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Rag Jobs (NOW HIRING)

Rag & Bone

Women's Designer, Cut & Sew Knits

Manhattan, NY · On-site

$80K - $95K/yr

About rag & bone: From our origins in New York in 2002, rag & bone was founded on a belief of uncompromising ideals: a commitment to doing things the right way, not the easy way. To making things ...

Rag & Bone

Assistant Store Manager

Aspen, CO · On-site

From our origins in New York in 2002, rag & bone was founded on a belief of uncompromising ideals: a commitment to doing things the right way, not the easy way. To making things that are as original ...

Rag & Bone

Store Manager

Seattle, WA · On-site

$80K - $90K/yr

About rag & bone From our origins in New York in 2002, rag & bone was founded on a belief of uncompromising ideals: a commitment to doing things the right way, not the easy way. To making things that ...

Rag & Bone

Assistant Store Manager

Livermore, CA · On-site

Rag & Bone Assistant Store Manager From our origins in New York in 2002, rag & bone was founded on a belief of uncompromising ideals: a commitment to doing things the right way, not the easy way. To ...

Rag & Bone

Store Manager

Central Valley, NY · On-site

About rag & bone From our origins in New York in 2002, rag & bone was founded on a belief of uncompromising ideals: a commitment to doing things the right way, not the easy way. To making things that ...

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Rag & Bone

Sales Specialist (Part Time)

Manhasset, NY · On-site

From our origins in New York in 2002, rag & bone was founded on a belief of uncompromising ideals: a commitment to doing things the right way, not the easy way. To making things that are as original ...

rag and bone

PT sales specialist

Wrentham, MA · On-site

Rag and Bone is looking for a sales representative to join our team in our Wrentham office. This person will actively seek out and engage prospective customers to sell our product and/or services.

Rag & Bone

Part-Time Sales Specialist

Marysville, WA · On-site

$18 - $20/hr

About rag & bone From our origins in New York in 2002, rag & bone was founded on a belief of uncompromising ideals: a commitment to doing things the right way, not the easy way. To making things that ...

Rag & Bone

Copywriter

Manhattan, NY · On-site

$105K - $110K/yr

Title - Copywriter About rag & bone From our origins in New York in 2002, rag & bone was founded on a belief of uncompromising ideals: a commitment to doing things the right way, not the easy way. To ...

Rag & Bone

Store Manager - Greenwich, CT

Greenwich, CT · On-site

About rag & bone From our origins in New York in 2002, rag & bone was founded on a belief of uncompromising ideals: a commitment to doing things the right way, not the easy way. To making things that ...

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Rag information

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$40.5K

$78.8K

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How much do rag jobs pay per year?

As of Jul 12, 2026, the average yearly pay for rag 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 a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer, AI research director, or executive roles like AI CTO. These roles often require advanced skills in programming, data analysis, and experience with AI frameworks, and may involve leadership responsibilities or specialized expertise in areas like deep learning or natural language processing.

Is RAG in demand?

RAG (Retrieval-Augmented Generation) is an emerging technology in the AI and machine learning fields, increasingly used in applications like chatbots and data analysis. Demand for skills in RAG and related AI tools is growing as organizations seek advanced natural language processing solutions. Professionals with knowledge of AI models, data retrieval, and programming languages such as Python are increasingly sought after in this area.

What are RAGs in the context of AI and machine learning jobs?

RAG stands for Retrieval-Augmented Generation, a model architecture that combines information retrieval with generative AI. In this role, a RAG specialist or engineer works on designing, implementing, and optimizing systems that retrieve relevant data from large databases to provide more accurate and informed AI-generated responses. This position typically requires strong knowledge of natural language processing, information retrieval, and deep learning frameworks. RAG models are particularly useful in applications like customer support, search engines, and knowledge management systems.

What are the key skills and qualifications needed to thrive as a RAG Engineer, and why are they important?

To thrive as a Retrieval-Augmented Generation (RAG) Engineer, you need a strong background in machine learning, natural language processing, and software engineering, often with a degree in computer science or a related field. Familiarity with frameworks like PyTorch or TensorFlow, experience with vector databases, and knowledge of APIs for language models are typically required. Problem-solving, effective communication, and adaptability are crucial soft skills for collaborating with teams and navigating evolving technologies. These skills are important to successfully develop, deploy, and maintain RAG systems that enhance the performance and relevance of AI-driven applications.

What is a RAG job?

A RAG job typically refers to a role involving Red, Amber, and Green (RAG) status reporting, often used in project management to indicate progress or risk levels. Such jobs may require skills in data analysis, reporting tools, and project coordination to monitor and communicate project health effectively.

What is the difference between Rag vs Data Analyst?

AspectRagData Analyst
Required CredentialsVaries, often no formal degreeBachelor's degree in data-related field, often certifications
Work EnvironmentFieldwork, on-site, or warehouse settingsOffice-based, computer-focused
Employer & Industry UsageConstruction, manufacturing, logisticsFinance, marketing, healthcare, tech
Common Search & ComparisonRag vs Data AnalystData Analyst roles and responsibilities

While Rags typically work in physical environments handling materials or equipment, Data Analysts focus on interpreting data to inform business decisions. Both roles require analytical skills but differ significantly in credentials, work setting, and industry applications.

What are some common challenges faced by RAG (Retrieval-Augmented Generation) engineers when integrating retrieval systems with large language models?

RAG engineers often encounter challenges in ensuring the seamless integration of retrieval systems with large language models, such as maintaining low latency while fetching relevant documents and ensuring retrieved data is contextually appropriate for generation tasks. Balancing retrieval accuracy and computational efficiency is key, especially when dealing with large-scale or real-time applications. Effective collaboration with data engineers, NLP researchers, and product teams is essential to continuously refine retrieval pipelines and improve the relevance of generated outputs.

What jobs pay 500,000 a year in the US?

High-paying jobs that can reach or exceed $500,000 annually in the US include roles such as senior corporate executives, investment bankers, specialized surgeons, and successful entrepreneurs. These positions often require advanced degrees, extensive experience, and strong industry networks, with compensation frequently including bonuses, stock options, or profit sharing.
More about Rag jobs
What cities are hiring for Rag jobs? Cities with the most Rag job openings:
What are the most commonly searched types of Rag jobs? The most popular types of Rag jobs are:
What states have the most Rag jobs? States with the most job openings for Rag jobs include:
What job categories do people searching Rag jobs look for? The top searched job categories for Rag jobs are:
Rag jobs near you
Infographic showing various Rag job openings in the United States as of July 2026, with employment types broken down into 72% Full Time, 9% Part Time, 2% Temporary, and 17% Contract. Highlights an 85% In-person, and 15% Remote job distribution, with an average salary of $78,753 per year, or $37.9 per hour.
Generative AI Applications Engineer (Agents & RAG)

Generative AI Applications Engineer (Agents & RAG)

Accenture Federal Services

Seattle, WA • On-site

Full-time

Re-posted 11 days ago

Accenture Federal Services rating

8.4

Company rating: 8.4 out of 10

Based on 19 frontline employees who took The Breakroom Quiz

50th of 449 rated business services

Job description

Job Summary:
Accenture Federal Services is dedicated to enhancing the capabilities of the US federal government through technology and innovation. The Generative AI Applications Engineer will be responsible for developing secure and scalable GenAI applications, focusing on agentic workflows and RAG systems for various federal missions.
Responsibilities:
• Design & ship mission grade GenAI: Build agentic workflows and RAG systems tailored to mission data and environments; target low hallucination, tight p95 latency, and predictable cost.
• Agent frameworks & orchestration: Apply patterns from LangChain/LlamaIndex/Semantic Kernel; design task decomposition, tool use, guardrails, and recovery/fallback strategies.
• Platform integration (no model training): Implement with AWS Bedrock, Azure OpenAI, Google Vertex AI, Amazon Kendra, and managed services (e.g., Document AI, Gemini, Gemma).
• LLM selection & evaluation: Compare models for quality, safety, latency, cost; author/test prompts & policies; deploy with observability and safe rollback/fallback.
• RAG done right: Build retrieval pipelines & vector search (Pinecone, Weaviate, OpenSearch, pgvector, FAISS/Chroma); handle data prep, chunking, metadata, and IRstyle evals (e.g., NDCG) to maximize signal to noise.
• Production rigor: Instrument metrics/logs/traces; run A/B experiments; maintain incident playbooks; and implement safety & compliance guardrails.
• SRE & FinOps for AI: Define SLIs/SLOs (quality/latency/safety/cost), run on call and postmortems, reduce MTTR; meter usage and optimize token/spend.
• Reusable platform components: Ship SDKs, CI/CD templates, Terraform/IaC modules, evaluation harnesses that accelerate multiple mission team not one-off projects.
• Operate in real world constraints: Deliver into hybrid, restricted, or air gapped environments with Zero Trust principles and audit ready controls.
Qualifications:
Required:
• End-to-end ownership of production systems: integration → deployment → observability → incident response.
• Hands-on experience with LLMs, transformer based apps, and RAG in production.
• Strong Python
• Experience with vector search and retrieval (Pinecone, Weaviate, OpenSearch, pgvector, FAISS/Chroma) and grounding AI in enterprise/mission data.
• U.S. Citizenship
Preferred:
• Integration with leading cloud AI services or on prem inference stacks
• Background in LLM evaluation, prompt authoring/testing, A/B experimentation, and LLM Ops.
• Responsible AI expertise (privacy, security, bias, transparency, human in the loop) and data governance.
• Experience implementing tool using agents for API integration and external data access.
• Containerization & orchestration (Docker, Kubernetes, VMware) and scripting/automation (Linux Bash, PowerShell).
• Prior work in regulated/secure environments (e.g., ATO, STIGs, Zero Trust) with fast shipping.
• Familiarity with NVIDIA AI Foundations, OpenAI ChatGPT, and AI assisted dev tools (Cursor, Windsurf, Claude).
• Contributions to internal frameworks or opensource; mentorship of engineers.
• Clear communication with engineers, PMs, and security/compliance stakeholders.
Company:
Accenture Federal Services is a leading US federal services company and subsidiary of Accenture. Founded in 1989, the company is headquartered in Arlington, USA, with a team of 10001+ employees. The company is currently Late Stage.

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