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Gen Ai Engineer Jobs in Tennessee (NOW HIRING)

Brooksource

AI Engineer

Hermitage, TN · On-site

Gen AI Engineer/Architect Direct Hire Opportunity Location: Nashville, TN or within driving distance Primarily Remote with 10% travel expectation As a GenAI Engineer , you will actively engage in ...

Deloitte

Oracle Gen AI Manager

Nashville, TN · On-site

Identify high-value AI use cases and guide teams on prompt engineering, model selection, and model ... Work you'll do As an Oracle Gen AI Architect Manager on the Oracle team, you will translate ...

Cyod

Principal Data Scientist

Shelbyville, TN · On-site

$140 - $180/hr

Practical experience designing Gen AI and agentic solutions, including prompt engineering, tool use, orchestration patterns, RAG architectures, guardrails, and human review workflows. * Machine ...

Symbotic Inc.

System Engineer

Seymour, TN

... end-to-end, AI-powered robotic and software platform. Symbotic reinvents the warehouse as a ... Applying next-gen technology, high-density storage and machine learning to solve today's complex ...

GOARC

Go-to-Market Engineer

Franklin, TN · On-site

About GOARC GOARC is an AI-native B2B SaaS company helping industrial organizations protect their ... gen and outbound. What's missing is the system underneath: the data, the automations, the content ...

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All JobsGen Ai Engineer JobsGen Ai Engineer Jobs in Tennessee

Gen Ai Engineer information

See Tennessee salary details

$54K

$101.3K

$184.2K

How much do gen ai engineer jobs pay per year?

As of Aug 30, 2026, the average yearly pay for gen ai engineer in Tennessee is $101,319.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,100.00 and $120,300.00 per year, depending on experience, location, and employer.

What is a Gen AI engineer?

Gen AI Engineers are professionals who design, develop, and deploy generative artificial intelligence systems, such as large language models and image generators. They combine expertise in machine learning, deep learning, and software engineering to build applications that can create new content, automate tasks, and solve complex problems. Gen AI Engineers often work with frameworks like TensorFlow or PyTorch and collaborate with data scientists and product teams to bring generative AI solutions into real-world products.

What are the key skills and qualifications needed to thrive as a Gen AI engineer?

To thrive as a Gen AI Engineer, you need a solid background in computer science, machine learning, and deep learning, typically supported by a relevant degree and experience with AI model development. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms such as AWS or Google Cloud, and proficiency in programming languages like Python are essential, as are certifications in AI or cloud technologies. Strong problem-solving skills, creativity, and the ability to communicate complex concepts effectively help you stand out in this role. These skills and qualities are crucial for building innovative AI solutions that meet business needs and drive technological advancement.

What are some common challenges Gen AI engineers face when deploying AI models in production environments?

Gen AI Engineers often encounter challenges such as ensuring model scalability, managing computational resources efficiently, and maintaining data privacy when deploying AI models. Additionally, integrating generative models with existing systems can require significant collaboration with DevOps and software engineering teams. Monitoring model performance in real-time and addressing issues like model drift or unexpected outputs are also critical responsibilities to ensure robust and reliable AI solutions.

What is the difference between Gen Ai Engineer vs Data Scientist?

AspectGen Ai EngineerData Scientist
Required CredentialsDegree in Computer Science, AI, or related fields; experience with AI frameworksDegree in Data Science, Statistics, or related fields; strong analytical skills
Work EnvironmentTech companies, AI startups, R&D labsBusiness analytics, research institutions, tech firms
Employer & Industry UsageDevelops generative AI models, focuses on AI product developmentAnalyzes data, builds predictive models, supports decision-making
Search & Comparison IntentUnderstanding AI-specific roles, skills, and responsibilitiesData analysis, insights, and statistical modeling

While both roles involve working with data and AI technologies, a Gen Ai Engineer primarily focuses on developing and deploying generative AI models, whereas a Data Scientist emphasizes analyzing data to extract insights and build predictive models. The roles often overlap in skills and work environment but differ in their core objectives and applications.

What are popular job titles related to Gen Ai Engineer jobs in Tennessee?

For Gen Ai Engineer jobs in Tennessee, the most frequently searched job titles are:

What job categories do people searching Gen Ai Engineer jobs in Tennessee look for?

The top searched job categories for Gen Ai Engineer jobs in Tennessee are:

What cities in Tennessee are hiring for Gen Ai Engineer jobs?

Cities in Tennessee with the most Gen Ai Engineer job openings:

Gen Ai Engineer jobs near you
Infographic showing various Gen Ai Engineer job openings in Tennessee as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 63% Physical, 5% Hybrid, and 32% Remote job distribution, with an average salary of $101,319 per year, or $48.7 per hour.

Gen AI Engineer- Systems Engineer

1 point system

Nashville, TN • On-site

Contractor

Re-posted 20 days ago

Job description

  • AI/ML Expertise: 8+ years of experience, with the last 2 years in GenAI technologies like OpenAI, Claude, Gemini, LangChain, Agents, Vector databases, Prompt Engineering, and fine-tuning.
  • Programming Languages & Libraries: Proficiency in Python, R, TensorFlow, PyTorch, Keras, Julia, and various ML libraries, along with NLP capabilities.
  • Web & Software Development: Skilled in Angular, React, NodeJS, Python, Streamlit, C#, .NET Core, Golang, SQL/NoSQL.
  • Cloud-Native Engineering: Experience with FaaS/PaaS/micro-services on cloud platforms like Azure, AWS, and GCP.
  • Methodologies & Tools: Strong understanding of XP, Lean, SAFe, DevSecOps, SRE, ADO, GitHub, SonarQube, and other tools for rapid, quality product delivery.