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Retrieval Augmented Generation Jobs in Rancho Cordova, CA

Data & AI Engineer

Sacramento, CA

$117K - $141K/yr

Applies foundational AI and agent-building skills, such as working with large language models, basic tool use, and retrieval-augmented generation, to support business use cases that require AI and ...

New

Data & AI Engineer

Sacramento, CA · On-site

$117K - $141K/yr

Applies foundational AI and agent-building skills, such as working with large language models, basic tool use, and retrieval-augmented generation, to support business use cases that require AI and ...

Applied AI Engineer

Sacramento, CA · On-site

$117K - $141K/yr

Architects reasoning chains, tool use, retrieval-augmented generation, and error handling; builds evaluation frameworks and monitors agent performance in production. * Leads governance of AI agents ...

Architect and deliver integrated AI solutions, including agentic workflows, retrieval-augmented generation pipelines, and enterprise platform integrations * Define and enforce governance, security ...

Experience with Retrieval-Augmented Generation (RAG) pipelines and open vector search ecosystems. * Background in high-performance computing (HPC) or hyperscale distributed environments. * Expertise ...

Platform Engineer

Roseville, CA · On-site

$35.54 - $47.37/hr

Use orchestration, prompt design, retrieval-augmented generation, structured outputs, and workflow automation to create dependable business solutions. * Establish appropriate validation, monitoring ...

Data Engineer

Rancho Cordova, CA · On-site

$122K - $146K/yr

Build and maintain data stores and indexing infrastructure that support retrieval-augmented generation (RAG) and other AI consumption patterns. * Implement data quality, validation, and lineage ...

Build and maintain data stores and indexing infrastructure that support retrieval-augmented generation (RAG) and other AI consumption patterns. * Implement data quality, validation, and lineage ...

Integrate enterprise data sources securely, including APIs, Graph connectors, retrieval-augmented generation (RAG), and event-driven patterns. * Maintain and optimize Power BI dashboards that support ...

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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.

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

Exciting opportunity for AI Engineer_ Rancho Cordova, CA-Onsite

Noblesoft Technologies

Rancho Cordova, CA • On-site

Contractor

Re-posted 16 days ago


Job description

Job Title:  AI Engineer

Location: Rancho Cordova, CA

Mode: Contract (6+ Months)

Job Description:

Responsibilities:

  • Develop, fine tune, and evaluate machine learning and LLM based models.
  • Build end to end AI pipelines including data preprocessing, feature engineering, training, and monitoring.
  • Design and optimize prompting strategies, RAG pipelines, or agent based workflows for LLM applications.
  • Implement production ready AI services and APIs using scalable architectures.
  • Collaborate with product managers and engineers to identify AI use cases and translate requirements into technical solutions.
  • Monitor model performance and drift, implementing continual improvements.
  • Conduct research into emerging AI techniques and tools to recommend adoption where appropriate.
  • Ensure responsible AI practices including fairness, safety, privacy, and compliance.

Required Qualifications:

  • Bachelor’s or Master’s in Computer Science, Machine Learning, Engineering, or a related field.
  • Experience with machine learning frameworks such as PyTorch, TensorFlow, or JAX.
  • Strong software engineering skills in Python, plus experience with APIs, cloud services (Azure, AWS, or GCP), and containerization.
  • Hands on experience building applications using LLMs (e.g., OpenAI, Azure OpenAI, Hugging Face, Anthropic).
  • Familiarity with vector databases (e.g., FAISS, Milvus, Pinecone) and retrieval augmented generation (RAG).
  • Experience deploying AI models to production environments.
  • Strong understanding of data structures, algorithms, and system design.