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Generative Ai Testing Jobs in Washington (NOW HIRING)

Experience with AI testing, validation, benchmarking, and evaluation frameworks for both traditional ML and generative AI systems. * Experience implementing practical MLOps pipelines and AI ...

Experience with AI testing, validation, benchmarking, and evaluation frameworks for both traditional ML and generative AI systems. * Experience implementing practical MLOps pipelines and AI ...

Experience with AI testing, validation, benchmarking, and evaluation frameworks for both traditional ML and generative AI systems * Experience implementing practical MLOps pipelines and AI ...

Experience with AI testing, validation, benchmarking, and evaluation frameworks for both traditional ML and generative AI systems * Experience implementing practical MLOps pipelines and AI ...

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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 much do AI testers get paid?

AI testers, involved in evaluating and validating generative AI models, typically earn salaries ranging from $60,000 to $120,000 annually depending on experience, location, and company size. Entry-level positions may start lower, while experienced testers with specialized skills in machine learning and data analysis can earn higher wages.

Is AI testing a good career?

AI testing, including roles like Generative AI Testing, is a growing field with increasing demand for skills in machine learning, data analysis, and software quality assurance. It offers opportunities in tech companies, research labs, and startups, often requiring knowledge of AI frameworks and testing tools. The career can be stable and rewarding for those with technical expertise and an interest in AI development.

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 is the salary of generative AI tester?

The salary of a generative AI tester typically ranges from $70,000 to $120,000 annually, depending on experience, location, and company size. Entry-level positions may start lower, while experienced testers with specialized skills in AI and machine learning can earn higher salaries. Certifications in AI or related fields can also influence compensation.

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.

How do I become an AI tester?

To become an AI tester, you should have a strong understanding of machine learning concepts, programming skills in languages like Python, and experience with data annotation and model evaluation. Familiarity with AI tools, testing frameworks, and quality assurance processes is also important. Gaining relevant certifications or training in AI and software testing can enhance your qualifications.

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 Washington? For Generative Ai Testing jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Generative Ai Testing jobs in Washington look for? The top searched job categories for Generative Ai Testing jobs in Washington are:
Infographic showing various Generative Ai Testing job openings in Washington as of July 2026, with employment types broken down into 74% Full Time, 22% Part Time, and 4% Contract. Highlights an 71% Physical, 3% Hybrid, and 26% Remote job distribution.

Senior AI Engineer - Generative AI / RAG

Ampcus Inc

Chantilly, VA • On-site

$57 - $73.75/hr

Full-time

Re-posted 13 days ago


Job description

Job Summary:
Ampcus Inc. is a certified global provider of a broad range of Technology and Business consulting services. We are seeking a Senior AI Engineer with strong expertise in Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) to build enterprise AI knowledge platforms and intelligent search solutions.
Responsibilities:
• Design and implement RAG-based AI solutions and enterprise knowledge bases.
• Integrate LLMs (OpenAI, Claude, Llama, etc.) into business applications.
• Develop AI-powered chatbots, search, and conversational AI platforms.
• Build and optimize data ingestion, embedding, and retrieval pipelines.
• Work with vector databases such as Pinecone, FAISS, Weaviate, or ChromaDB.
• Collaborate with engineering and business teams to deploy scalable AI solutions.
• Improve AI response quality, grounding, and hallucination reduction.
Qualifications:
Required:
• 7 years of software engineering or AI/ML experience.
• Strong hands-on experience with Generative AI and RAG implementations.
• Expertise with Python and AI frameworks such as LangChain or LlamaIndex.
• Experience with LLM APIs, embeddings, semantic search, and prompt engineering.
• Knowledge of vector databases and enterprise AI architecture.
• Experience with AWS, Azure, or GCP cloud platforms.
• Familiarity with APIs, Docker, Kubernetes, and MLOps/LLMOps practices.
Preferred:
• Experience with AI agents, fine-tuning, or Graph RAG.
• Knowledge of AI governance, security, and responsible AI.
• Experience building enterprise AI assistants or knowledge management solutions.
Company:
Ampcus is a global business, technology consulting and an staff augmentation firm specializing in AI/ML,digital solutions, Cybersecurity & Risk management, Testing, Forensics & Fraud services and human capital management. Founded in 2004, the company is headquartered in Chantilly, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

Ampcus logo

About Ampcus

Sourced by ZipRecruiter

Ampcus Inc. is a ISO 20000, ISO 27000, ISO 9001, CMMI DEV/3 SM and CMMI SVC/3 SM certified global provider of a broad range of Technology and Business consulting services. From strategy to execution, our disciplined yet flexible approach starts and ends with our clients. By listening hard and working harder, client goals become our goals. Their success is our satisfaction. It’s why our clients sleep well at night. We believe that the success of an engagement is determined by strong project management, as well as clear communication and mutual commitment working collaboratively. Our methodology begins with listening to the customer about their needs, then working with their team to gain a clear understanding of the requirements, while providing knowledge transfer of best practices for the organization.

Industry

It services

Company size

1,001 - 5,000 Employees

Headquarters location

Chantilly, VA, US

Year founded

2004