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Gen Ai Software Developer Jobs in Florida (NOW HIRING)

As a Mid-Level AI Software Developer, you will own and deliver production-ready AI features end-to-end. You will work across LLM integrations, retrieval-augmented generation (RAG) systems, and AI ...

Python Gen AI Developer

Jacksonville, FL ยท On-site

$50 - $62/hr

Python Gen AI Developer At NTT DATA, we know that with the right people on board, anything is possible. The quality, integrity, and commitment of our employees have been key factors in our company ...

Gen AI Technology Lead

Tampa, FL ยท On-site

$113K - $170K/yr

Extensive experience with Gen-AI frameworks such as LangChain, LangGraph, LlamaIndex, and Hugging ... Extensive experience system analysis and in programming of software applications * Experience in ...

Gen AI Engineer Location: Sunrise, FL or Phoenix, AZ Hybrid role - In a week three days onsite. Experience - 6 to 8 Years We are seeking a Machine Learning Engineer to design, build, and deploy ...

Software Engineering Job Type: Contractor (10-15 hours per week) Location: Remote Job Summary: We are looking for experienced software engineers to help train and evaluate next-generation AI systems ...

AI Software Engineer Miami (Hybrid) About our crew Boats Group is the leading digital marketplace ... Experience with modern DevOps practices, version control (Git), and CI/CD pipelines. * A curious ...

Sr Gen AI Developer

Tampa, FL ยท On-site

$49.50 - $65.50/hr

Senior Generative AI Developer Location: Tampa, FL (Hybrid - 3 Days onsite) We are seeking an ... Required Skills & Qualifications: * 8+ years of professional experience in software development and ...

Software Engineering Job Type: Contractor (10-15 hours per week) Location: Remote Job Summary: We are looking for experienced software engineers to help train and evaluate next-generation AI systems ...

AI Software Engineer Miami (Hybrid) About our crew Boats Group is the leading digital marketplace ... Experience with modern DevOps practices, version control (Git), and CI/CD pipelines. * A curious ...

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Gen Ai Software Developer information

How do Gen AI Software Developers typically collaborate with data scientists and product managers during the development process?

Gen AI Software Developers regularly work alongside data scientists to translate machine learning models into scalable, production-ready applications. They collaborate closely with product managers to understand user requirements and ensure that AI-powered features align with business goals. This teamwork often involves participating in cross-functional meetings, iterative feedback cycles, and joint problem-solving sessions to address technical challenges and optimize model performance. Clear communication and a shared understanding of project objectives are essential for success in this collaborative environment.

What are the key skills and qualifications needed to thrive as a Gen AI Software Developer, and why are they important?

To thrive as a Gen AI Software Developer, you need strong programming skills (especially in Python), a background in computer science or a related field, and expertise in machine learning and deep learning principles. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud platforms (such as AWS or Azure), and knowledge of version control systems are typically required, along with certifications in AI or data science being advantageous. Creative problem-solving, collaboration, and effective communication help developers work across technical and non-technical teams and drive innovation. These skills ensure the development of robust, scalable AI solutions that address real-world needs and integrate seamlessly within organizations.

What is a Gen AI Software Developer?

A Gen AI Software Developer is a professional who designs, builds, and maintains software systems that leverage generative artificial intelligence models, such as large language models (LLMs) or generative adversarial networks (GANs). Their work often involves training, fine-tuning, and deploying AI models to generate content, automate tasks, or enhance user experiences in applications. They need strong programming skills, a solid understanding of machine learning principles, and familiarity with AI frameworks. Gen AI Software Developers collaborate with data scientists, engineers, and product teams to deliver innovative AI-driven solutions. As generative AI becomes more prevalent, these developers play a key role in shaping the future of software development.

What is the difference between Gen Ai Software Developer vs Machine Learning Engineer?

AspectGen Ai Software DeveloperMachine Learning Engineer
Required CredentialsBachelor's in CS, AI, or related; experience with AI frameworksBachelor's or higher in CS, Data Science, or related; strong programming skills
Work EnvironmentTech companies, startups, AI-focused teamsResearch labs, tech firms, AI/ML departments
Employer & Industry UsageAI product development, software solutionsModel development, data analysis, AI system deployment
Common Search & ComparisonFocuses on AI application development in softwareFocuses on building and optimizing ML models

While both roles involve AI and require programming skills, Gen Ai Software Developers primarily focus on creating AI-powered software applications, whereas Machine Learning Engineers specialize in designing, building, and optimizing machine learning models. The roles often overlap but differ in their core focus and typical work environments.

What cities in Florida are hiring for Gen Ai Software Developer jobs? Cities in Florida with the most Gen Ai Software Developer job openings:
AI Software Developer

AI Software Developer

Advantive

Tampa, FL โ€ข On-site

Other

This job post hasย expired 1 day ago.ย Applications are no longer accepted.


Job description

We are building the next generation of intelligent enterprise softwareโ€”platforms that think, adapt, and automate alongside the people who use them. Our AI & Business Intelligence team delivers conversational assistants, intelligent search, data-driven agents, predictive analytics, and workflow automation that transform how businesses operate.

As a Mid-Level AI Software Developer, you will own and deliver production-ready AI features end-to-end. You will work across LLM integrations, retrieval-augmented generation (RAG) systems, and AI-driven workflows, building reliable backend services and applications that directly impact enterprise customers.

This role is ideal for an experienced software engineer who has shipped AI-powered features in production and is ready to take full ownership of feature delivery, including performance, reliability, and cost efficiency. We are looking for candidates who are practical, collaborative, and comfortable making sound engineering trade-offs in real production environments.

Responsibilities:

  • Design and deliver AI-powered product features end-to-end, from requirements and solution design through implementation, testing, deployment, and post-release optimization.
  • Build and maintain retrieval-augmented generation (RAG) workflows that ground LLM responses in enterprise data, including application-side retrieval design, response grounding, and retrieval tuning.
  • Implement application and backend services that integrate large language models and AI services into enterprise products through well-designed APIs and service boundaries.
  • Develop AI-assisted workflows and agent-style automations that interact safely with enterprise data, product capabilities, and external systems.
  • Create and maintain automated tests, evaluation practices, monitoring, and operational runbooks for AI-enabled features so reliability is designed in from the start.
  • Analyze production behavior, user feedback, and telemetry to improve answer quality, latency, reliability, and cost efficiency. Make and communicate trade-offs between model quality, latency, and cost.
  • Collaborate with product, UX, data, QA, and platform teams to define use cases, acceptance criteria, evaluation methods, and rollout plans.
  • Contribute to engineering standards through code reviews, technical design discussions, and shared best practices focused on testing, observability, security, and performance.

What Success Looks Like

  • Owns AI-powered features end-to-end in production, from implementation through post-release improvement.
  • Uses telemetry, user feedback, and evidence to improve answer quality, latency, reliability, and cost efficiency.
  • Makes sound trade-offs between quality, latency, and cost, and can clearly explain those decisions to technical and non-technical stakeholders.
  • Delivers reliable, well-tested features with appropriate monitoring, evaluation, and operational readiness.
  • Collaborates effectively across engineering, product, UX, data, QA, and platform partners to ship high-quality releases.