ZipRecruiter

Log In

1

Full Stack Ai Engineer Jobs in Florida (NOW HIRING)

Fortegra

Senior Full Stack AI Engineer

Jacksonville, FL · On-site

$110K - $190K/yr

Fortegra is building a next-generation engineering capability focused on AI-accelerated development and rapid application delivery. We are seeking Full Stack Engineers who thrive in fast-moving ...

Fortegra

AI Engineer - Full Stack

Jacksonville, FL · On-site

Strong full-stack engineering skills, including proficiency in React-based web development and the ability to review, understand, and refine AI-generated code. Experience designing or implementing ...

Lennar Homes

Principal Full Stack Engineer

Miami, FL · On-site

Principal Full Stack Engineer We are Lennar Lennar is one of the nation's leading homebuilders ... Drive AI engineering strategy across the stack, authoring RFCs and leading design reviews that ...

Lennar

Principal Full Stack Engineer

Miami, FL · On-site

Principal Full Stack Engineer We are Lennar Lennar is one of the nation's leading homebuilders ... Drive AI engineering strategy across the stack, authoring RFCs and leading design reviews that ...

Lennar

Principal Full Stack Engineer

Miami, FL · On-site

Principal Full Stack Engineer We are Lennar Lennar is one of the nation's leading homebuilders ... Drive AI engineering strategy across the stack, authoring RFCs and leading design reviews that ...

MDG Solutions

Full Stack Engineer

Boca Raton, FL · On-site

We are looking for a Full Stack Software Engineer who builds for the web end to end and owns what ... AI-assisted development is an established part of how this team works and a firm requirement of the ...

next page

Showing results 1-20

All JobsFull Stack Ai Engineer JobsFull Stack Ai Engineer Jobs in Florida

Full Stack Ai Engineer information

See Florida salary details

$33.3K

$100.7K

$142.4K

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

As of Jun 28, 2026, the average yearly pay for full stack ai engineer in Florida is $100,713.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,900.00 and $118,100.00 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 Florida? For Full Stack Ai Engineer jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Full Stack Ai Engineer jobs in Florida look for? The top searched job categories for Full Stack Ai Engineer jobs in Florida are:
What cities in Florida are hiring for Full Stack Ai Engineer jobs? Cities in Florida with the most Full Stack Ai Engineer job openings:
Full Stack Ai Engineer jobs near you
Infographic showing various Full Stack Ai Engineer job openings in Florida as of June 2026, with employment types broken down into 100% Full Time. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $100,713 per year, or $48.4 per hour.

Fulltime - Senior Full Stack AI Engineer

Futran Tech Solutions Pvt. Ltd.

Tampa, FL • On-site

Full-time

Posted 21 days ago

Job description

Role: Senior Full Stack AI Engineer
Location: Tampa, FL (3 Days onsite/ week)
Fulltime
Requirements:
• Extensive Experience: Minimum of 5 years of proven software development experience.
• Modern Application Development:
• In-depth knowledge of modern application architecture principles.
• Clear understanding of Data Structures and Object Oriented Principles
• Practical experience with Artificial Intelligence (AI) tools for enhancing development workflows.
• Proficiency in Microservices frameworks Event-Driven Services, and Cloud-Native Application
Development.
• Multiple years of experience on Service Oriented and Microservices architectures, including
REST and GraphQL implementations
• Strong Python Engineering: Expert-level proficiency in Python and relevant libraries (e.g.,
FastAPI, Pydantic, PyTorch, HuggingFace Ecosystem).
• Experience with LLM-based pipelines: Proven experience in building and deploying applications
using Large Language Models.
• Knowledge of vector search and embeddings: Hands-on experience with vector databases and
developing embedding pipelines.
• RAG Concepts: Strong understanding and practical experience with Retrieval-Augmented
Generation (RAG) frameworks (e.g., LangChain, LlamaIndex).
• GenAI Tuning: Experience with generative AI tuning techniques such as QLORA, LORA, and PEFT.
• MCP Experience: Practical experience with Agentic Workflows, and Model Context Protocol
(MCP) for enhancing development workflows
• NLP Expertise: Strong hands-on experience with NLP techniques such as text classification,
summarization, and topic modeling.
• Full Stack Proficiency: Demonstrated ability to design, develop, and maintain both front-end and back-
end components of robust web applications.
Personal - Individual Use
• Front-End Development: Strong expertise in developing intuitive user interfaces using contemporary
JavaScript frameworks (e.g., React), HTML5, and CSS.
• Back-End Development: Solid experience in developing server-side logic and APIs using languages
Python, Java, or similar.
• Database Expertise: Comprehensive knowledge of SQL and PL/SQL, with a deep understanding of
Relational Database Management Systems (RDBMS), particularly Oracle.
• API Development: Proven capability in designing, developing, and implementing high-performance
RESTful APIs leveraging appropriate frameworks and technologies.
• CI/CD and DevOps:
• Proficiency with Continuous Integration/Continuous Deployment (CI/CD) pipelines and tools for
building (e.g., Maven, Gradle) and deploying code (e.g., Docker, Jenkins, OpenShift).
• Experience with AWS is considered a significant advantage.
• Agile Methodologies: Practical experience working within Agile development methodologies and utilizing
project management tools such as JIRA.
• Testing Automation: Ability to develop and automate comprehensive unit, integration, and end-to-end
tests to ensure code quality.
• Version Control: Solid understanding and practical experience with code versioning tools, including
GitHub Enterprise.

Apply