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Prompt Engineer Jobs in Orlando, FL (NOW HIRING)

Tror AI for everyone

AI Engineer

Lake Mary, FL · On-site

Prompt Engineering * Tokenization, context windows * Model selection * Handling hallucinations and grounding responses. * Retrieval-Augmented generation (RAG) * Document Ingestion and preprocessing

Holland & Knight

AI Legal Engineer

Orlando, FL · On-site

... prompt design, retrieval pipelines, document templates, evaluations, and guardrails with practice-group-facing training, enablement, and change management. The AI Legal Engineer will serve as a ...

Disney Experiences

Sr Software Engineer

Orlando, FL · On-site

$135K - $181K/yr

Hands-on building and deploying LLM-based applications, including prompt engineering and fine-tuning * Experience with RAG (Retrieval Augmented Generation), vector databases, and embeddings

The Walt Disney Company

Sr Software Engineer

Orlando, FL · On-site

$135K - $181K/yr

Hands-on building and deploying LLM-based applications, including prompt engineering and fine-tuning * Experience with RAG (Retrieval Augmented Generation), vector databases, and embeddings

247Hire

Machine Learning Engineer

Orlando, FL · On-site

$125 - $150/hr

Research and implement prompt engineering and in‑context learning optimization * Create novel architectures for specific generative tasks * Production AI/ML Systems: Design A/B testing frameworks ...

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Prompt Engineer information

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How much do prompt engineer jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for prompt engineer in Orlando, FL is $43.96, according to ZipRecruiter salary data. Most workers in this role earn between $33.41 and $56.78 per hour, depending on experience, location, and employer.

What is a prompt engineer?

A Prompt Engineer is a professional who designs, refines, and optimizes prompts to improve interactions with AI models, such as ChatGPT. Their role involves understanding model behavior, crafting precise queries, and experimenting with phrasing to achieve desired outputs. They may work in AI research, software development, or content generation to maximize AI efficiency. Strong skills in language, logic, and sometimes coding are essential for success in this role.

What does a prompt engineer do?

A typical day for a Prompt Engineer involves designing, testing, and refining prompts to enhance the performance of AI language models, often collaborating closely with data scientists, software engineers, and product managers. You might analyze the results of model outputs, integrate user or stakeholder feedback, and iterate on prompt strategies to solve diverse business challenges. Your role will usually include documentation, troubleshooting, and keeping up with the latest advances in AI technologies. Expect a mix of independent work and regular team meetings in a dynamic, fast-evolving environment focused on innovation and improvement.

What skills and qualifications are needed to be a prompt engineer?

To thrive as a Prompt Engineer, you need a strong grasp of natural language processing (NLP), machine learning concepts, and experience crafting effective prompts for large language models, usually supported by a technical degree or relevant experience. Familiarity with tools such as OpenAI's API, Hugging Face, or other AI platforms, as well as knowledge of programming languages like Python, is highly valuable. Creative thinking, analytical problem-solving, and cross-functional communication skills help differentiate top candidates in this field. These abilities are crucial for optimizing AI outcomes and ensuring collaboration with both technical and non-technical teams.

Are prompt engineers still in demand?

Prompt engineers are currently in demand as organizations seek professionals skilled in designing effective prompts for AI language models. The role often requires knowledge of natural language processing, machine learning, and familiarity with AI tools like GPT. Demand is expected to grow as AI integration expands across industries.

How much do prompt engineers make?

Prompt engineers typically earn between $80,000 and $150,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in AI and machine learning can command higher salaries, especially in tech hubs or companies investing heavily in AI development.

What exactly is prompt engineer work?

A prompt engineer designs and optimizes prompts used to interact with AI language models, ensuring accurate and relevant responses. This role involves understanding AI behavior, crafting clear instructions, and often requires knowledge of machine learning, programming, or data analysis.

What are popular job titles related to Prompt Engineer jobs in Orlando, FL?

For Prompt Engineer jobs in Orlando, FL, the most frequently searched job titles are:

What job categories do people searching Prompt Engineer jobs in Orlando, FL look for?

The top searched job categories for Prompt Engineer jobs in Orlando, FL are:

What cities near Orlando, FL are hiring for Prompt Engineer jobs?

Cities near Orlando, FL with the most Prompt Engineer job openings:

Prompt Engineer jobs near you
Infographic showing various Prompt Engineer job openings in Orlando, FL as of August 2026, with employment types broken down into 7% Internship, 66% Full Time, 8% Part Time, and 19% Contract. Highlights an 81% In-person, and 19% Remote job distribution, with an average salary of $91,428 per year, or $44 per hour.

AI Engineer

Tror AI for everyone

Lake Mary, FL • On-site

Contractor

Re-posted 26 days ago

Job description

Job Role: AI Engineer

Job Location: Lake Mary, FL (3 Days Onsite)

Job Type: Contract

Need 11+ Years of experience resumes.

Job Description:

  • Python Intermediate/Advanced - async programming
  • API Development - Fast API
  • Writing production-grade, scalable code
  • Testing (unit, integration)
  • Debugging complex distributed system
  • LLM Fundamentals
  • Prompt Engineering
  • Tokenization, context windows
  • Model selection
  • Handling hallucinations and grounding responses.
  • Retrieval-Augmented generation (RAG)
  • Document Ingestion and preprocessing
  • Chunking Strategies (semantic, recursive, sliding window)
  • Embeddings
  • Vector database - pgvector
  • Hybrid search (keyword (BM25) + semantic)
  • Re-ranking and relevance tuning. 
  • Agentic Frameworks and Orchestration.
  • Multi-agent coordination
  • Memory Management
  • Workflow orchestration
  • Evaluation and Observability
  • LLM Evaluation metrics (accuracy, faithfulness and relevance)
  • Prompt/version tracking
  • Logging and Tracking
  • Human in the loop (HITL) feedback loops
  • Deployment and MLOPS
  • Containerization (Docker)
  • CI/CD pipelines
  • Monitoring