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Generative Ai Testing Jobs in California (NOW HIRING)

Redolent, Inc.

AI Engineer with Java background

Sunnyvale, CA · On-site

$61.75 - $84.50/hr

Design, develop, and deploy AI-powered applications and solutions using modern LLMs and Generative ... Participate in architecture discussions, code reviews, testing, deployment, and ongoing support ...

Avathon

Senior AI Engineer

Pleasanton, CA · On-site

$116K - $159K/yr

Responsibilities : • Design, develop, and deploy machine learning and Generative AI solutions to ... testing • Practical experience deploying LLM applications with guardrails, prompt versioning ...

Vivodyne

AI Senior Scientist

San Francisco, CA · Hybrid

Domain & Technical Growth - Remain current with the latest research trends in Generative AI ... with continuous testing and governance compliance. * Resource Optimization - Apply financial ...

Vivodyne

AI Senior Scientist

San Francisco, CA · On-site

We accelerate the successful discovery, design, and development of human therapeutics by testing on ... Domain & Technical Growth - Remain current with the latest research trends in Generative AI ...

Avathon

Senior AI Engineer

Pleasanton, CA

$116K - $159K/yr

You Will * Design, develop, and deploy machine learning and Generative AI solutions to solve ... testing * Practical experience deploying LLM applications with guardrails, prompt versioning ...

Avathon

Senior AI Engineer

Pleasanton, CA · On-site

$116K - $159K/yr

You Will * Design, develop, and deploy machine learning and Generative AI solutions to solve ... testing * Practical experience deploying LLM applications with guardrails, prompt versioning ...

REDICA Systems

AI Engineer

Pleasanton, CA · On-site

Contribute to testing, monitoring, and performance optimization of AI services. * Assist in ... Strong experience in building and deploying LLM and Generative AI applications at scale * Extensive ...

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Generative Ai Testing information

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 are popular job titles related to Generative Ai Testing jobs in California? For Generative Ai Testing jobs in California, the most frequently searched job titles are:
What job categories do people searching Generative Ai Testing jobs in California look for? The top searched job categories for Generative Ai Testing jobs in California are:
What cities in California are hiring for Generative Ai Testing jobs? Cities in California with the most Generative Ai Testing job openings:
Generative Ai Testing jobs near you
Infographic showing various Generative Ai Testing job openings in California as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 19% Part Time, 2% Temporary, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

AI Engineer with Java background

Redolent, Inc.

Sunnyvale, CA • On-site

$61.75 - $84.50/hr

Contractor

Re-posted 6 days ago

Job description

Job Title: AI Engineer (Java Background)
Location: Sunnyvale, CA (Hybrid)
Employment Type: Full-Time (FTE)
Position Overview
We are seeking a highly motivated AI Engineer with a strong software engineering foundation in Java and hands-on experience with Generative AI, Large Language Models (LLMs), and AI-powered development tools.
This role is ideal for an engineer who enjoys leveraging AI to solve complex business problems, automate engineering workflows, and improve developer productivity.
The successful candidate will work across multiple technologies and disciplines, developing AI-driven applications, integrating LLMs into enterprise systems, and building tools that enhance software development efficiency.
While Java will be the primary development language, the role requires versatility across modern technologies including Python, JavaScript, and front-end frameworks.
Key Responsibilities
  • Design, develop, and deploy AI-powered applications and solutions using modern LLMs and Generative AI technologies.
  • Build, customize, and enhance AI tools, agents, and workflows to improve engineering productivity and operational efficiency.
  • Integrate AI capabilities into enterprise applications and software development processes.
  • Develop and maintain scalable backend services primarily using Java.
  • Utilize AI-assisted development tools (such as GitHub Copilot, Cursor, Claude, ChatGPT, or similar platforms) to accelerate software development and innovation.
  • Evaluate emerging AI technologies, frameworks, and models and recommend their adoption where appropriate.
  • Collaborate with product managers, architects, and engineering teams to identify opportunities for AI-driven automation and optimization.
  • Create proof-of-concepts, prototypes, and production-ready AI solutions.
  • Participate in architecture discussions, code reviews, testing, deployment, and ongoing support activities.
  • Develop solutions across multiple technology stacks, including backend, frontend, APIs, automation, and AI frameworks.
Required Qualifications
  • Bachelor's degree in Computer Science, Software Engineering, or a related technical field.
  • 5+ years of professional software development experience.
  • 2+ years of hands-on experience working with Generative AI, Large Language Models (LLMs), AI agents, or AI-powered applications.
  • Strong proficiency in Java and object-oriented software development.
  • Experience leveraging AI coding assistants and AI development platforms to design, develop, test, and deploy software solutions.
  • Ability to use AI technologies to perform a wide range of engineering tasks, including coding, testing, debugging, documentation, automation, and system design.
  • Experience with one or more additional programming languages such as Python, JavaScript, TypeScript, or similar.
  • Strong problem-solving skills and ability to rapidly learn and adapt to emerging AI technologies.
  • Experience developing REST APIs, microservices, and cloud-based applications.
Preferred Qualifications
  • Experience with OpenAI, Anthropic, Gemini, Llama, or other foundation models.
  • Experience with AI frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or similar.
  • Experience building AI agents, Retrieval-Augmented Generation (RAG) solutions, vector databases, and prompt engineering workflows.
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.
  • Experience with modern frontend frameworks such as React, Angular, or Vue.js.
  • Knowledge of MLOps, model deployment, and AI governance best practices.
What We're Looking For
  • A software engineer who uses AI as a force multiplier.
  • Someone passionate about applying AI to real-world engineering challenges.
  • A hands-on builder who can rapidly prototype, evaluate, and deploy AI-driven solutions.
  • An individual who stays current with the rapidly evolving AI ecosystem and enjoys experimenting with new tools and technologies.

Keywords: Java, AI Engineer, Generative AI, LLM, OpenAI, Claude, Gemini, LangChain, AI Agents, RAG, Python, JavaScript, Cloud, Automation, Developer Productivity, Enterprise AI.
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About Redolent

Sourced by ZipRecruiter

Redolent, a dynamic and rapidly expanding company committed to excellence in software solutions, where success is fueled by a combination of technical expertise and efficient management practices. Our solutions create a measurable delta in our clients’ productivity and profitability, contributing to their growth and success.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

San Jose, CA, US

Year founded

2008

Social media

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