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Generative Ai Testing Jobs in Tennessee (NOW HIRING)

Accenture

Senior Data Scientist

Nashville, TN · On-site

... generative AI, agentic AI, and decision-science problem statements. * Perform exploratory data analysis, statistical analysis, hypothesis testing, experimental design, feature engineering, predictive ...

Accenture

Senior Data Scientist

Morristown, TN · On-site

... generative AI, agentic AI, and decision-science problem statements. * Perform exploratory data analysis, statistical analysis, hypothesis testing, experimental design, feature engineering, predictive ...

corpay

Engineering Manager

Brentwood, TN · Hybrid

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Experience applying generative AI to software design, development, testing, or delivery. * Experience with AWS or Azure cloud services * Experience with Git and modern source control workflows.

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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 Tennessee?

For Generative Ai Testing jobs in Tennessee, the most frequently searched job titles are:

What job categories do people searching Generative Ai Testing jobs in Tennessee look for?

The top searched job categories for Generative Ai Testing jobs in Tennessee are:

What cities in Tennessee are hiring for Generative Ai Testing jobs?

Cities in Tennessee with the most Generative Ai Testing job openings:

Generative Ai Testing jobs near you
Infographic showing various Generative Ai Testing job openings in Tennessee as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 10% Part Time, 5% Contract, and 1% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Cloud Engineer- Data/AI Focused

Innovative Solutions

Nashville, TN • On-site

$110K - $132K/yr

Full-time

Re-posted 8 days ago

Job description

Job Summary:
Innovative Solutions is a technology company focusing on Data and AI solutions. As a Data & AI Engineer, you will build and deploy modern data pipelines and generative AI solutions on AWS while working directly with clients to deliver secure, scalable, and production-ready solutions.
Responsibilities:
• Implementing data pipelines using AWS services such as Glue, Lambda, Step Functions, and EMR
• Creating and maintaining data extraction, transformation, and loading processes
• Configuring and optimizing AWS database services including RDS, Aurora, Redshift, and DynamoDB
• Implementing data lakes using S3 and related AWS services
• Designing and building production-ready Generative AI applications using Amazon Bedrock and foundation models such as Anthropic Claude
• Building and optimizing RAG (Retrieval-Augmented Generation) pipelines with vector databases
• Developing AI agents and multi-agent orchestration systems using frameworks like LangChain or LlamaIndex
• Writing and testing SQL queries and stored procedures
• Documenting technical solutions and providing knowledge transfer to customers
• Supporting the implementation of data governance and security controls
• Troubleshooting and resolving issues with data pipelines and AI services
• Participating in code reviews and implementing feedback
• Assisting with proof-of-concept implementations for customer engagements
Qualifications:
Required:
• 5+ years of software engineering experience with at least 2+ years focused on AI/ML, data engineering, or cloud-native development
• 2+ years of hands-on AWS experience with production deployments
• 1+ years of direct Generative AI experience (LLMs, embeddings, RAG, agents)
• Proven track record delivering production AI applications from concept to deployment
• Strong understanding of software engineering best practices (version control, testing, code review, documentation)
• Experience working in agile/scrum environments with distributed teams
• Excellent problem-solving skills and ability to work independently with minimal supervision
• Strong written and verbal communication skills for client-facing interactions
Preferred:
• Technical familiarity with AWS data and AI/ML services and modern data engineering practices
• Hands-on experience with ETL/ELT processes and data transformation
• Exposure to Generative AI concepts including LLMs, embeddings, RAG, and agent frameworks
• Ability to write and optimize SQL queries across various database platforms
• Knowledge of data modeling concepts and best practices
• Strong analytical and problem-solving skills
• Eagerness to learn new technologies and keep up with cloud and AI innovations
• Excellent communication skills with the ability to explain technical concepts clearly
• Attention to detail and commitment to solution quality
• Collaborative mindset with strong teamwork capabilities
• Experience or interest in automation and infrastructure as code
Company:
Innovative Solutions is an IT company that specializes in software development, mobile app development, and game development. Founded in 2009, the company is headquartered in Karachi, PAK, with a team of 51-200 employees. The company is currently Growth Stage.

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