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Applied Ai Engineer Jobs in Tennessee (NOW HIRING)

Applied AI Engineer II

Nashville, TN · On-site

$94K - $128K/yr

As an Applied AI Engineer II , you will actively engage in your engineering craft, taking a hands-on approach to building and enhancing high-visibility, full-stack products that serve the business ...

Applied AI Engineer II

Hermitage, TN · On-site

$85K - $117K/yr

As an Applied AI Engineer II , you will actively engage in your engineering craft, taking a hands-on approach to building and enhancing high-visibility, full-stack products that serve the business ...

Lead Applied AI Engineer II

Hermitage, TN · On-site

$89K - $118K/yr

As a Lead Applied AI Engineer II , you will actively engage in your engineering craft, taking a hands-on approach to multiple high-visibility projects. Your expertise will be pivotal in delivering ...

Lead Applied AI Engineer II

Hermitage, TN · On-site

$89K - $118K/yr

As a Lead Applied AI Engineer II , you will actively engage in your engineering craft, taking a hands-on approach to multiple high-visibility projects. Your expertise will be pivotal in delivering ...

Applied AI Product Manager An Applied AI Product Manager is a senior individual contributor ... Co-create in collaboration with business stakeholders, engineering, experience, and delivery. * Use ...

Applied AI SRE III - PxE GPS

Hermitage, TN · On-site

$50 - $66.50/hr

Applied AI Site Reliability Engineer III Role Overview: As an Applied AI Site Reliability Engineer III , you will actively engage in your engineering craft, taking a hands-on approach to the ...

AI - Data Engineer

Nashville, TN · On-site

$129 - $150/hr

The ideal candidate combines strong software engineering fundamentals with hands on experience building applied AI systems that operate reliably in production environments and deliver measurable ...

New

Position Summary C2 Labs is hiring an AI Engineer to design, build, and ship AI and technology ... systems, or applied technology products (or equivalent intensity). · 1-3 years shipping AI ...

Applied AI Solutions Analyst

Nashville, TN · On-site +1

$93K - $169K/yr

Are you a Product Manager, Pre-Sales Engineer, or Business Analyst who lives and breathes AI? This ... The Applied AI Solutions Analyst sits at the center of that effort. You won't hand requirements to ...

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Showing results 1-20

Applied Ai Engineer information

What are the key skills and qualifications needed to thrive as an applied AI engineer?

To thrive as an Applied AI Engineer, you need strong proficiency in programming (especially Python), machine learning algorithms, statistics, and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud platforms (such as AWS or Azure), and knowledge of data management tools are typically required. Excellent problem-solving, communication, and teamwork skills help you translate complex models into real-world solutions and collaborate across disciplines. These competencies ensure you can effectively develop, deploy, and maintain AI systems that drive business value.

What are some common challenges applied AI engineers face when deploying AI models into production environments?

Applied AI Engineers often encounter challenges such as ensuring models perform consistently on real-world data, optimizing models for speed and scalability, and integrating AI solutions with existing systems. Managing data privacy, monitoring for model drift, and maintaining robust documentation are also key concerns. Collaboration with DevOps, data engineering, and product teams is essential to address these challenges effectively and deliver reliable AI-driven solutions.

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

AspectApplied Ai EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; experience with AI frameworksBachelor's or Master's in CS, Statistics, or related fields; strong analytical skills
Work EnvironmentDevelops and deploys AI models in production environmentsAnalyzes data to extract insights and build predictive models
Industry UsageUsed in tech, healthcare, finance for deploying AI solutionsUsed across industries for data analysis and modeling

Applied Ai Engineers focus on implementing and deploying AI models in real-world applications, while Data Scientists primarily analyze data to generate insights and build predictive models. Both roles require similar educational backgrounds but differ in their core responsibilities and work environments.

How much does an applied AI engineer make?

An applied AI engineer's salary varies based on experience, location, and industry, but typically ranges from $80,000 to $150,000 annually. Senior roles or those with specialized skills in machine learning, deep learning, and programming languages like Python or TensorFlow tend to earn higher salaries.

What does an applied AI engineer do?

An applied AI engineer develops and implements artificial intelligence models and algorithms to solve real-world problems. They work with data, machine learning frameworks, and programming languages like Python or TensorFlow to create practical AI solutions for businesses or products.

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

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

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

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

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

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

Infographic showing various Applied 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.

Applied AI Engineer II

Deloitte

Nashville, TN • On-site

$94K - $128K/yr

Full-time

Re-posted 11 days ago


Key responsibilities

  • Build and enhance high-visibility, full-stack products that serve the business and its users.

  • Collaborate with cross-functional teams to design, develop, and ship products end to end, from concept through production.

  • Develop engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality, lean designs and implementations.


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 93 frontline employees who took The Breakroom Quiz

46th of 152 rated financial services


Job description

As an Applied AI Engineer II, you will actively engage in your engineering craft, taking a hands-on approach to building and enhancing high-visibility, full-stack products that serve the business and its users. Your expertise will be pivotal in delighting customers and users, while driving tangible value across Deloitte's product and AI investments. You will leverage your engineering craftsmanship across full-stack software engineering and modern frameworks-together with applied AI fluency that lets you build GenAI and agentic capabilities directly into the products you deliver-consistently demonstrating your strong track record in delivering high-quality, outcome-focused solutions. The ideal candidate will be a dependable team player, collaborating with cross-functional teams to design, build, and ship products end to end, from concept through production.

Key Responsibilities

  • Outcome-Driven Accountability: Embrace and drive a culture of accountability for customer and business outcomes-and for the cost of achieving them. Develop engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality, lean designs and implementations, and owning the inference, token, and cloud cost of what you build.
  • Technical Leadership and Advocacy: Serve as the technical advocate for products, ensuring code integrity, feasibility, and alignment with business and customer goals. Participate in requirement analysis, component design, development, testing, integrations, and support.
  • Engineering Craftsmanship: Maintain accountability for code-design integrity, implementation fidelity to architecture and tech stack, quality, data, and ongoing maintenance and operations. Be hands-on, self-driven, and continuously learn new approaches, languages, and frameworks. Create technical specifications, and write high-quality, supportable, scalable code ensuring all quality KPIs are met or exceeded. Demonstrate collaborative skills to work effectively with diverse teams.
  • Customer-Centric Engineering: Develop lean engineering solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time.
  • Incremental and Iterative Delivery: Adopt a mindset that favors action and evidence over extensive planning. Utilize a leaning-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions.
  • Cross-Functional Collaboration and Integration: Work collaboratively with empowered, cross-functional teams including product management, experience, and delivery. Integrate diverse perspectives to make well-informed decisions that balance feasibility, viability, usability, and value. Foster a collaborative environment that enhances team synergy and innovation.
  • Advanced Technical Proficiency: Possess expertise in modern software engineering practices and principles, including AI and Agentic SSDLC to deliver daily product deployments using full automation from discovery to production to operations with all quality checks through SSDLC lifecycle. Learn to be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate understanding of the full lifecycle product development, focusing on continuous improvement and learning.
  • Domain Expertise: Quickly acquire domain-specific knowledge relevant to the business or product. Translate business/user needs, architectures, and UX/UI designs into technical specifications and code. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff.
  • Effective Communication and Influence: Exhibit exceptional communication skills, capable of articulating complex technical concepts clearly and compellingly. Inspire and influence teammates and product teams through well-structured arguments and trade-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives.
  • Engagement and Collaborative Co-Creation: Engage and collaborate with product engineering teams at all organizational levels, including customers as needed. Build and maintain constructive relationships, fostering a culture of co-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions.

The successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The Team

US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value/outcomes that leverages a progressive and responsive talent structure. As Deloitte's primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results and outcomes. It helps power Deloitte's success. It is the engine that drives Deloitte, serving many of the world's largest, most respected companies. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence.

Qualifications

Required: 

  • A bachelor's degree in computer science, software engineering, data science, machine learning, or related discipline. Experience is the most relevant factor.
  • 3+ years of experience with most of the following: Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, as well as unit testing frameworks.
  • 2+ years of experience building AI/ML and agentic applications, with hands-on GenAI experience across LLM integration (OpenAI, Anthropic, or open-source models), RAG pipelines, prompt engineering, vector databases, evaluations, and AI agent orchestration.
  • 2+ years of experience with cloud-native engineering, using FaaS, PaaS, or micro-services on any of the cloud hyperscalers such as Azure, AWS, or GCP, including their AI/ML services such as Azure OpenAI, AWS Bedrock, or Vertex AI, plus application-level infrastructure-as-code and cost-aware engineering (FinOps accountability).
  • Prior software engineering experience with the understanding of Business Context Diagrams (BCD), sequence/activity/state/entity relationship/data flow diagrams, OOP/OOD, data structures, algorithms, and code instrumentations, and AI-augmented spec-driven development.
  • Prior experience using methodologies & tools such as XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow, and agentic AI frameworks (e.g. LangFuse, LangSmith, or equivalent multi-agent orchestration tools) etc. to deliver high-quality products rapidly.
  • Candidates must be located within a commutable distance to one of the select locations available for this role
  • Ability to work in your local office at a minimum of 3 days per week
  • Ability to travel 10%, on average, based on the work you do and products you build.
  • Limited immigration sponsorship may be available.
  • Candidates must be located within a commutable distance to one of the select locations available for this role
  • Ability to work in your local office at a minimum of 3 days per week

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $88,600 to $181,900.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance. 

Qualifications:

As an Applied AI Engineer II, you will actively engage in your engineering craft, taking a hands-on approach to building and enhancing high-visibility, full-stack products that serve the business and its users. Your expertise will be pivotal in delighting customers and users, while driving tangible value across Deloitte's product and AI investments. You will leverage your engineering craftsmanship across full-stack software engineering and modern frameworks-together with applied AI fluency that lets you build GenAI and agentic capabilities directly into the products you deliver-consistently demonstrating your strong track record in delivering high-quality, outcome-focused solutions. The ideal candidate will be a dependable team player, collaborating with cross-functional teams to design, build, and ship products end to end, from concept through production.

Key Responsibilities

  • Outcome-Driven Accountability: Embrace and drive a culture of accountability for customer and business outcomes-and for the cost of achieving them. Develop engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality, lean designs and implementations, and owning the inference, token, and cloud cost of what you build.
  • Technical Leadership and Advocacy: Serve as the technical advocate for products, ensuring code integrity, feasibility, and alignment with business and customer goals. Participate in requirement analysis, component design, development, testing, integrations, and support.
  • Engineering Craftsmanship: Maintain accountability for code-design integrity, implementation fidelity to architecture and tech stack, quality, data, and ongoing maintenance and operations. Be hands-on, self-driven, and continuously learn new approaches, languages, and frameworks. Create technical specifications, and write high-quality, supportable, scalable code ensuring all quality KPIs are met or exceeded. Demonstrate collaborative skills to work effectively with diverse teams.
  • Customer-Centric Engineering: Develop lean engineering solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time.
  • Incremental and Iterative Delivery: Adopt a mindset that favors action and evidence over extensive planning. Utilize a leaning-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions.
  • Cross-Functional Collaboration and Integration: Work collaboratively with empowered, cross-functional teams including product management, experience, and delivery. Integrate diverse perspectives to make well-informed decisions that balance feasibility, viability, usability, and value. Foster a collaborative environment that enhances team synergy and innovation.
  • Advanced Technical Proficiency: Possess expertise in modern software engineering practices and principles, including AI and Agentic SSDLC to deliver daily product deployments using full automation from discovery to production to operations with all quality checks through SSDLC lifecycle. Learn to be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate understanding of the full lifecycle product development, focusing on continuous improvement and learning.
  • Domain Expertise: Quickly acquire domain-specific knowledge relevant to the business or product. Translate business/user needs, architectures, and UX/UI designs into technical specifications and code. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff.
  • Effective Communication and Influence: Exhibit exceptional communication skills, capable of articulating complex technical concepts clearly and compellingly. Inspire and influence teammates and product teams through well-structured arguments and trade-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives.
  • Engagement and Collaborative Co-Creation: Engage and collaborate with product engineering teams at all organizational levels, including customers as needed. Build and maintain constructive relationships, fostering a culture of co-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions.

The successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The Team

US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value/outcomes that leverages a progressive and responsive talent structure. As Deloitte's primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results and outcomes. It helps power Deloitte's success. It is the engine that drives Deloitte, serving many of the world's largest, most respected companies. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the...


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Benefits

Hours and flexibility

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