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Generative Ai Testing Jobs in San Rafael, CA (NOW HIRING)

Our latest advancements in generative AI are used by thousands of radiologists daily, supporting ... Own release coordination , covering QA, testing sign-off, and stakeholder readiness before each ...

Understanding of A/B testing and human-in-the-loop system design for model evaluation in production ... generative AI . Your work will directly shape how people connect, communicate, and build ...

AI Auditor, Principal

Oakland, CA · On-site

$137K - $206K/yr

... of generative AI tools * Lead cross-functional fact-finding and root-cause reviews involving ... Develop risk-based audit plans, control matrices, testing procedures, investigative workplans, and ...

Senior Software and AI Engineer

San Francisco, CA · On-site

$144K - $190K/yr

... to accelerate development, testing, and documentation • Ensure robust observability ... with Generative AI frameworks (LangChain, LangGraph, ChatGPT API, or Glean API) and experience ...

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Generative Ai Testing information

See San Rafael, CA salary details

$35

$59

$85

How much do generative ai testing jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for generative ai testing in San Rafael, CA is $59.89, according to ZipRecruiter salary data. Most workers in this role earn between $49.33 and $68.61 per hour, depending on experience, location, and employer.

What is the difference between Generative Ai Testing vs Data Scientist?

AspectGenerative Ai TestingData Scientist
Required CredentialsKnowledge of AI models, testing tools, programming skillsStatistics, programming, data analysis certifications
Work EnvironmentAI development teams, testing labs, tech companiesResearch labs, tech firms, finance, healthcare
Employer & Industry UsageAI product testing, quality assurance in techData analysis, predictive modeling across industries

Generative Ai Testing focuses on evaluating and validating AI-generated content and models, ensuring quality and accuracy. Data Scientists analyze data, build models, and derive insights. While both roles require programming and AI knowledge, Generative Ai Testing emphasizes testing processes, whereas Data Scientists focus on data analysis and model development.

How do I become a Generative AI Testing?

To become a Generative AI Tester, develop skills in machine learning, natural language processing, and programming languages like Python. Gain experience with AI frameworks such as TensorFlow or PyTorch and understand data quality and model evaluation techniques. Certifications in AI or data science can enhance your qualifications and improve job prospects.

Is Generative AI Testing a good career?

Generative AI Testing is a growing field within AI development that involves evaluating the quality and safety of AI-generated content. It requires skills in machine learning, programming, and understanding AI models, making it a promising career path with increasing demand as AI technologies expand. Professionals in this area can find opportunities in tech companies, research labs, and startups focused on AI innovation.

What are the key skills and qualifications needed to thrive as a generative AI testing specialist, and why are they important?

To thrive as a Generative AI Testing Specialist, you need a robust understanding of machine learning principles, model evaluation techniques, and a background in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and model evaluation frameworks, as well as experience with automated testing platforms, is typically required. Analytical thinking, attention to detail, and strong communication skills help you identify model weaknesses and collaborate effectively with development teams. These skills are crucial to ensure the reliability, safety, and ethical deployment of generative AI solutions.

What are some common challenges faced when testing generative AI models, and how can I prepare to address them in this role?

Testing generative AI models often involves unique challenges such as evaluating the quality and relevance of generated content, detecting bias or inappropriate outputs, and ensuring model consistency across various prompts. You may work closely with data scientists and engineers to create robust evaluation frameworks and develop automated as well as manual testing strategies. Familiarity with prompt engineering, statistical evaluation techniques, and domain-specific knowledge will help you address these challenges effectively. Proactively staying updated on industry best practices and collaborating with cross-functional teams are key to success in this dynamic field.

What is generative AI testing?

Generative AI Testing refers to the process of evaluating and validating AI systems, particularly those that generate content such as text, images, or code. This type of testing focuses on assessing the accuracy, reliability, fairness, and safety of generative models to ensure they function as intended and avoid producing harmful or biased outputs. Testers use various methods, including automated and manual techniques, to check for issues like hallucinations, inappropriate content, or security vulnerabilities. The goal is to build trust in generative AI systems and ensure they meet quality and ethical standards before deployment.
What job categories do people searching Generative Ai Testing jobs in San Rafael, CA look for? The top searched job categories for Generative Ai Testing jobs in San Rafael, CA are:
What cities near San Rafael, CA are hiring for Generative Ai Testing jobs? Cities near San Rafael, CA with the most Generative Ai Testing job openings:
Infographic showing various Generative Ai Testing job openings in San Rafael, CA as of June 2026, with employment types broken down into 91% Full Time, 5% Part Time, and 4% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $124,569 per year, or $59.9 per hour.

Lead Engineer - AI Trust & Governance

Salesforce, Inc.

San Francisco, CA • On-site

$172.50 - $260.10/hr

Other

Medical, Dental, Vision, Life, Retirement

Re-posted 14 days ago


Salesforce rating

8.1

Company rating: 8.1 out of 10

Based on 58 frontline employees who took The Breakroom Quiz

112th of 242 rated software companies


Job description

## Lead Engineer - AI Trust & GovernanceApplyremote type: Office Tech-Flexiblelocations: California - San Francisco: California - Palo Alto: Illinois - Chicago: New York - New York: Washington - Seattletime type: Full timeposted on: Posted Todayjob requisition id: JR344097*To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.*Job CategorySoftware EngineeringJob Details****About Salesforce****Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.We are seeking a highly skilled, hands-on, and deeply technical Software Development Engineers to help build our AI Governance platform from the ground up. This is a critical senior role responsible for designing and developing both the front-end and back-end foundations of a platform that enables safe, trusted, and scalable AI deployment across the enterprise.This role will directly support our number one value: TrustYou will help architect and deliver a platform that spans governance, intake workflows, lifecycle management, monitoring, observability, risk controls, and operational tooling for AI systems and agents. We are looking for a builder who is comfortable wearing multiple hats across software engineering, cloud infrastructure, platform engineering, developer tooling, and user experience. You should be energized by ambiguity, excited to build systems from scratch, and motivated by solving difficult problems at the intersection of AI, governance, trust, observability, and enterprise scale.What You’ll Do* Key Responsibilities:* Full Stack Platform Development: Lead the end-to-end design, development, and scaling of the AI governance platform, building both the front-end and back-end components that support enterprise wide AI governance* AI-Assisted Engineering: Use AI development tools such as Claude and other coding assistants as part of the software development lifecycle to accelerate delivery, improve code quality, prototype faster, and enhance engineering productivity* AWS Cloud Infrastructure Development: Design and build secure, scalable, and resilient cloud native infrastructure on AWS to support platform services, governance workflows, system integrations, and application performance at enterprise scale* ML and AI Platform Services: Build and support platform capabilities that enable AI and machine learning systems to be governed, monitored, tracked, and managed throughout their lifecycle, including services that support model and agent operations* CI/CD Delivery Process Knowledge: Bring practical knowledge of CI/CD concepts, automated testing, and deployment workflows, and release management practices to help ensure the platform can be delivered reliably across environments* Architecture and Technical Design: Define and drive the overall platform architecture, including service design, API strategy, data flows, integration patterns, event-driven workflows, and system scalability considerations* Monitoring and Operational Visibility: Develop monitoring capabilities that provide insight into system health, application performance, workflow execution, service reliability, and platform usage across the governance ecosystem* Observability and Telemetry: Build observability components that capture logs, metrics, traces, and runtime telemetry across platform services, enabling deeper diagnostics, issue detection, root cause analysis, and ongoing operational intelligence* Generative AI Platform Development: Assist with designing and developing Generative AI capabilities as part of the platform, including LLM powered features, intelligent workflows, agent-based functionality, and other AI native applications* Technical Leadership and Ownership: Provide strong technical leadership across the stack, establish engineering standards, influence design decisions, mentor other engineers, and take ownership of delivering a strategic platform from the ground up* Cross Functional Collaboration: Partner closely with product, architecture, security, compliance, governance, and engineering stakeholders to translate business goals and trust requirements into scalable technical solutionsWhat We’re Looking For* 10+ years of professional software development experience with significant depth across both front-end and back-end development* Strong hands-on expertise in full stack development, including modern front-end frameworks, API design, distributed systems, and back-end application development.* Proven experience building complex platforms or enterprise applications from scratch* Deep experience with AWS and cloud-native architecture, including designing scalable, secure, and production grade systems.* Strong experience with platform engineering, developer infrastructure, and production software delivery practices* Demonstrated ability to build and scale CI/CD pipelines, automated frameworks, and deployment workflows* Experience building systems with strong monitoring, observability, logging, telemetry, and operational insight capabilities* Strong architectural judgment* Experience working in environments where security, compliance, governance, and auditability are important design considerations* Comfort working across ambiguity and leading technical execution in highly visible, high-impact initiatives* Excellent collaboration and communication skills* Demonstrated experience using Generative AI as part of the software development lifecyclePreferred Qualifications (Bonus Points):* Experience with Salesforce Ecosystem* Experience building or supporting AI governance, model governance, risk, trust, compliance, or observability platforms* Experience with Gen AI applications, LLM-powered systems, agentic workflows, and model evaluation frameworks.* Experience with MLOps, LLMOps, or AI platform engineering, including model lifecycle tolling and development controls* Familiarity with data privacy, model risk, or regulatory considerations in enterprise AI environments* Experience in regulated or trust sensitive industries where system reliability, governance, and control are critical* Experience designing systems for auditability, lineage, traceability, and evidence managementUnleash Your PotentialWhen you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and *be your best*, and our AI agents accelerate your impact so you can *do your best*. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.AccommodationsIf you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form.Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates’ resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.Posting StatementSalesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.### ### ### ### At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions.The typical base salary range for this position is $172,500 - $260,100 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $207,800 - $285,500 annually. #J-18808-Ljbffr

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