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Rag Hiring Jobs (NOW HIRING)

Ally Waste Services

Trash Valet (RAG)

Bradenton, FL · On-site

$60/hr

Trash Collector Ally Waste Services is currently hiring for a part-time Trash Collector to join our team! This trash valet position works part-time starting at 7 pm and earns a competitive wage of ...

Ally Waste Services

Trash Valet (RAG)

Bradenton, FL · On-site

$50 - $60/day

Trash Collector Ally Waste Services is currently hiring for a part-time Trash Collector to join our team! This trash valet position works part-time starting at 7 pm and earns a competitive wage of ...

Harnham

Software Engineer AI

San Jose, CA · On-site

$190K - $240K/yr

... is hiring a Software Engineer, A I to own the full-stack development of customer-facing AI features. This is a product engineering role, not platform/infra -- you'll turn LLMs, agents, and RAG ...

New

Harnham

Software Engineer AI

Alameda, CA · On-site

$190K - $240K/yr

... is hiring a Software Engineer, A I to own the full-stack development of customer-facing AI features. This is a product engineering role, not platform/infra -- you'll turn LLMs, agents, and RAG ...

New

Harnham

Software Engineer AI

Mundelein, IL · On-site

$190K - $240K/yr

... is hiring a Software Engineer, A I to own the full-stack development of customer-facing AI features. This is a product engineering role, not platform/infra -- you'll turn LLMs, agents, and RAG ...

New

Harnham

Software Engineer AI

Sonoma, CA · On-site

$190K - $240K/yr

... is hiring a Software Engineer, A I to own the full-stack development of customer-facing AI features. This is a product engineering role, not platform/infra -- you'll turn LLMs, agents, and RAG ...

New

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All JobsRag Hiring Jobs

Rag Hiring information

See salary details

$40.5K

$78.8K

$118.5K

How much do rag hiring jobs pay per year?

As of Aug 29, 2026, the average yearly pay for rag hiring in the United States is $78,753.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,000.00 and $93,500.00 per year, depending on experience, location, and employer.

What is the difference between Rag Hiring vs Fabricator?

AspectRag HiringFabricator
Required CredentialsHigh school diploma or equivalent, basic safety trainingHigh school diploma, technical training or apprenticeship
Work EnvironmentConstruction sites, industrial settingsManufacturing plants, workshops
Employer & Industry UsageConstruction companies, industrial firmsMetalworking, manufacturing industries
Common Search & ComparisonYesYes

Rag Hiring typically refers to temporary or casual labor hiring, often for manual tasks, while Fabricators are skilled workers involved in metal or material fabrication. Both roles may require safety training and work in industrial environments, but Fabricators usually have more technical skills and training. Understanding these differences helps job seekers find the right opportunities based on skills and industry focus.

More about Rag Hiring jobs

What cities are hiring for Rag Hiring jobs?

Cities with the most Rag Hiring job openings:

What states have the most Rag Hiring jobs?

States with the most job openings for Rag Hiring jobs include:

What job categories do people searching Rag Hiring jobs look for?

The top searched job categories for Rag Hiring jobs are:

Rag Hiring jobs near you
Infographic showing various Rag Hiring job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 20% Part Time, 3% Contract, and 1% Nights. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $78,753 per year, or $37.9 per hour.

Senior AI Engineer - LLM, RAG

BrightAI Corporation

Palo Alto, CA • On-site

$122K - $168K/yr

Full-time

Re-posted 25 days ago

Job description

Sr. AI Engineer - LLM, RAG
BrightAI is a high-growth Physical AI company transforming how businesses interact with the physical world through intelligent automation. Our AI platform processes visual, spatial, and temporal data from billions of real-world events-captured across edge devices, mobile sensors, and cloud infrastructure-to enable intelligent decision-making at scale.
We are now hiring a Sr. AI Engineer - LLM, RAG to lead the development of Retrieval-Augmented Generation (RAG) systems that harness the power of large language models (LLMs) and real-world knowledge sources. This role is pivotal to building next-generation intelligent assistants that help technicians and operators troubleshoot complex issues in industrial settings.
You'll work at the intersection of NLP, foundational models, and real-time information systems-developing intelligent tools that turn manuals, technician notes, and sensor data into actionable, conversational guidance for the physical world.
Responsibilities
  • Lead the architecture and development of RAG systems that combine LLMs (e.g., LLAMA, Mistral, Claude, GPT) with structured and unstructured external information sources.
  • Develop AI-powered assistants to support technicians in diagnosing and resolving anomalies or failures in factory, plant, or industrial settings.
  • Build pipelines to ingest, preprocess, and index large corpora of documents (manuals, logs, notes, procedures) for semantic search and grounding.
  • Customize and fine-tune foundational models to incorporate domain-specific language, tone, and logic for industrial troubleshooting scenarios.
  • Collaborate with product, data, and cloud teams to design scalable, privacy-compliant, and latency-sensitive LLM applications.
  • Design evaluation strategies to measure performance, accuracy, and user experience of RAG-enabled systems in production settings.
  • Stay up to date with the latest advances in LLM architectures, retrieval methods, and prompt engineering, and integrate emerging techniques into the product roadmap.
Educational Background
  • M.S. or Ph.D. in Computer Science, AI, Machine Learning, or a related field, with specialization in NLP or deep learning.
  • Strong research or applied background in large language models (LLMs) and retrieval-augmented generation (RAG) systems. Agentic RAG experience is highly desirable.
Required Skills & Expertise
  • 5+ years of experience in machine learning or AI with a strong focus on NLP, LLMs, or conversational AI.
  • Fluency with modern LLMs and open-source foundational models (e.g., LLAMA, Falcon, Mistral, GPT, Claude).
  • Experience building RAG pipelines with tools like LangChain, LlamaIndex, or custom vector database integrations, with at least one production grade system was built.
  • Fluency with prompt engineering, instruction tuning, or fine-tuning open-source models.
  • Deep understanding of document retrieval (semantic search, embedding generation, similarity metrics) and vector stores (e.g., FAISS, Weaviate, Pinecone).
  • Strong foundation in core machine learning techniques, including experience with reinforcement learning (RL) or decision-making models.
  • Proficiency with ML development frameworks such as PyTorch, Hugging Face Transformers, or similar. Strong Python programming is a must.
  • Experience integrating AI systems into real-world applications with user-facing interfaces and operational constraints.
  • Excellent problem-solving and critical thinking skills; ability to design solutions for complex, ambiguous problems.
  • Strong written and verbal communication skills, with ability to collaborate cross-functionally with engineers, product managers, and domain experts.
Bonus Qualifications
  • Experience applying LLMs in industrial or physical infrastructure settings (e.g., manufacturing, logistics, utilities, energy).
  • Knowledge of industrial control systems, maintenance workflows, or technician support processes.
  • Exposure to multimodal models or integrating textual data with sensor and/or time-series data.
  • Prior experience in a startup or a fast-paced environment building LLM-powered products from the ground up.
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About BrightAI

Sourced by ZipRecruiter

Industry

Software development

Company size

11 - 50 Employees

Headquarters location

San Francisco, CA, US

Year founded

2019

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