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Full Time Prompt Engineering Jobs in Florida (NOW HIRING)

Virtusa

Architect (ATC)

Tampa, FL · On-site

... is a full-time position and you will be required to work from the clients office The ideal ... of prompt engineering implementation exposure to LLM agents like LangChain vector databases ...

Virtusa

Architect (ATC)

Tampa, FL · On-site

... is a full-time position and you will be required to work from the clients office The ideal ... of prompt engineering implementation exposure to LLM agents like LangChain vector databases ...

Kubikware

AI Engineer (Latam, Remote)

Aventura, FL · On-site +1

Strong understanding of prompt engineering and AI tool orchestration * Experience developing ... Fully remote position (LATAM) * Full-time position * Opportunity to work on cutting-edge AI ...

Royal Caribbean Group

AI Engineer

Miami, FL · On-site

... full time AI Engineer reporting to the Senior Manager, Data Science . This position is onsite and ... prompt engineering, and agent workflows where they improve reuse, quality, and enterprise ...

The Walt Disney Company

Sr Software Engineer

Orlando, FL

$135K - $181K/yr

Hands-on building and deploying LLM-based applications, including prompt engineering and fine ... Software Engineer Employment Type: Full time Primary City, State, Region, Postal Code: Glendale, CA ...

The Florida Panthers

Automation Engineer

Sunrise, FL · On-site

Exempt Employment Type: Full-Time On-Site Location: Florida Panthers Hockey Club Position Overview ... Exposure to LLM applications, prompt engineering, or AI agent frameworks. * Experience producing ...

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Full Time Prompt Engineering information

What is the difference between Full Time Prompt Engineering vs Data Scientist?

AspectFull Time Prompt EngineeringData Scientist
Required CredentialsBachelor's in CS, AI, or related; experience with NLP and AI toolsBachelor's/Master's in CS, Statistics, or related; experience with data analysis and modeling
Work EnvironmentTech companies, AI startups, remote or office-basedResearch labs, tech firms, finance, healthcare; often office-based or remote
Industry UsageAI development, NLP projects, chatbot designData analysis, predictive modeling, business insights
Common Search/ComparisonYesYes

Full Time Prompt Engineering focuses on designing and optimizing prompts for AI models, primarily in NLP tasks. Data Scientists analyze data to build models and generate insights. While both roles require technical skills and often overlap in AI projects, Prompt Engineers specialize in prompt design, whereas Data Scientists focus on data analysis and modeling.

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

To thrive as a Full Time Prompt Engineer, you need a solid background in computer science, natural language processing, and machine learning, often supported by a relevant degree or experience with AI models. Familiarity with tools like Python, large language model APIs (such as OpenAI or Anthropic), and prompt optimization frameworks is typically required. Strong analytical thinking, creativity, and clear written communication are crucial soft skills for designing effective prompts and collaborating with multidisciplinary teams. These skills ensure the development of high-performing AI solutions and the ability to translate user needs into actionable, efficient prompts.

What are some common challenges faced by Full Time Prompt Engineers, and how can they overcome them?

Full Time Prompt Engineers often encounter the challenge of crafting prompts that consistently yield accurate, relevant, and unbiased responses from AI models. Adapting to rapidly evolving AI technologies and understanding nuanced model behaviors can also be demanding. Overcoming these challenges requires staying current with the latest AI developments, collaborating closely with data scientists and developers, and continuously testing and refining prompts based on feedback and performance metrics. Embracing a mindset of experimentation and regular communication within cross-functional teams is key to success in this dynamic field.

What is prompt engineering?

Prompt engineering is the practice of designing, testing, and refining the inputs (prompts) given to artificial intelligence models, such as large language models, to achieve specific and desirable outputs. This role involves understanding how AI models interpret language and using that knowledge to create prompts that guide the model toward accurate, relevant, or creative responses. Prompt engineers often work closely with developers, data scientists, and product teams to optimize AI performance for various applications. As AI models become more advanced, prompt engineering has become an essential skill for leveraging their full potential.
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Full Time Prompt Engineering jobs near you

Fulltime - Python Developer - Generative AI & Cloud (Agentic AI)

Futran Tech Solutions Pvt. Ltd.

Tampa, FL • On-site

$47.50 - $65.50/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Role: Python Developer - Generative AI & Cloud (Agentic AI)
Location: Tampa, FL and Jersey City, NJ (3 Days onsite/week)
Fulltime
Job Description:
• Strong hands-on experience in Python development for AI/ML workloads
• Practical exposure to Generative AI models (LLMs, transformers, diffusion models)
• Understanding/practical knowledge on Agentic AI frameworks
• Experience working with cloud-native AI services on GCP/AWS/Azure
• Understanding of privacy-preserving ML techniques and responsible AI practices
• Experience working with prompt engineering including tool calling and guardrails
• Familiarity with MLOps pipelines, model deployment, and monitoring
• Ability to design scalable, production-ready AI solutions
Key Responsibilities:
• Design, develop, and optimize Python-based AI/ML applications
• Build, fine-tune, and deploy Generative AI solutions using modern frameworks
• Integrate AI models with cloud platforms and managed AI services
• Develop scalable APIs and microservices supporting AI workloads
• Collaborate with data scientists, ML engineers, and product teams to deliver end-to-end solutions
• Implement CI/CD pipelines ensuring code quality, testing, and security
• Monitor and optimize performance, reliability, and cost of cloud AI deployments
• Ensure compliance with data privacy, security, and responsible AI guidelines

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