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Ai Audit Jobs in Riverside, CA (NOW HIRING)

Develop and maintain the AI Use Case Inventory and AI Tool Catalog; assign tracking IDs, manage lifecycle status, and ensure audit readiness. * Set and communicate risk tier classifications in ...

Sr AI/Agentic Engineer

Tustin, CA · On-site

$115K - $158K/yr

... and audit trails. • Hands-on experience with fine-tuning and adaptation -- LoRA, QLoRA ... AI capabilities as reliable internal APIs with clear contracts, error handling, and cost controls ...

Embed compliance by design: 21 CFR Part 11, Annex 11, ALCOA+, data retention/archival, audit trails ... Govern AI safety: model cards, redteam testing, bias/fairness checks, PHI/PII safeguards, vendor ...

Embed compliance by design: 21 CFR Part 11, Annex 11, ALCOA+, data retention/archival, audit trails ... Govern AI safety: model cards, redteam testing, bias/fairness checks, PHI/PII safeguards, vendor ...

Director Data AI & Analytics

Irvine, CA · On-site

$154.57 - $216.10/hr

Embed compliance by design: 21 CFR Part 11, Annex 11, ALCOA+, data retention/archival, audit trails ... Govern AI safety: model cards, red-team testing, bias/fairness checks, PHI/PII safeguards, vendor ...

Embed compliance by design: 21 CFR Part 11, Annex 11, ALCOA+, data retention/archival, audit trails ... Govern AI safety: model cards, red-team testing, bias/fairness checks, PHI/PII safeguards, vendor ...

Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit ... The Opportunity As part of the People Tech & AI team you will lead the design, build, and operation ...

CTIO AI Engineering Manager

Irvine, CA · On-site

$73K - $244K/yr

Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit ... Responsibilities - Work with cross-functional teams to incorporate AI into various applications ...

AI Solutions Engineering Delivery Lead

Irvine, CA · On-site

$110K - $144K/yr

Adhere to and enforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance) the Firm's code of conduct, and independence requirements. The Opportunity : The AI ...

ERP AI Engineer - Manager

Irvine, CA · On-site

$99K - $232K/yr

Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit ... This role offers the chance to shape AI solution architecture while driving innovation and ...

Showing results 21-40

Ai Audit information

See Riverside, CA salary details

$63.6K

$125.4K

$164.3K

How much do ai audit jobs pay per year?

As of Aug 13, 2026, the average yearly pay for ai audit in Riverside, CA is $125,438.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,500.00 and $142,400.00 per year, depending on experience, location, and employer.

How do you become an AI auditor?

To become an AI auditor, individuals typically need a background in data science, machine learning, or computer science, along with knowledge of AI ethics and compliance standards. Gaining experience with AI systems, programming skills in languages like Python, and certifications in AI or data auditing can enhance qualifications for this role.

What are the key skills and qualifications needed to thrive as an AI auditor, and why are they important?

To thrive as an AI Auditor, you need a strong background in data analysis, machine learning principles, compliance, and risk assessment, typically supported by a relevant degree in computer science, data science, or auditing. Familiarity with AI audit frameworks, automated testing tools, and certifications like Certified Information Systems Auditor (CISA) or Certified Ethical Hacker (CEH) is often required. Critical thinking, attention to detail, and clear communication are vital soft skills for identifying issues and explaining findings to both technical and non-technical stakeholders. These skills ensure AI systems are transparent, ethical, and compliant with regulations, minimizing risk and building trust.

What is an AI audit?

An AI audit is a systematic evaluation of artificial intelligence systems to ensure they operate as intended, comply with regulations, and uphold ethical standards. This process involves assessing data quality, algorithmic fairness, transparency, privacy, and potential biases in AI models. The goal is to identify risks, improve accountability, and build trust in AI technologies by making sure they are reliable and safe for users. Organizations often conduct AI audits to meet legal requirements and industry best practices.

What is the difference between Ai Audit vs Data Analyst?

AspectAi AuditData Analyst
Required CredentialsCertifications in AI, data analysis, and auditing toolsDegree in Data Science, Statistics, or related fields
Work EnvironmentCorporate, consulting firms, or tech companies focusing on AI systemsBusiness, finance, healthcare, or tech sectors analyzing data sets
Employer & Industry UsageUsed by organizations implementing AI to ensure compliance and accuracyUsed across industries to interpret data and support decision-making
Search & Comparison IntentUnderstanding AI auditing roles and responsibilitiesAnalyzing data trends and insights for business strategies

While both roles involve working with data, Ai Audits focus on evaluating AI systems for compliance, accuracy, and ethical considerations, often requiring specialized AI knowledge. Data Analysts interpret data to inform business decisions, with a broader scope across industries. The roles overlap in data skills but differ in focus and application.

What are the typical challenges faced by professionals in AI audit roles, and how can they be addressed?

AI Audit professionals often encounter challenges such as rapidly evolving technologies, ensuring transparency in complex AI systems, and assessing compliance with emerging regulations. Staying current with the latest advancements and maintaining a solid understanding of both technical and regulatory frameworks are crucial. Collaboration with data scientists, legal teams, and business units is essential to effectively audit AI models and mitigate risks. Regular training and leveraging industry best practices can help address these challenges and ensure thorough, up-to-date audits.

How much do AI auditors make?

AI auditors typically earn between $70,000 and $120,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in machine learning and data analysis can earn higher salaries, often exceeding $150,000. Compensation may also include benefits such as bonuses and professional development opportunities.

What are popular job titles related to Ai Audit jobs in Riverside, CA?

For Ai Audit jobs in Riverside, CA, the most frequently searched job titles are:

What job categories do people searching Ai Audit jobs in Riverside, CA look for?

The top searched job categories for Ai Audit jobs in Riverside, CA are:

What cities near Riverside, CA are hiring for Ai Audit jobs?

Cities near Riverside, CA with the most Ai Audit job openings:

Infographic showing various Ai Audit job openings in Riverside, CA as of August 2026, with employment types broken down into 75% Full Time, 20% Part Time, and 5% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $125,438 per year, or $60.3 per hour.

Principal Data Scientist - Gen AI & Agentic AI

Socket.dev

Diamond Bar, CA • On-site

$149 - $217.38/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

At Niagara, we’re looking for Team Members who want to be part of achieving our mission to provide our customers the highest quality most affordable bottled water.

  • Work in an entrepreneurial and dynamic environment with a chance to make an impact.
  • Develop lasting relationships with great people.
  • Have the opportunity to build a satisfying career.

We offer competitive compensation and benefits packages for our Team Members.
Principal Data Scientist – Gen AI & Agentic AI
The Principal Scientist leads other scientists and engineers on Research & Development (R&D) initiatives in materials, design, and process. Focuses on long‑term team and business growth. Strategizes, guides and performs innovative research. Interacts with other team members and teams to create new products and systems, improves line efficiency, quality, or enables other projects which add value to Niagara’s core business or aids in creating new business directions.

Essential Functions
  • Lead the strategy, design, and delivery of enterprise‑grade GenAI and agentic AI solutions, driving the development of next‑generation agents, LLM‑powered applications, and hybrid GenAI/ML systems that improve decision‑making, automation, and operational efficiency across Niagara’s business units.
  • Partner with senior business leaders, product management, and cross‑functional technology teams to translate ambiguous or complex business challenges into clear problem statements, measurable outcomes, and prioritized AI initiatives.
  • Architect robust agentic systems, including multi‑step orchestration, tool‑use agents, retrieval‑augmented workflows, grounding layers, and guardrail frameworks that ensure reliability, safety, and domain accuracy.
  • Design and implement scalable analytic and modeling approaches, including feature engineering, embedding strategies, retrieval pipelines, fine‑tuning, prompt engineering, supervised learning, and hybrid architectures combining classical ML with GenAI capabilities.
  • Develop, prototype, and operationalize LLM‑driven solutions using enterprise platforms such as Azure OpenAI, Databricks, Snowflake Cortex, Oracle AI Agent Studio, and containerized microservices.
  • Build reusable, interpretable, and production‑ready models, agents, and pipelines, ensuring they meet standards for scalability, observability, resilience, and maintainability.
  • Establish and own Niagara’s LLMOps and agent lifecycle practices, including CI/CD for models and agents, monitoring, evaluation frameworks, prompt testing, drift detection, and continuous improvement workflows.
  • Champion Responsible AI principles, embedding safety, fairness, explainability, privacy, security, grounding, and governance throughout the agent and model development lifecycle.
  • Define technical standards and best practices for GenAI development, including vector database usage, evaluation frameworks, embeddings, data preparation workflows, and content grounding strategies.
  • Collaborate with IT, data engineering, and platform teams to ensure required infrastructure—data access, compute environments, vector stores, APIs, and application integration layers is in place for scalable deployment.
  • Influence executive stakeholders by crafting compelling narratives, visualizations, and recommendations that communicate complex AI concepts in business‑relevant terms and drive strategic alignment.
  • Coach, mentor, and uplift the technical capabilities of data scientists and senior individual contributors, providing thought leadership, code reviews, architectural guidance, and development plans.
  • Drive innovation initiatives and proofs‑of‑concept, evaluating emerging GenAI frameworks, agent orchestration tools, evaluation stacks, retrieval technologies, and model families.
  • Contribute to enterprise AI governance, including model/agent documentation, risk assessments, access control, versioning, testing standards, and audit readiness.
  • Foster cross‑functional collaboration, identifying opportunities to leverage GenAI across manufacturing, supply chain, commercial operations, HR, legal, and corporate functions.
  • Represent DDI as a subject‑matter expert for GenAI and agentic AI, sharing insights, educating stakeholders, and building organizational readiness for advanced AI capabilities.
  • Analytics Product Expertise Strong knowledge of agile analytics product delivery, full‑stack development (Data Engineering, Data Science, UX/UI), and industry best practices.
  • Product & Project Management Skilled in developing Product Briefs, managing roadmaps, backlog prioritization, release planning, sprint metrics, and cross‑team coordination while ensuring business value‑driven outcomes.
  • Business & Process Understanding deep comprehension of business processes, functional digital capabilities (Supply Chain, Manufacturing, Finance, Sales & Marketing), and high‑quality analytics delivery.
  • Change & People Management skilled in managing change initiatives, fostering collaboration, and balancing competing priorities in a fast‑paced environment.
Qualifications
  • Minimum Qualifications:
  • 10+ years of experience in Data Science or Analytics, including 4+ years leading projects or technical teams.
  • Deep expertise in Machine Learning, Generative AI, Large Language Models (LLMs), Retrieval‑Augmented Generation (RAG), and agentic AI systems.
  • Demonstrated experience designing and delivering production AI systems using Azure and Databricks.
  • Strong storytelling, executive communication, and influence skills, with an ability to translate complex AI concepts into business outcomes.
  • experience may include a combination of work experience and education
  • Preferred Qualifications:
  • 12–15+ years of experience in Data Science, AI/ML engineering, or advanced analytics, including leading platform‑level or enterprise GenAI programs.
  • Experience working with agent orchestration frameworks, vector databases, evaluation stacks, and modern LLMOps tooling.
  • Experience with Oracle AI Agent Studio.
  • experience may include a combination of work experience and education
Competencies
  • Strategy & Technical Leadership – Ability to define enterprise AI strategy, set technical direction for GenAI and agentic AI programs, and guide long‑term architectural decisions.
  • Architecture & Delivery Excellence – Expertise in designing end‑to‑end agentic systems, retrieval pipelines, and LLM‑powered applications with strong standards for scalability, reliability, and security.
  • LLMOps & Governance – Deep understanding of model/agent lifecycle management, evaluation frameworks, monitoring, guardrails, Responsible AI principles, and enterprise governance processes.
  • Stakeholder Influence – Strong capability to communicate complex AI concepts to executive audiences, drive alignment across product and business teams, and influence cross‑functional decisions.
  • People Leadership – Demonstrated ability to coach and develop data scientists and senior ICs, elevate technical maturity, and foster a culture of innovation and high performance.
  • Advanced GenAI & Agentic System Design – Expertise in LLMs, RAG, embeddings, vector databases, agent frameworks, and multi‑step orchestration patterns.
  • AI Solution Delivery & Integration – Experience integrating models and agents into applications, microservices, or enterprise platforms (Azure, Databricks, Snowflake, Oracle AI Agent Studio).
  • Analytical & Systems Thinking – strong ability to break down ambiguous problems, synthesize complex information, and design solutions that balance technical depth with business impact.
  • Cross‑Functional Collaboration – Proven ability to work effectively with product, engineering, IT, operations, and business stakeholders to unlock enterprise‑wide value.
  • Executive Communication & Storytelling – Skilled at creating compelling narratives, visualizations, and recommendations that drive strategic decisions.
Education
  • Minimum Required:
  • Bachelor's Degree in Computer Science/Data Science/Statistics or other related field
  • Preferred:
  • Master’s Degree in Computer Science/Data Science/Statistics or other related field
Certification/License
  • Required: N/A
  • Preferred: Agentic AI / Gen AI / Machine Learning or Advanced Analytics certifications.
Typical Compensation Range

Pay Rate Type: Salary

$149,915.38 - $217,377.31 / Yearly

Bonus Target: 15% Annual

Benefits

Our Total Rewards package is thoughtfully designed to support both you and your family:

*Regular full-time team members are offered a comprehensive benefits package, while part-time, intern, and seasonal team members are offered a limited benefits package.*

  • Paid Time Off for holidays, sick time, and vacation time
  • Paid parental and caregiver leaves
  • Medical, including virtual care options
  • Dental
  • Vision
  • 401(k) with company match
  • Health Savings Account with company match
  • Flexible Spending Accounts
  • Expanded mental wellbeing benefits including free counseling sessions for all team members and household family members
  • Family Building Benefits including enhanced fertility benefits for IVF and fertility preservation plus adoption, surrogacy, and Doula reimbursements
  • Income protection including Life and AD&D, short and long‑term disability, critical illness and an accident plan
  • Special discount programs including pet plans, pre‑paid legal services, identity theft, car rental, airport parking, etc.
  • Tuition reimbursement, college savings plan and scholarship opportunities
  • And more!

https://careers.niagarawater.com/us/en/benefits

  • *Los Angeles County applicants only** Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers, the California Fair Chance Act, and any other applicable local and state laws.

Any employment agency, person or entity that submits a résumé into this career site or to a hiring manager does so with the understanding that the applicant's résumé will become the property of Niagara Bottling, LLC. Niagara Bottling, LLC will have the right to hire that applicant at its discretion without any fee owed to the submitting employment agency, person or entity.
Employment agencies that have fee agreements with Niagara Bottling, LLC and have been engaged on a search shall submit résumé to the designated Niagara Bottling, LLC recruiter or, upon authorization, submit résumé into this career site to be eligible for placement fees.
Niagara Plant Name
CORP-MAIN

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