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Full Stack Ai Engineer Jobs in Ohio (NOW HIRING)

AI Engineer

Cincinnati, OH · On-site

$135K/yr

... full-stack AI solutions for our clients. Our deep industry, process and engineering expertise ... enables us to build an organization's unique context into technology systems that amplify human ...

Join our team as a Full Stack Engineer and be the hands-on technical owner for modern, data-aware applications ( including AI-powered features ) in a Microsoft/Azure environment. You'll set ...

Full-Stack Developers at CapTech are part of a capable, highly-motivated community who strive to ... Experience with a Varied AI Toolset- Claude code, CodeX, Opencode, OpenClaude * Preferred ...

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Full-Stack Developers at CapTech are part of a capable, highly-motivated community who strive to ... Experience with a Varied AI Toolset- Claude code, CodeX, Opencode, OpenClaude * Preferred ...

Full-Stack Developers at CapTech are part of a capable, highly-motivated community who strive to ... Experience with a Varied AI Toolset- Claude code, CodeX, Opencode, OpenClaude * Preferred ...

Create and maintain Rovo agents and leverage AI capabilities to enhance search, insights, and ... Proven experience as a Full Stack Developer or similar role * Strong proficiency in back-end ...

... AI solutions within enterprise applications on Amazon Web Services, Microsoft Azure, or Google ... As a Full Stack Engineer, you will design, develop, and enhance applications across frontend and ...

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Showing results 1-20

Full Stack Ai Engineer information

See Ohio salary details

$42.3K

$128.1K

$181.1K

How much do full stack ai engineer jobs pay per year?

As of Jul 3, 2026, the average yearly pay for full stack ai engineer in Ohio is $128,126.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,500.00 and $150,200.00 per year, depending on experience, location, and employer.

What is a Full Stack AI Engineer?

A Full Stack AI Engineer is a professional who develops and deploys artificial intelligence solutions across both the front-end and back-end of applications. They combine expertise in AI and machine learning with software engineering skills, allowing them to build, integrate, and maintain AI-powered features throughout the entire technology stack. Their responsibilities often include designing machine learning models, integrating them with APIs, and ensuring seamless user experiences on web or mobile platforms. Full Stack AI Engineers bridge the gap between data science and software development, enabling scalable and production-ready AI applications.

How do Full Stack AI Engineers typically collaborate with data scientists and front-end developers on AI-driven projects?

Full Stack AI Engineers often serve as the bridge between data scientists, who develop machine learning models, and front-end developers, who build user interfaces. They work closely with data scientists to understand the model requirements and deployment needs, and with front-end teams to ensure seamless integration of AI functionalities into applications. This collaboration requires effective communication skills and a clear understanding of both the technical and user experience aspects. Regular meetings, code reviews, and shared documentation are common practices to facilitate smooth teamwork and successful project outcomes.

What are the key skills and qualifications needed to thrive as a Full Stack AI Engineer, and why are they important?

To thrive as a Full Stack AI Engineer, you need strong programming skills (such as Python, JavaScript), understanding of machine learning algorithms, and experience with both front-end and back-end development, often supported by a degree in computer science or related fields. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (AWS, Azure, GCP), and containerization tools (Docker, Kubernetes) is typically required. Excellent problem-solving abilities, collaboration, and effective communication are standout soft skills in this role. These skills and qualifications enable the seamless integration of AI models into scalable applications, ensuring innovative and robust solutions.
What are popular job titles related to Full Stack Ai Engineer jobs in Ohio? For Full Stack Ai Engineer jobs in Ohio, the most frequently searched job titles are:
What cities in Ohio are hiring for Full Stack Ai Engineer jobs? Cities in Ohio with the most Full Stack Ai Engineer job openings:
Software Engineer II- Full-stack Developer

Software Engineer II- Full-stack Developer

Deloitte

Columbus, OH • On-site

Other

Posted 14 days ago


Deloitte rating

8.0

Company rating: 8.0 out of 10

Based on 89 frontline employees who took The Breakroom Quiz

71st of 146 rated financial services


Job description

Software Engineer II, AI & Engineering/Engineering as a Service

Position Summary

Software Engineer II, AI & Engineering/Engineering as a Service
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Engineering as a Service provides complete design, implementation, and technology operations, leveraging our core engineering expertise. We transform engineering teams, modernize technology, and deliver complex programs with a product engineering approach. Our flexible delivery models-traditional teams, pools, or pods-are tailored to each client's needs, offering engineering-led advisory, implementation, and operational capabilities to accelerate innovation.

Recruiting for this role ends on 8/1/26.

Work You'll Do

You are a hands-on full-stack developer who builds, tests, and ships reliable software as part of an agile engineering team. You contribute to the design and implementation of cloud-native applications and AI-augmented features, growing your technical depth across the stack. You will work alongside senior engineers to grow your technical skills while making meaningful contributions to our projects.

Key Responsibilities

  • Design, build, test, and maintain scalable full-stack features across front-end and back-end systems, following project engineering standards and conventions.
  • Write clean, well-documented, and maintainable code; participate in code reviews and contribute constructive technical feedback to peers.
  • Develop and maintain back-end microservices and scalable APIs; implement CI/CD pipelines, containerized workloads, and infrastructure-as-code as part of client engagements.
  • Integrate LLM APIs (OpenAI, Anthropic Claude, Google Gemini, Azure OpenAI) to build intelligent, context-aware features within client applications.
  • Implement agentic AI patterns - tool-calling agents, RAG pipelines, prompt chaining, and memory management - within full-stack applications under senior engineer guidance.
  • Collaborate on prototyping and iterating AI-powered workflows and automation solutions, contributing to the practice's growing AI delivery capability.
  • Participate actively in code reviews, providing and incorporating constructive feedback.
  • Collaborate with product managers, designers, and fellow engineers to translate requirements into technical solutions.
  • Identify, diagnose, and resolve bugs and performance issues in development and production environments.
  • Assist in breaking down technical requirements into well-scoped tasks and estimates.
  • Support junior engineers through pairing, knowledge sharing, and informal mentorship.
  • Write and maintain unit, integration, and end-to-end tests to ensure software reliability.
  • Participate in on-call rotations and contribute to incident response and post-mortems.

A 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

Qualifications

  • 4-6 years of professional software engineering experience with a focus on full-stack development.
  • 3+ years of full system lifecycle development experience, from requirements through production deployment.
  • 3+ years of hands-on full-stack experience with proficiency in at least one back-end language (Python, Java, .NET, Go, or Node.js) and a modern front-end framework (React, Angular, or Vue.js).
  • 2+ years in a client-facing development role, or a demonstrated ability to engage professionally with external stakeholders.
  • 2+ years building and consuming RESTful APIs and/or GraphQL services in a professional, team-based delivery environment.
  • Solid understanding of software engineering fundamentals including data structures, algorithms, and OOP principles.
  • Familiarity with relational or NoSQL databases and comfort writing efficient queries.
  • Working knowledge of version control systems (Git) and collaborative development workflows.
  • Understanding of testing practices and experience writing automated test suites.
  • Strong verbal and written communication skills with the ability to work effectively in a team environment.
  • Working knowledge of at least one major cloud platform (AWS, Azure, or GCP), including deployment, managed services, and basic infrastructure configuration.
  • Hands-on experience integrating at least one LLM platform or generative AI API (OpenAI, Azure OpenAI, Anthropic, Google Vertex AI, or equivalent).
  • Bachelor's degree in computer science, Engineering, or a related discipline - or equivalent professional experience.
  • Ability to travel up to 50% based on the work you do and the clients and industries/sectors you serv
  • Limited immigration sponsorship may be available

In addition, successful Software Engineer II candidates will have the following preferred background:

  • Experience with containerization and orchestration tools such as Docker and Kubernetes.
  • Familiarity with CI/CD pipelines and DevOps practices.
  • Experience working in an Agile/Scrum environment using tools like Jira or Linear.
  • Contributions to open-source projects or a personal portfolio demonstrating technical initiative.
  • Interest in mentoring others and taking on increased technical responsibility over time.
  • Industry-recognized cloud certifications (AWS Certified Developer, Azure Developer Associate, GCP Professional Developer, or equivalent).

Wages + Salary

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 $95,600 to $188,400

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:

Software Engineer II, AI & Engineering/Engineering as a Service

Position Summary

Software Engineer II, AI & Engineering/Engineering as a Service
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Engineering as a Service provides complete design, implementation, and technology operations, leveraging our core engineering expertise. We transform engineering teams, modernize technology, and deliver complex programs with a product engineering approach. Our flexible delivery models-traditional teams, pools, or pods-are tailored to each client's needs, offering engineering-led advisory, implementation, and operational capabilities to accelerate innovation.

Recruiting for this role ends on 8/1/26.

Work You'll Do

You are a hands-on full-stack developer who builds, tests, and ships reliable software as part of an agile engineering team. You contribute to the design and implementation of cloud-native applications and AI-augmented features, growing your technical depth across the stack. You will work alongside senior engineers to grow your technical skills while making meaningful contributions to our projects.

Key Responsibilities

  • Design, build, test, and maintain scalable full-stack features across front-end and back-end systems, following project engineering standards and conventions.
  • Write clean, well-documented, and maintainable code; participate in code reviews and contribute constructive technical feedback to peers.
  • Develop and maintain back-end microservices and scalable APIs; implement CI/CD pipelines, containerized workloads, and infrastructure-as-code as part of client engagements.
  • Integrate LLM APIs (OpenAI, Anthropic Claude, Google Gemini, Azure OpenAI) to build intelligent, context-aware features within client applications.
  • Implement agentic AI patterns - tool-calling agents, RAG pipelines, prompt chaining, and memory management - within full-stack applications under senior engineer guidance.
  • Collaborate on prototyping and iterating AI-powered workflows and automation solutions, contributing to the practice's growing AI delivery capability.
  • Participate actively in code reviews, providing and incorporating constructive feedback.
  • Collaborate with product managers, designers, and fellow engineers to translate requirements into technical solutions.
  • Identify, diagnose, and resolve bugs and performance issues in development and production environments.
  • Assist in breaking down technical requirements into well-scoped tasks and estimates.
  • Support junior engineers through pairing, knowledge sharing, and informal mentorship.
  • Write and maintain unit, integration, and end-to-end tests to ensure software reliability.
  • Participate in on-call rotations and contribute to incident response and post-mortems.

A 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

Qualifications

  • 4-6 years of professional software engineering experience with a focus on full-stack development.
  • 3+ years of full system lifecycle development experience, from requirements through production deployment.
  • 3+ years of hands-on full-stack experience with proficiency in at least one back-end language (Python, Java, .NET, Go, or Node.js) and a modern front-end framework (React, Angular, or Vue.js).
  • 2+ years in a client-facing development role, or a demonstrated ability to engage professionally with external stakeholders.
  • 2+ years building and consuming RESTful APIs and/or GraphQL services in a professional, team-based delivery environment.
  • Solid understanding of software engineering fundamentals including data structures, algorithms, and OOP principles.
  • Familiarity with relational or NoSQL databases and comfort writing efficient queries.
  • Working knowledge of version control systems (Git) and collaborative development workflows.
  • Understanding of testing practices and experience writing automated test suites.
  • Strong verbal and written communication skills with the ability to work effectively in a team environment.
  • Working knowledge of at least one major cloud platform (AWS, Azure, or GCP), including deployment, managed services, and basic infrastructure configuration.
  • Hands-on experience integrating at least one LLM platform or generative AI API (OpenAI, Azure OpenAI, Anthropic, Google Vertex AI, or equivalent).
  • Bachelor's degree in computer science, Engineering, or a related discipline - or equivalent professional experience.
  • Ability to travel up to 50% based on the work you do and the clients and industries/sectors you serv
  • Limited immigration sponsorship may be available

In addition, successful Software Engineer II candidates will have the following preferred background:

  • Experience with containerization and orchestration tools such as Docker and Kubernetes.
  • Familiarity with CI/CD pipelines and DevOps practices.
  • Experience working in an Agile/Scrum environment using tools like Jira or Linear.
  • Contributions to open-source projects or a personal portfolio demonstrating technical initiative.
  • Interest in mentoring others and taking on increased technical responsibility over time.
  • Industry-recognized cloud certifications (AWS Certified Developer, Azure Developer Associate, GCP Professional Developer, or equivalent).

Wages + Salary

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 f...


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