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Retrieval Augmented Generation Rag Jobs in Coraopolis, PA

GenAI Ops Solution Architect

Pittsburgh, PA · On-site

$61.25 - $80.50/hr

Retrieval Augmented Generation (RAG) * Agentic AI * Prompt Engineering * AI Evaluation Frameworks * ModelOps / LLMOps * AI Governance * Experience designing enterprise-scale cloud solutions on Azure ...

GenAI Ops Solution Architect

Pittsburgh, PA · On-site

$61.25 - $80.50/hr

Retrieval Augmented Generation (RAG) * Agentic AI * Prompt Engineering * AI Evaluation Frameworks * ModelOps / LLMOps * AI Governance * Experience designing enterprise-scale cloud solutions on Azure ...

Basic understanding of Retrieval-Augmented Generation (RAG) and vector databases. * Comfortable working with LLM APIs and integrating them into applications. * A solid understanding of machine ...

Engineer

Pittsburgh, PA · On-site

$100K - $105K/yr

Highly skilled Senior Full-Stack Engineer with strong expertise in Python, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) to design, and build an Agentic Platform for internal ...

Design Retrieval-Augmented Generation (RAG) pipelines for context-aware AI responses * Develop scalable backend services and APIs to support AI agent operations * Monitor agent performance ...

Engineer

Pittsburgh, PA · On-site

$100K - $120K/yr

Develop, optimize, and evaluate prompt strategies, embedding models, and Retrieval-Augmented Generation (RAG) systems to improve response accuracy. [1, 2, 3, 4, 5] * Infrastructure Management: Handle ...

Senior Software Engineer

Pittsburgh, PA · On-site

$118K - $156K/yr

... Retrieval-Augmented Generation (RAG) and vector databases. • Comfortable working with LLM APIs and integrating them into applications. • A solid understanding of machine learning concepts (e.g ...

Design Retrieval-Augmented Generation (RAG) pipelines for context-aware AI responses. * Develop scalable backend services and APIs to support AI agent operations. * Monitor agent performance ...

Design Retrieval-Augmented Generation (RAG) pipelines for context-aware AI responses. * Develop scalable backend services and APIs to support AI agent operations. * Monitor agent performance ...

Design Retrieval-Augmented Generation (RAG) pipelines for context-aware AI responses. * Develop scalable backend services and APIs to support AI agent operations. * Monitor agent performance ...

Design Retrieval-Augmented Generation (RAG) pipelines for context-aware AI responses. * Develop scalable backend services and APIs to support AI agent operations. * Monitor agent performance ...

Design Retrieval-Augmented Generation (RAG) pipelines for context-aware AI responses. * Develop scalable backend services and APIs to support AI agent operations. * Monitor agent performance ...

Design Retrieval-Augmented Generation (RAG) pipelines for context-aware AI responses. * Develop scalable backend services and APIs to support AI agent operations. * Monitor agent performance ...

Design Retrieval-Augmented Generation (RAG) pipelines for context-aware AI responses. * Develop scalable backend services and APIs to support AI agent operations. * Monitor agent performance ...

Design Retrieval-Augmented Generation (RAG) pipelines for context-aware AI responses. * Develop scalable backend services and APIs to support AI agent operations. * Monitor agent performance ...

Design Retrieval-Augmented Generation (RAG) pipelines for context-aware AI responses. * Develop scalable backend services and APIs to support AI agent operations. * Monitor agent performance ...

Design Retrieval-Augmented Generation (RAG) pipelines for context-aware AI responses. * Develop scalable backend services and APIs to support AI agent operations. * Monitor agent performance ...

Design Retrieval-Augmented Generation (RAG) pipelines for context-aware AI responses. * Develop scalable backend services and APIs to support AI agent operations. * Monitor agent performance ...

Showing results 21-40

Retrieval Augmented Generation Rag information

See Coraopolis, PA salary details

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How much do retrieval augmented generation rag jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for retrieval augmented generation rag in Coraopolis, PA is $19.31, according to ZipRecruiter salary data. Most workers in this role earn between $16.49 and $20.19 per hour, depending on experience, location, and employer.

What are popular job titles related to Retrieval Augmented Generation Rag jobs in Coraopolis, PA?

For Retrieval Augmented Generation Rag jobs in Coraopolis, PA, the most frequently searched job titles are:

Infographic showing various Retrieval Augmented Generation Rag job openings in Coraopolis, PA as of June 2026, with employment types broken down into 82% Full Time, and 18% Contract. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $40,167 per year, or $19.3 per hour.

GenAI Ops Solution Architect

System One

Pittsburgh, PA • On-site

$61.25 - $80.50/hr

Full-time

Re-posted 13 days ago


Job description

GenAI Ops Solution Architect Permanent Full Time 5 days Strongsville, OH, Dallas, TX, or Pittsburgh, PA. Visa : USC, GC, EAD (Only W2, No Sponsorship) Position Description GenAI Ops Solution Architect who will lead the design, governance, and evolution of enterprise-scale Generative AI platforms and solutions. This role is responsible for defining architecture standards, platform capabilities, integration patterns, governance controls, and engineering practices that enable secure, scalable, and reusable GenAI adoption across the enterprise. The architect will work closely with business stakeholders, engineering teams, platform teams, governance organizations, and cloud providers to establish a centralized GenAIOps capability supporting Retrieval Augmented Generation (RAG), Agentic AI, ModelOps, Evaluation, Observability, and AI Governance. Enterprise GenAI Architecture

  • Define and govern the enterprise GenAI platform architecture.
  • Establish architecture standards, design patterns, and reusable frameworks for enterprise AI adoption.
  • Lead solution design for RAG, Document Intelligence, Agentic AI, Evaluation, Observability, and Governance capabilities.
  • Define reference architectures and integration patterns for onboarding GenAI use cases.
GenAIOps Platform Leadership
  • Drive the design and implementation of centralized GenAIOps capabilities including:
    • RAG & Retrieval Services
    • AgentOps
    • ModelOps / LLMOps
    • Evaluation Pipelines
    • Observability & Monitoring
    • AI Governance & Controls
  • Establish reusable engineering patterns and shared platform services.
Architecture Governance
  • Lead architecture reviews and technical governance processes.
  • Ensure alignment with enterprise security, compliance, risk, and regulatory requirements.
  • Define standards for Responsible AI, auditability, traceability, and human-in-the-loop controls.
  • Participate in governance forums and stakeholder reviews.
Cloud & Integration Strategy
  • Define cloud architecture and deployment strategies across Azure, AWS, or hybrid environments.
  • Establish enterprise integration patterns for APIs, data platforms, document repositories, workflow systems, and identity providers.
  • Lead architecture decisions around scalability, resiliency, security, and performance.
Engineering Leadership
  • Provide technical leadership to Value Engineers, Context Engineers, Alignment Engineers, and ModelOps teams.
  • Support platform onboarding and use case architecture activities.
  • Mentor engineering teams and drive adoption of best practices.
  • Evaluate emerging GenAI technologies and recommend platform enhancements.
Stakeholder Engagement
  • Collaborate with business and technology leaders to align architecture decisions with strategic objectives.
  • Support roadmap planning, platform evolution, and capability expansion initiatives.
  • Act as the primary architecture authority for enterprise GenAI initiatives.
Required Qualifications
  • 10+ years of experience in Solution Architecture, Enterprise Architecture, Cloud Architecture, or Platform Engineering.
  • 3+ years of experience designing and implementing Generative AI and enterprise AI solutions.
  • Deep understanding of:
    • Large Language Models (LLMs)
    • Retrieval Augmented Generation (RAG)
    • Agentic AI
    • Prompt Engineering
    • AI Evaluation Frameworks
    • ModelOps / LLMOps
    • AI Governance
  • Experience designing enterprise-scale cloud solutions on Azure, AWS, or GCP.
  • Strong knowledge of microservices, APIs, event-driven architectures, and distributed systems.
  • Experience leading architecture governance and enterprise technology standards.
  • Strong stakeholder management and executive communication skills.
Success Measures
  • Establish a scalable and reusable enterprise GenAI platform.
  • Accelerate onboarding of GenAI use cases through reusable architecture patterns.
  • Ensure alignment with governance, security, and compliance requirements.
  • Improve platform adoption, operational efficiency, and engineering productivity.
  • Enable sustainable long-term ownership through architecture standardization and knowledge transfer.
#M1 #DI-CB2 #L1 - KB1


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About System One

Sourced by ZipRecruiter

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