AI Engineer Jobs in Tennessee
AI Engineer jobs in Tennessee are actively sought across healthcare technology, financial services, logistics, and defense contracting, with openings ranging from entry-level data pipeline roles through senior machine learning architects. Nashville, Memphis, and Knoxville anchor most of the hiring, with employers like HCA Healthcare, FedEx, and Oak Ridge National Laboratory maintaining consistent demand for ai engineers. The most in-demand specialties in the state include natural language processing, computer vision, and MLOps infrastructure. Find a role that fits below and apply directly.
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Showing 5 of 28+ AI Engineer jobs
We are looking for engineers who are excited to experiment, prototype, learn quickly, and turn promising ideas into production-quality software . You will have opportunities to work with LLMs, AI agents, reasoning systems, context and retrieval techniques, evaluation systems, and intelligent automation while solving real developer productivity problems.
Success in this role requires curiosity and strong engineering fundamentals. You should be comfortable working on problems where the requirements or technical approach may not initially be clear. You will collaborate with senior engineers, product managers, AI/ML teams, and OCI service teams to explore potential solutions, validate assumptions through experimentation, and determine which ideas can deliver meaningful improvements to the developer experience.
As a Senior Software Engineer, you will own significant components from design through production. You will contribute to architecture and technical decisions, build prototypes to evaluate new approaches, and develop scalable services and platform capabilities that turn successful AI experiments into reliable developer experiences.
- Design and build AI-powered developer tools and platform capabilities that improve developer productivity across software development, testing, debugging, delivery, and operational workflows.
- Experiment with emerging AI technologies by building prototypes, evaluating models and agentic approaches, testing hypotheses, and using results to determine which ideas should progress toward production.
- Develop production services integrating LLMs, AI agents, context and retrieval systems, tool integrations, orchestration, evaluation, and intelligent automation .
- Own substantial components through the complete engineering lifecycle, including design, implementation, testing, deployment, observability, operations, and continuous improvement.
- Work effectively in ambiguous problem spaces , breaking broad problems into tractable engineering challenges, evaluating alternatives, and iterating as requirements and technologies evolve.
- Contribute to architecture and design discussions, working with senior technical leaders to develop solutions that are scalable, extensible, secure, reliable, and cost-efficient.
- Build mechanisms to evaluate the effectiveness of AI-powered experiences , using automated evaluation, telemetry, experimentation, and developer feedback to improve quality and reliability.
- Collaborate across engineering, product, AI/ML, and OCI service teams to integrate platform capabilities and deliver end-to-end developer experiences.
- Investigate complex technical issues across distributed systems and AI components, identify root causes, and implement durable solutions. Contribute to a strong engineering culture through thoughtful design and code reviews, technical documentation, knowledge sharing, and mentoring other engineers.
Required Qualifications
- 5+ years of software engineering experience designing, building, and operating production software systems.
- Strong programming and software engineering skills, with experience building distributed systems, cloud services, developer infrastructure, platform services, or large-scale backend systems .
- Experience with or strong demonstrated interest in LLMs, generative AI, AI agents, or related AI technologies , including the engineering considerations involved in integrating AI capabilities into software products.
- Demonstrated willingness to experiment and learn in rapidly evolving technical areas , including building prototypes, evaluating alternatives, using data to validate assumptions, and adapting based on results.
- Ability to work effectively with ambiguous requirements , independently break down complex problems, make sound engineering tradeoffs, and drive substantial technical work to completion.
- Experience designing and delivering reliable production software, including considerations around APIs, scalability, testing, observability, performance, security, and operational excellence . BS or MS in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience.
Desired Qualifications
- Experience building AI-powered developer tools, coding assistants or agents, intelligent testing or debugging systems, developer automation, or developer productivity platforms .
- Practical experience with LLMs, agentic workflows, tool use, context engineering, retrieval, inference, model APIs, or AI evaluation techniques .
- Experience with cloud-native and distributed systems technologies , including containers, orchestration, service APIs, messaging, data stores, and production observability.
- Experience using experimentation and quantitative evaluation to assess new technologies or product capabilities and improve them based on measurable results. Demonstrated ability to learn unfamiliar technologies quickly, contribute to technical design discussions, collaborate effectively across teams, and take ownership of complex engineering problems.
#LI-SP1
We are looking for engineers who are excited to experiment, prototype, learn quickly, and turn promising ideas into production-quality software . You will have opportunities to work with LLMs, AI agents, reasoning systems, context and retrieval techniques, evaluation systems, and intelligent automation while solving real developer productivity problems.
Success in this role requires curiosity and strong engineering fundamentals. You should be comfortable working on problems where the requirements or technical approach may not initially be clear. You will collaborate with senior engineers, product managers, AI/ML teams, and OCI service teams to explore potential solutions, validate assumptions through experimentation, and determine which ideas can deliver meaningful improvements to the developer experience.
As a Senior Software Engineer, you will own significant components from design through production. You will contribute to architecture and technical decisions, build prototypes to evaluate new approaches, and develop scalable services and platform capabilities that turn successful AI experiments into reliable developer experiences.
- Design and build AI-powered developer tools and platform capabilities that improve developer productivity across software development, testing, debugging, delivery, and operational workflows.
- Experiment with emerging AI technologies by building prototypes, evaluating models and agentic approaches, testing hypotheses, and using results to determine which ideas should progress toward production.
- Develop production services integrating LLMs, AI agents, context and retrieval systems, tool integrations, orchestration, evaluation, and intelligent automation .
- Own substantial components through the complete engineering lifecycle, including design, implementation, testing, deployment, observability, operations, and continuous improvement.
- Work effectively in ambiguous problem spaces , breaking broad problems into tractable engineering challenges, evaluating alternatives, and iterating as requirements and technologies evolve.
- Contribute to architecture and design discussions, working with senior technical leaders to develop solutions that are scalable, extensible, secure, reliable, and cost-efficient.
- Build mechanisms to evaluate the effectiveness of AI-powered experiences , using automated evaluation, telemetry, experimentation, and developer feedback to improve quality and reliability.
- Collaborate across engineering, product, AI/ML, and OCI service teams to integrate platform capabilities and deliver end-to-end developer experiences.
- Investigate complex technical issues across distributed systems and AI components, identify root causes, and implement durable solutions. Contribute to a strong engineering culture through thoughtful design and code reviews, technical documentation, knowledge sharing, and mentoring other engineers.
Required Qualifications
- 5+ years of software engineering experience designing, building, and operating production software systems.
- Strong programming and software engineering skills, with experience building distributed systems, cloud services, developer infrastructure, platform services, or large-scale backend systems .
- Experience with or strong demonstrated interest in LLMs, generative AI, AI agents, or related AI technologies , including the engineering considerations involved in integrating AI capabilities into software products.
- Demonstrated willingness to experiment and learn in rapidly evolving technical areas , including building prototypes, evaluating alternatives, using data to validate assumptions, and adapting based on results.
- Ability to work effectively with ambiguous requirements , independently break down complex problems, make sound engineering tradeoffs, and drive substantial technical work to completion.
- Experience designing and delivering reliable production software, including considerations around APIs, scalability, testing, observability, performance, security, and operational excellence . BS or MS in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience.
Desired Qualifications
- Experience building AI-powered developer tools, coding assistants or agents, intelligent testing or debugging systems, developer automation, or developer productivity platforms .
- Practical experience with LLMs, agentic workflows, tool use, context engineering, retrieval, inference, model APIs, or AI evaluation techniques .
- Experience with cloud-native and distributed systems technologies , including containers, orchestration, service APIs, messaging, data stores, and production observability.
- Experience using experimentation and quantitative evaluation to assess new technologies or product capabilities and improve them based on measurable results. Demonstrated ability to learn unfamiliar technologies quickly, contribute to technical design discussions, collaborate effectively across teams, and take ownership of complex engineering problems.
#LI-SP1
See All 28 AI Engineer Jobs in Tennessee
Find roles in Tennessee that match your experience and apply in just a few clicks.
Find AI Engineer JobsAI Engineer Jobs by City in Tennessee
Where Tennessee roles are concentrated, by current openings.
AI Engineer Job Market in Tennessee
A snapshot from current Tennessee openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
What Tennessee Employers Look For
The qualifications that appear most often in AI engineer jobs across Tennessee.
- Bachelor's or master's degree in computer science, data science, or a closely related field
- Proficiency in Python and machine learning frameworks such as TensorFlow or PyTorch
- Experience designing, training, and deploying machine learning models in production environments
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for AI workloads
- Strong understanding of data engineering pipelines, feature stores, and model monitoring
- Ability to communicate model performance and limitations to non-technical business stakeholders
AI Engineer Jobs in Tennessee: Frequently Asked Questions
How do you become a ai engineer in Tennessee?
Tennessee does not require a state-issued license to work as an ai engineer. The standard path is a bachelor's degree in computer science, data science, or electrical engineering, followed by hands-on experience with machine learning frameworks and cloud platforms. Many Tennessee employers, particularly in healthcare technology and defense, also value candidates who hold industry certifications in AWS Machine Learning or Google Professional Machine Learning Engineer alongside a strong project portfolio.
Which companies hire ai engineers in Tennessee?
Employers hiring ai engineers in Tennessee right now include Oracle, Capgemini, and BPD, based on current listings on Migrate Mate as of September 2026. Tennessee's concentration of large healthcare systems, logistics companies, and federally funded research institutions means ai engineer demand is spread across multiple industry verticals rather than concentrated in a single sector.
Which Tennessee cities have the most ai engineer jobs?
Nashville, Memphis, and Chattanooga have the most ai engineer openings in Tennessee. Nashville leads because of its dense cluster of healthcare technology companies and corporate headquarters, Memphis draws demand from logistics and supply chain operations anchored by FedEx, and Knoxville benefits from proximity to Oak Ridge National Laboratory and the University of Tennessee's research partnerships.
Are there remote ai engineer jobs in Tennessee?
Yes, and more than most fields. About 64% of ai engineer openings tied to Tennessee are remote or hybrid as of September 2026, reflecting how naturally the role fits distributed work. Model development, experimentation, and data pipeline work are the parts of the role most commonly performed fully remote, while roles tied to on-site infrastructure or classified government contracts at Oak Ridge typically require in-person presence.
How can I get hired as a ai engineer in Tennessee with little or no experience?
The most realistic entry path is applying for junior data scientist or machine learning associate roles at Tennessee's large healthcare technology firms, where companies like HCA Healthcare and Ciara Health run structured new-graduate programs. Building a public portfolio on GitHub with end-to-end projects, including data ingestion through model deployment, gives candidates a meaningful edge. Adjacent roles in data analytics or data engineering at Tennessee employers are also a common stepping stone into a dedicated ai engineer position.
Where can I find and apply to ai engineer jobs in Tennessee?
You can find and apply to ai engineer jobs in Tennessee on Migrate Mate, which lists current Tennessee openings across Nashville, Memphis, Knoxville, and surrounding areas. Find roles that fit your experience and specialization and apply directly to the employers posting them.
See All 28 AI Engineer Jobs in Tennessee
Find roles in Tennessee that match your experience and apply in just a few clicks.
Find AI Engineer Jobs