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Generative Ai Testing Jobs in Tennessee (NOW HIRING)

Principal AI Engineer

Nashville, TN · On-site

$180 - $240/hr

... generative AI, and agentic systems, but many face a critical challenge: moving beyond demos and ... Define and implement testing and evaluation approaches for agent performance, prompt quality ...

AI Lead Engineer

Nashville, TN · On-site

$99K - $130K/yr

... for Generative AI and Agentic AI capabilities within the Assure Build Platform, ensuring ... testing automation, performance analysis, and operational intelligence. • Establish and enforce ...

Principal AI Engineer

Nashville, TN · On-site

$150 - $210/hr

... generative AI, and agentic systems, but many face a critical challenge: moving beyond demos and ... Define and implement testing and evaluation approaches for agent performance, prompt quality ...

AI Engineer

Nashville, TN · On-site

$50K - $112K/yr

... Applying generative AI techniques, including prompt engineering, LLM evaluation, and fine-tuning ... testing, and adversarial benchmarking, to assess reasoning, tool-calling reliability, and output ...

AI Lead Engineer

Nashville, TN · On-site

$99K - $130K/yr

Understand the define technical vision, roadmap, and architecture for Generative AI and Agentic AI ... testing automation, performance analysis, and operational intelligence. * Establish and enforce ...

AI Lead Engineer

Nashville, TN · On-site

$99K - $130K/yr

Understand the define technical vision, roadmap, and architecture for Generative AI and Agentic AI ... testing automation, performance analysis, and operational intelligence. * Establish and enforce ...

AI Lead Engineer

Nashville, TN · On-site

$99K - $130K/yr

Understand the define technical vision, roadmap, and architecture for Generative AI and Agentic AI ... testing automation, performance analysis, and operational intelligence. * Establish and enforce ...

AI Solutions Engineer

Nashville, TN · On-site

$107K - $170K/yr

This role combines Generative AI, Microsoft Power Platform, Databricks, and modern software ... Own solutions throughout their lifecycle, including testing, deployment, monitoring, and continuous ...

AI Solutions Engineer

Nashville, TN · On-site

$107K - $170K/yr

This role combines Generative AI, Microsoft Power Platform, Databricks, and modern software ... Own solutions throughout their lifecycle, including testing, deployment, monitoring, and continuous ...

Showing results 21-40

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:

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.

Principal AI Engineer

Cyod

Nashville, TN • On-site

$180 - $240/hr

Other

Posted 4 days ago


Job description

Principal AI EngineerFocus

Agentic Systems, Google Cloud & Vertex AI, LLMs, and Clinical Operations Engineering

Location

Nashville, TN area preferred

Insight at a Glance
  • 14,000+ engaged teammates globally
  • $8.2 billion in revenue in 2025
  • Certified as a Great Place to work in 9 Countries in 2025
  • Fortune 500 Company (No. 447) in 2025
  • Received 25+ industry and partner awards in the past year
  • $1.4M+ total charitable contributions in 2024 by Insight globally
About the Role

Now is the time to bring your expertise to Insight. Healthcare and enterprise organizations are rapidly adopting large language models, generative AI, and agentic systems, but many face a critical challenge: moving beyond demos and prototypes into secure, maintainable, production‑grade AI applications that integrate with real clinical and operational workflows.

We are seeking a Principal AI Engineer with deep experience in agentic systems, Google Cloud Platform and Vertex AI, large language models, clinical operations, and forward deployed engineering. In this client‑facing consulting role, you will design and build AI‑enabled applications that connect clinical and enterprise data, tools, workflows, and users through scalable, governed engineering patterns.

You will bridge the gap between AI strategy and production implementation, partnering with clinicians, architects, data teams, security leaders, and operations stakeholders to deliver solutions that are useful, observable, secure, and ready for enterprise adoption.

What You'll Do
  • Agentic AI Solution Engineering: Design and build agentic AI systems that reason across tasks, use tools, retrieve context, and orchestrate multi‑step workflows to automate and optimize clinical and operational processes, with human‑in‑the‑loop review.
  • Google Cloud & Vertex AI Delivery: Develop AI solutions using Google Cloud technologies such as Vertex AI, Gemini models, Vertex AI Agent Builder, Vertex AI Search, Document AI, BigQuery, and related Google Cloud services.
  • Clinical Note & Document Processing: Build LLM‑powered pipelines to extract, summarize, and structure clinical notes and unstructured healthcare documents, improving accuracy, speed, and downstream operational workflows.
  • MLOps and AI Delivery Automation: Establish CI/CD and MLOps pipelines, infrastructure‑as‑code, environment management, automated testing, release controls, and observability practices for AI‑enabled applications on Google Cloud.
  • RAG and Enterprise Knowledge Systems: Build retrieval‑augmented generation solutions that connect securely to clinical content, structured data, EHR and document repositories, and operational systems.
  • Security, Identity, and Governance: Implement authentication, authorization, RBAC, data access controls, logging, auditability, and guardrails to ensure AI systems handle PHI safely and operate compliantly in regulated healthcare environments.
  • Evaluation and Quality Engineering: Define and implement testing and evaluation approaches for agent performance, prompt quality, retrieval relevance, hallucination risk, response quality, latency, and reliability.
  • Forward Deployed Technical Leadership: Serve as a hands‑on, forward deployed senior engineer and technical advisor, embedding with client teams to make architecture decisions, resolve implementation blockers, and move AI solutions from prototype to production.
  • Practice Enablement: Mentor engineers and consultants while contributing reusable agentic design patterns, reference architectures, DevOps templates, and Google Cloud AI delivery accelerators for Insight.
What We're Looking For
  • Experience: 6+ years of experience in software engineering, cloud engineering, AI engineering, enterprise application development, or solution architecture, ideally in consulting, healthcare, or client‑facing delivery environments.
  • Agentic Systems Expertise: Hands‑on experience designing and building agentic AI applications, including orchestration, tools, memory, planning, multi‑step workflows, RAG, and human‑in‑the‑loop controls.
  • Google Cloud AI Platform Depth: Strong experience with Vertex AI and the broader Google Cloud AI ecosystem, including Gemini models, Vertex AI Agent Builder, Vertex AI Search, Document AI, BigQuery, or related Google Cloud services.
  • Software Engineering Foundation: Strong proficiency in modern programming languages and frameworks commonly used for AI application development, such as Python, TypeScript, Go, FastAPI, LangChain/LangGraph, or similar technologies.
  • DevOps and Cloud Engineering: Experience with GitHub Actions, Cloud Build, CI/CD, infrastructure‑as‑code (Terraform), containers (GKE and Cloud Run), APIs, monitoring, logging, environment promotion, and production release management.
  • Clinical Operations & Healthcare Data: Experience integrating AI with clinical and operational systems—EHRs, clinical documentation, and healthcare data standards such as HL7 and FHIR—including handling of PHI in regulated environments.
  • AI Quality and Observability: Understanding of AI evaluation, prompt/version management, automated testing, telemetry, tracing, monitoring, model behavior analysis, and operational support patterns.
  • Consulting Mindset: Strong communication skills with the ability to translate technical trade‑offs into practical recommendations for executives, clinical leaders, platform teams, security stakeholders, and operations users.
Preferred Certifications
  • Google Cloud / AI: Google Cloud Professional Machine Learning Engineer, Professional Cloud Architect, Generative AI Leader, or relevant Google Cloud and AI certifications.
  • DevOps / Engineering: GitHub, Google Cloud Professional DevOps Engineer, Kubernetes (CKA), Terraform, or cloud‑native engineering certifications.
  • Healthcare / Governance: HIPAA, Responsible AI, or healthcare data and AI governance‑related certifications are a plus.
What you can expect

We’re legendary for taking care of you, your family and to help you engage with your local community.

But what really sets us apart are our core values of Hunger, Heart, and Harmony, which guide everything we do, from building relationships with teammates, partners, and clients to making a positive impact in our communities.

Join us today, your ambITious journey starts here.

Equal Opportunity Employer Statement

Insight is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, sexual orientation or any other characteristic protected by law.

When you apply, please tell us the pronouns you use and any reasonable adjustments you may need during the interview process.

At Insight, we celebrate diversity of skills and experience so even if you don’t feel like your skills are a perfect match - we still want to hear from you!

Insight does not accept unsolicited resumes from recruiters or employment agencies. Unsolicited resumes will be treated as direct applications from the candidate, and recruiters or agencies who submit candidates for this position without a prior, written vendor agreement will not be eligible for any form of compensation, even if the candidate is hired.

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