production, and stay informed about the latest advancements in AI and information retrieval.

What skills and qualifications are needed for retrieval augmented generation?

To thrive in a Retrieval Augmented Generation (RAG) engineering role, you need a solid background in machine learning, natural language processing (NLP), and experience with scalable information retrieval systems, typically supported by a relevant degree in computer science or a related field. Familiarity with tools such as Python, PyTorch or TensorFlow, vector databases, and search platforms like Elasticsearch is essential, along with practical experience deploying and tuning RAG pipelines. Strong problem-solving skills, a collaborative mindset, and effective communication abilities set outstanding professionals apart in this field. These competencies are crucial for designing, implementing, and optimizing hybrid retrieval-generation AI systems that address complex, real-world information needs.

What are the most commonly searched types of Retrieval Augmented Generation jobs in Pennsylvania?

The most popular types of Retrieval Augmented Generation jobs in Pennsylvania are:

What are popular job titles related to Retrieval Augmented Generation jobs in Pennsylvania?

For Retrieval Augmented Generation jobs in Pennsylvania, the most frequently searched job titles are:

What job categories do people searching Retrieval Augmented Generation jobs in Pennsylvania look for?

The top searched job categories for Retrieval Augmented Generation jobs in Pennsylvania are:

What cities in Pennsylvania are hiring for Retrieval Augmented Generation jobs?

Cities in Pennsylvania with the most Retrieval Augmented Generation job openings:

Infographic showing various Retrieval Augmented Generation job openings in Pennsylvania as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution.

GenAI Context Engineer

System One

Pittsburgh, PA • On-site

Full-time

Re-posted 16 days ago


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.
Required qualifications to be successful in this role
  • 6+ years of experience in knowledge engineering, enterprise search, data engineering, AI engineering, or platform engineering roles.
  • Experience building enterprise AI search or knowledge platforms in banking, financial services, healthcare, or other regulated industries.
  • Familiarity with knowledge graphs, ontology modeling, AI observability, and enterprise governance frameworks.
  • Understanding of responsible AI, groundedness evaluation, and enterprise compliance requirements for GenAI systems.
  • Hands on experience with Retrieval Augmented Generation (RAG), semantic search, embeddings, vector databases, and enterprise knowledge systems.
  • Strong programming skills in Python and experience with API based integrations.
  • Experience with GenAI and retrieval technologies such as: o Azure OpenAI / OpenAI o Azure AI Search o LangChain / Semantic Kernel o Elasticsearch / OpenSearch o Vector databases and embedding frameworks
  • Experience designing ingestion pipelines, metadata frameworks, chunking strategies, and contextual retrieval systems.
  • Strong understanding of enterprise data governance, access control, lineage, and permission aware retrieval. Experience integrating enterprise content systems including SharePoint, Confluence, Jira, document repositories, and enterprise APIs.
  • Familiarity with cloud platforms such as Azure, AWS, or GCP and containerized environments.
  • Strong analytical, troubleshooting, and problem solving skills.
  • Excellent communication and collaboration skills with the ability to work across engineering, architecture, governance, and business teams.
Required Skills:
  • LangChain
  • LangGraph
  • LlamaIndex
  • Microsoft Azure AI Solution
  • OpenAI
  • Python
  • Retrieval-Augmented Gen.(RAG)
Ref: #404-IT Pittsburgh


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About System One

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System One helps employers get work done more efficiently and economically without compromising quality. Over our 35+ year history, we've helped connect thousands of talented people with innovative companies. The excitement of a perfect fit motivates us every single day.

Industry

Business consulting services and recruiting and staffing services

Company size

5,001 - 10,000 Employees

Headquarters location

Pittsburgh, PA, US