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Ai Rag Jobs in Modesto, CA (NOW HIRING)

Calance

GCP Architect or Engineer - Fully Remote

Modesto, CA · On-site

$67.75 - $86.25/hr

Vertex AI / Gemini (Agent Engine, RAG Engine, Vector Search, Model Armor, Model Garden); Cloud Run; Prisma Cloud (CSPM); CI/CD policy-as-code (OPA/Conftest, Checkov, tfsec); and Network Connectivity ...

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Ai Rag information

See Modesto, CA salary details

$33.8K

$61.4K

$88.1K

How much do ai rag jobs pay per year?

As of Aug 28, 2026, the average yearly pay for ai rag in Modesto, CA is $61,449.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,700.00 and $68,600.00 per year, depending on experience, location, and employer.

What is an AI RAG?

AI RAGs, or Retrieval-Augmented Generation systems, are a type of artificial intelligence that combines the power of retrieving information from large databases or documents with generating human-like text responses. This approach allows AI models to provide more accurate, up-to-date, and contextually relevant answers by referencing external data sources during the generation process. RAGs are commonly used in applications like chatbots, search engines, and customer support systems, where comprehensive and factual responses are important.

What are the key skills and qualifications needed to thrive as an AI researcher?

To thrive as an AI Researcher, you need a strong background in computer science, mathematics, and machine learning, usually with an advanced degree such as a Master's or Ph.D. Proficiency with programming languages like Python, deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with scientific research tools is essential. Critical thinking, creativity, and effective collaboration are vital soft skills for generating novel ideas and working in multidisciplinary teams. These skills and qualities are crucial to drive innovation and solve complex problems in the rapidly evolving field of artificial intelligence.

What are common challenges faced by AI RAG engineers when integrating retrieval systems with large language models?

AI RAG engineers often encounter challenges such as ensuring seamless integration between retrieval systems and language models, maintaining low latency for real-time responses, and handling the quality and relevance of retrieved data. Additionally, tuning the system to balance retrieval accuracy with generative fluency can be complex, especially when dealing with large or unstructured datasets. Collaboration with data engineers, ML researchers, and product teams is essential to address these challenges and optimize system performance.

What is the difference between Ai Rag vs Data Analyst?

AspectAi RagData Analyst
Required CredentialsTypically a diploma or certification in AI, machine learning, or related fieldsBachelor's degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and various industries
Employer & Industry UsagePrimarily in AI development and researchAcross industries for data interpretation and decision-making
Common Search & ComparisonYesYes

Ai Rag and Data Analyst roles share overlapping skills in data handling and analysis, but Ai Rag focuses more on AI-specific applications and machine learning, while Data Analysts concentrate on interpreting data to inform business decisions. Both roles are vital in data-driven industries, with Ai Rag often working in AI development environments and Data Analysts supporting strategic insights across sectors.

What job categories do people searching Ai Rag jobs in Modesto, CA look for?

The top searched job categories for Ai Rag jobs in Modesto, CA are:

What cities near Modesto, CA are hiring for Ai Rag jobs?

Cities near Modesto, CA with the most Ai Rag job openings:

Ai Rag jobs near you
Infographic showing various Ai Rag job openings in Modesto, CA as of August 2026, with employment types broken down into 70% Full Time, 28% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $61,449 per year, or $29.5 per hour.

GCP Architect or Engineer - Fully Remote

Calance

Modesto, CA • On-site

$67.75 - $86.25/hr

Other

Posted 8 days ago

Job description

Role GCP Enterprise Architect (Platform Automation Architect, GCP)


Practice Trace3 — Cloud Solutions Group, Digital · Google Cloud Practice


Workstream Product Teams Support


Location Remote (U.S.)


Reports To Trace3 Google Cloud Practice / Engagement leadership

43647

Role Overview

Serves as the dedicated enterprise architect for Gap's Google Cloud program, evaluating incoming use cases holistically and defining the most appropriate end-to-end solution design across security, networking, and infrastructure automation. This Trace3-led role translates business and technical requirements into scalable, secure, and supportable cloud automation patterns; produces documented, repeatable architecture artifacts; and coordinates required changes across dependent teams to completion. The architect strengthens the overall solution-design process, improves cross-functional alignment, and accelerates delivery of Gap's cloud initiatives.

Key Responsibilities

• Evaluate incoming use cases holistically and define end-to-end solution designs spanning security, networking, and infrastructure automation.

• Translate business and technical requirements into scalable, secure, and supportable cloud automation patterns.

• Produce documented, repeatable architecture artifacts and reference designs that delivery teams can operationalize.

• Partner across Gap's InfoSec, Network, and Infrastructure Automation teams to ensure designs align across all foundational pillars and can be operationalized effectively.

• Coordinate required changes across dependent teams and drive them to completion.

• Provide architectural direction across the program's technical domains — network security architecture, foundational GCP organization and IAM, cloud security posture management, Terraform/IaC structure, and the Gemini Enterprise Agent (Vertex AI) platform.

• Guide persona-based least-privilege IAM design, organization policy, VPC Service Controls, Private Service Connect, and CMEK/encryption standards.

• Establish Terraform architecture standards — separation of global/shared policy from perimeter-specific implementation, shared-module strategy, drift detection, and CI/CD policy-as-code gating.

• Provide architectural guidance to the NCC network transition and hybrid-connectivity direction (including Cross-Cloud Interconnect to Azure) where it intersects platform automation.

• Support project governance — participate in design reviews, secure architecture sign-off, and maintain alignment to timelines and scope.

Primary Deliverables

• Architecture designs and supporting documentation for approved use cases.

• Reusable reference solution patterns spanning security, networking, and infrastructure automation.

• Persona-based IAM / least-privilege role design and foundation policy recommendations.

• Terraform repository and structure design guidance (global vs. shared policy separation, module strategy, drift detection, IaC security scanning).

• Design artifacts for the Gemini Enterprise Agent Platform (Agent Engine, RAG Engine, Vector Search), including governance and threat-model considerations.

Required Qualifications

• Extensive enterprise / cloud architecture experience with deep, hands-on Google Cloud Platform expertise.

• Demonstrated ability to own end-to-end solution design across security, networking, and infrastructure automation.

• Expert-level Terraform / Infrastructure-as-Code design and standards.

• Strong command of GCP foundations: resource hierarchy and organization policy, IAM and least-privilege design, Shared VPC, VPC Service Controls, Private Service Connect, and CMEK.

• Experience embedding security and compliance into cloud designs (e.g., PII/PCI-regulated workloads) and cloud security posture management.

• Proven cross-functional leadership — aligning InfoSec, Network, and Infrastructure/Platform teams and driving change to completion.

• Excellent documentation, communication, and stakeholder-management skills.

Preferred Qualifications

• Google Cloud Professional certifications (Cloud Architect, Cloud Security Engineer, and/or Cloud Network Engineer).

• Vertex AI / generative-AI platform architecture — Agent Engine, RAG Engine, Vector Search, Model Armor, and Model Garden governance.

• CI/CD policy-as-code tooling (OPA/Conftest, Checkov, tfsec) and layered Terraform pipelines.

• Cloud security posture management with Prisma Cloud.

• Network Connectivity Center (NCC), hub-and-spoke fabric, and hybrid connectivity including Cross-Cloud Interconnect to Azure.

• Experience in large, regulated, enterprise-scale (e.g., retail) environments.

Core Technology Environment

Google Cloud Platform; Terraform / Infrastructure-as-Code; IAM, organization policy, Shared VPC, VPC Service Controls, Private Service Connect, and CMEK; Vertex AI / Gemini (Agent Engine, RAG Engine, Vector Search, Model Armor, Model Garden); Cloud Run; Prisma Cloud (CSPM); CI/CD policy-as-code (OPA/Conftest, Checkov, tfsec); and Network Connectivity Center with Cross-Cloud Interconnect to Azure.


Engagement Details & Working Arrangement

• Delivery model: Dedicated Trace3 consulting resource embedded with Gap's GCP program, supporting the Product Teams Support workstream alongside the broader GCP Architecture Support and NCC Transition projects.

• Location: Remote (U.S.). All work performed remotely via secure VPN/collaboration tooling.

• Hours: Normal business hours (8:00 AM – 5:00 PM client local time); occasional off-hours work by mutual agreement to support change windows.

• Security & compliance: Trace3-managed device, hard-drive encryption, two-factor authentication, and adherence to the client's remote-work protocols and information-security standards.

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