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Retrieval Augmented Generation Jobs in Riverside, CA

RAVE Aerospace LLC

AI Developer

Brea, CA · On-site

Working knowledge of retrieval-augmented generation (RAG): embeddings, vector search, chunking strategies * Solid SQL and relational data modeling skills * Comfortable with containerized development ...

Qcells Europe

Applied AI Engineer

Irvine, CA · On-site

$121K - $145K/yr

... Implement Retrieval-Augmented Generation (RAG) pipelines, AI agentic patterns, and multi-modal model architectures to address complex use cases. • Collaborate with data engineers to collect ...

Origence

AI Solution Architect

Irvine, CA

$67.50 - $89/hr

Implement RAG (Retrieval-Augmented Generation) architectures leveraging Microsoft Fabric's unified data platform and MCP servers * Implement vector search and semantic capabilities within the ...

Reply

AI/ML Engineer (AWS)

Irvine, CA · Remote

$120K - $155K/yr

Experience with retrieval-augmented generation (RAG), embeddings, or agent-based architectures. * Experience designing distributed systems or working within cloud-based environments. * Experience ...

Corvel

Data Science Manager

Irvine, CA · On-site

$119K - $197K/yr

Knowledge of Retrieval-Augmented Generation (RAG) patterns, including how to manage embeddings, vector indexing, and the "chunking" of unstructured data for AI consumption * Excellent written and ...

Corvel

Data Science Manager

Irvine, CA · On-site +1

Knowledge of Retrieval-Augmented Generation (RAG) patterns, including how to manage embeddings, vector indexing, and the "chunking" of unstructured data for AI consumption * Excellent written and ...

CompassX Group

Solution Architect - GenAI

Irvine, CA · On-site

$150K - $190K/yr

Design end-to-end architectures for AI-powered applications - from LLM selection and prompt engineering through orchestration, retrieval-augmented generation (RAG), and integration with enterprise ...

CompassX Group

Solution Architect - GenAI

Irvine, CA · On-site

$67.50 - $89/hr

Design end-to-end architectures for AI-powered applications - from LLM selection and prompt engineering through orchestration, retrieval-augmented generation (RAG), and integration with enterprise ...

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Retrieval Augmented Generation information

What are the typical daily responsibilities of a Retrieval Augmented Generation engineer?

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 is a Retrieval Augmented Generation job?

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 are the key skills and qualifications needed to thrive in the Retrieval Augmented Generation position, and why are they important?

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 Riverside, CA? The most popular types of Retrieval Augmented Generation jobs in Riverside, CA are:
What are popular job titles related to Retrieval Augmented Generation jobs in Riverside, CA? For Retrieval Augmented Generation jobs in Riverside, CA, the most frequently searched job titles are:
What job categories do people searching Retrieval Augmented Generation jobs in Riverside, CA look for? The top searched job categories for Retrieval Augmented Generation jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for Retrieval Augmented Generation jobs? Cities near Riverside, CA with the most Retrieval Augmented Generation job openings:
Retrieval Augmented Generation jobs near you

AI Developer

RAVE Aerospace LLC

Brea, CA • On-site

Full-time

Medical, Retirement, PTO

Posted 12 days ago

Job description

RAVE Aerospace is redefining the in-flight experience through innovative entertainment and connectivity solutions trusted by airlines around the world. We combine advanced hardware, intelligent software, and connected digital platforms to help airlines create more engaging, seamless, and reliable passenger experiences. As the future of air travel evolves, RAVE is building the technology that keeps passengers connected from takeoff to landing.

We are seeking an experienced AI Developer to design, build, and scale production AI applications and autonomous agents on a modern, self-hosted platform. This role will play a key part in shaping the architecture, tooling, and engineering standards that power AI capabilities across the organization. Working across the full technology stack, the AI Developer will leverage large language models and AI coding agents as core components of the development process to deliver reliable, high-impact solutions. This is a highly influential, hands-on engineering role focused on building practical, production-ready AI systems in a fast-moving and collaborative environment.

This individual is equally comfortable discussing architecture and implementing solutions, with a strong sense of ownership and a desire to influence platform direction, tooling decisions, and engineering best practices. They are curious, adaptable, and energized by solving complex problems while building scalable, maintainable systems. Strong collaboration and communication skills are essential, as this role partners closely with technical and cross-functional teams to bring AI capabilities into production.

Responsibilities

  • Design and implement AI-powered services, agents, and internal applications
  • Build and maintain MCP (Model Context Protocol) servers that expose enterprise systems to LLM clients
  • Develop end-to-end features — backend services, data pipelines, and user-facing UIs — using agent-assisted workflows
  • Design retrieval pipelines (chunking, embeddings, vector search) and prompt strategies
  • Integrate LLMs across managed and self-hosted runtimes, choosing the right tool for cost, latency, and privacy constraints
  • Instrument prompts and agents with traces, evals, and regression checks
  • Enforce shared platform conventions: authentication, RBAC, container networking, secrets handling
  • Mentor other engineers on applied AI patterns and on getting the most out of agentic coding tools

Requirements

Required Skills & Experience

  • 10+ years of experience in software engineering
  • 2+ years working directly with AI/ML or LLM-based applications
  • Strong software engineering fundamentals) — systems thinking, debugging, API design, data modeling
  • Production experience shipping web services and/or data products in any modern stack
  • Demonstrated fluency with AI coding agents (Claude Code, Cursor, Copilot, Aider, or similar) as part of daily work
  • Practical experience integrating LLMs into real products (any major provider)
  • Working knowledge of retrieval-augmented generation (RAG): embeddings, vector search, chunking strategies
  • Solid SQL and relational data modeling skills
  • Comfortable with containerized development (Docker / docker-compose)
  • A pragmatic approach to tests, observability, and operational quality

Preferred Experience

Hands-on experience with any of the following:

  • Model Context Protocol (MCP) — building servers and/or clients
  • Managed LLM platforms (Bedrock, Anthropic, OpenAI, Azure OpenAI)
  • Self-hosted LLM runtimes (Ollama, vLLM, llama.cpp)
  • Production vector databases (Qdrant, pgvector, Weaviate, Pinecone)
  • LLM observability and eval tooling (Langfuse, LangSmith, Phoenix, etc.)
  • Workflow orchestration (Prefect, Airflow, Dagster)
  • Modern frontend work (React or similar) for building internal tools and agent UIs
  • SSO / OIDC and role-based access control patterns
  • Prompt engineering and structured-output techniques (tool use, JSON schema, function calling)
  • Experience operating GPU workloads on Linux
  • Prior technical leadership or tech-lead experience on AI / data products

Development Environment

  • Self-hosted Linux platform with GPU acceleration for local model inference
  • Containerized services with shared internal networking
  • AI coding agents available and encouraged for day-to-day development
  • Local-first development with simple bypasses for auth and external dependencies
  • Focus on simplicity, observability, and reproducibility over framework sprawl

What We're Looking For

  • An applied AI engineer who ships — comfortable owning a feature from prompt design through production rollout
  • Someone who treats LLMs as one component in a system, not the whole system — strong fundamentals in APIs, data, and infrastructure
  • An engineer who is genuinely fluent with agentic coding tools and can demonstrate how they use them to multiply their output
  • A pragmatic builder who values evals, traces, and clear contracts over framework magic
  • A collaborator who can translate fuzzy stakeholder requests into concrete agent and application designs

Benefits

The base salary range for this position is $150,000-200,000 per year and reflects multiple levels within the role. Final level and compensation will be determined based on the candidate’s skills, experience, qualifications, and internal equity.

In addition to a comprehensive package of health benefits that include company contributions, RAVE Aerospace offers a variety of additional benefits and perks to enhance your work-life balance experience including but not limited to:

  • A home allowance to elevate your home workspace
  • Discretionary bonus program
  • Future financial security with a 401(k) program with company match
  • Paid time off covering vacations, personal time off and sick days, capped off by an exciting year-end holiday shutdown
  • Embraced flexibility with our alternative work schedule (9/80) to navigate your workweeks with every other Friday off