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Remote Rag Jobs in Oakley, CA (NOW HIRING)

TriNet

Software Engineer

Dublin, CA · On-site +1

$89K - $168K/yr

RAG (Retrieval-Augmented Generation) * Generative AI technologies * AI agent development Additional ... remote hire at the company's discretion. The candidate's final salary offer will be based on the ...

TriNet

Software Engineer

Dublin, CA · On-site +1

$89K - $168K/yr

RAG (Retrieval-Augmented Generation) * Generative AI technologies * AI agent development Additional ... remote hire at the company's discretion. The candidate's final salary offer will be based on the ...

All JobsRag JobsRemote Rag JobsRemote Rag Jobs in Oakley, CA

Remote Rag information

See Oakley, CA salary details

$18

$23

$25

How much do remote rag jobs pay per hour?

As of Jul 26, 2026, the average hourly pay for remote rag in Oakley, CA is $23.32, according to ZipRecruiter salary data. Most workers in this role earn between $19.57 and $24.76 per hour, depending on experience, location, and employer.

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

I'm sorry, but 'Remote Rag' does not appear to be a recognized professional occupation. Please provide a valid job title.

What is a Remote RAG (Retrieval-Augmented Generation) specialist?

A Remote RAG specialist is a professional who works with Retrieval-Augmented Generation (RAG) systems, typically in the field of artificial intelligence and machine learning. RAG combines traditional information retrieval techniques with generative models like large language models to provide more accurate and contextually relevant answers to user queries. Remote RAG specialists often build, fine-tune, and maintain these systems while working from a remote location. They may also work on integrating RAG models into applications, improving retrieval accuracy, and customizing outputs based on user needs.

What are some common challenges faced by professionals working in a remote RAG (Responsible AI Governance) role?

Professionals in remote RAG roles often encounter challenges related to cross-functional collaboration and maintaining clear communication, especially when working across different time zones. Ensuring alignment on ethical AI standards and compliance requirements can be complex, as it typically involves coordinating with data scientists, legal teams, and business stakeholders. Staying current with evolving regulatory frameworks and best practices in AI governance is also essential, demanding continuous learning and adaptability. Building trust and rapport within a remote team can require extra effort, but leveraging digital collaboration tools and regular check-ins can help mitigate these challenges.
What job categories do people searching Remote Rag jobs in Oakley, CA look for? The top searched job categories for Remote Rag jobs in Oakley, CA are:
What cities near Oakley, CA are hiring for Remote Rag jobs? Cities near Oakley, CA with the most Remote Rag job openings:
Remote Rag jobs near you
Gen AI Architect

Gen AI Architect

Noblesoft Technologies

Pleasanton, CA • Remote

Contractor

Posted 8 days ago

Job description

Job Title: Gen AI Architect
Location: Pleasanton , California (Remote)
 
JD: We are seeking an experienced Generative AI Architect to lead the design, development, and deployment of cutting-edge generative AI systems. The ideal candidate will combine deep technical knowledge of AI/ML (particularly large language models and diffusion models) with strong architecture and leadership skills. You will play a critical role in shaping our AI strategy and enabling innovative products powered by generative technologies.
 
Key Responsibilities:
  • Architect and design end-to-end generative AI solutions (text, image, audio, or multimodal) that align with business objectives.
  • Evaluate and select appropriate foundation models (e.g., GPT, LLaMA, Stable Diffusion) and fine-tuning strategies.
  • Lead the development of custom LLM applications, including prompt engineering, fine-tuning, RLHF, and model compression.
  • Collaborate with cross-functional teams (engineering, product, design, data science) to integrate AI into products and platforms.
  • Ensure responsible and ethical AI practices are embedded in system design (e.g., fairness, privacy, explainability).
  • Guide the implementation of AI infrastructure (data pipelines, vector databases, model serving, APIs).
  • Stay up-to-date on the latest AI research and tools, and make recommendations for adoption.
  • Conduct proofs-of-concept, prototypes, and performance benchmarking.
  • Mentor junior engineers and contribute to best practices and internal knowledge sharing.
 
 
Required Qualifications:
  • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning
  • 7+ years of experience in AI/ML, with 3+ years in generative AI (LLMs, diffusion models, etc.).
  • Proven experience designing and deploying large-scale AI systems.
  • Deep understanding of transformer architectures, tokenization, and pretraining/fine-tuning paradigms.
  • Hands-on experience with AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, etc.
  • Strong knowledge of MLOps, cloud platforms (AWS, GCP, Azure), and scalable architectures (e.g., microservices, serverless).
  • Experience with vector databases (e.g., Pinecone, Weaviate, FAISS) and retrieval-augmented generation (RAG) systems.
  • Familiarity with responsible AI frameworks and privacy-preserving techniques.
 
 
Preferred Qualifications:
  • Experience with open-source LLMs and model distillation/quantization techniques.
  • Exposure to multimodal AI models (e.g., CLIP, DALL·E, Imagen).
  • Contributions to AI/ML research (e.g., published papers, open-source projects).
  • Experience building GenAI copilots, chatbots, or productivity tools.
 
 
Soft Skills:
  • Strong problem-solving and analytical skills.
  • Excellent communication and stakeholder management abilities.
  • Ability to translate complex AI concepts into business value.
  • Entrepreneurial mindset and passion for innovation