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Google

Senior Software Engineer, Generative AI

Sunnyvale, CA · On-site

$143K - $188K/yr

They are seeking a Senior Software Engineer specializing in Generative AI to manage project priorities, deadlines, and deliverables while designing, developing, testing, and deploying software ...

Block

Senior Data Scientist, AI & Model Risk

New York, NY · On-site +1

Lead end-to-end AI Risk Assessments for generative AI and LLM use cases across the Bank; Embedding ... Assess pre-deployment testing for adequacy inclusive of output integrity, hallucination detection ...

New

Cotiviti

$32 - $40/hr

Conduct research on Agentic AI models and their potential impact on healthcare workflows and decision-making. * Assist in designing, developing, and testing autonomous AI agents and generative AI ...

Cotiviti

Intern - Generative AI/Agentic AI/Research

$32 - $40/hr

Conduct research on Agentic AI models and their potential impact on healthcare workflows and decision-making. * Assist in designing, developing, and testing autonomous AI agents and generative AI ...

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How much do generative ai testing jobs pay per hour?

As of Jun 5, 2026, the average hourly pay for generative ai testing in the United States is $53.73, according to ZipRecruiter salary data. Most workers in this role earn between $44.23 and $61.54 per hour, depending on experience, location, and employer.

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 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.

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Generative Ai Testing jobs near you
Infographic showing various Generative Ai Testing job openings in the United States as of May 2026, with employment types broken down into 12% Internship, 76% Full Time, 6% Part Time, and 6% Contract. Highlights an 53% In-person, 12% Hybrid, and 35% Remote job distribution, with an average salary of $111,750 per year, or $53.7 per hour.

Backend Engineer, Generative AI Services

OPPO US Research Center

Palo Alto, CA • On-site

Full-time

Posted 13 days ago

Job description

OPPO US Research Center is seeking a talented and experienced backend engineer to join our growing team. In this pivotal role, you will be responsible for designing, developing, and maintaining scalable and high-performance RESTful APIs that serve as the backbone for our generative AI-powered Android applications.

You will work primarily with platforms like Google Cloud or Azure to bring advanced AI capabilities directly to our users' mobile phones. This is a unique opportunity to build mission-critical services that will define how users interact with AI in a mobile platform, from concept to deployment.

Requirements

Core Development & Infrastructure

  • Design, develop, and maintain scalable RESTful APIs in Python to power generative AI features
  • Integrate backend services provided by the platform such as GCP Vertex AI or developed internally

Performance & Systems

  • Optimize API performance and scalability for global Android users
  • Contribute to architectural design of distributed systems (availability, fault tolerance)

Collaboration & Operations

  • Work closely with Android and ML teams on API contracts and model integration
  • Implement monitoring, logging, and security best practices for production systems

Quality & Innovation

  • Ensure code quality through testing (unit, integration, E2E) and documentation
  • Stay updated on generative AI and cloud technology trends

Qualifications:

  • Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
  • 3+ years of professional backend software development experience, with a focus on building and deploying RESTful APIs.
  • Proficiency in Python and one of the associated web frameworks (e.g., Flask, Django).
  • Demonstrable experience with at least one major cloud platform (AWS, Azure, or GCP)
  • Experience with relational (e.g., PostgreSQL, MySQL) and/or NoSQL databases (e.g., Firestore, MongoDB).
  • Solid understanding of microservices architecture, asynchronous processing, and event-driven systems.
  • Experience with version control systems, particularly Git.
  • Strong problem-solving skills, with the ability to debug complex systems and diagnose issues across the stack.

Preferred Qualifications:

  • Master's degree in Computer Science, AI, or a related field.
  • Direct hands-on experience integrating with Google Cloud Platform's Vertex AI APIs (e.g., PaLM, Gemini, Imagen, Codey, etc.)
  • Experience with containerization technologies (Docker) and orchestration (Kubernetes, Cloud Run, GKE).
  • Familiarity with CI/CD pipelines and DevOps practices.
  • Understanding of fundamental machine learning and deep learning concepts, especially in the context of generative AI.
  • Experience or strong interest in building APIs specifically for mobile applications (Android/iOS).
  • Knowledge of data streaming technologies (e.g., Kafka, GCP Pub/Sub).
  • Experience with caching technologies (e.g., Redis, Memcached).
  • The ability to collaborate effectively with cross-functional teams.

Benefits

OPPO is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

The US base salary range for this full-time position is $100,000-$200,000 + bonus + long term incentives benefits. Our salary ranges are determined by role, level, and location.