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Dejan Velimirovic
Full-Stack Software Developer
Previously at
Aleksa Stevic
Full-Stack Developer
Previously at
Experience our in-house-like model and hire proven Prompt Engineer in just 4 steps!
Share the roles, skills, experience and engagement type you're looking for. We’ll use this to match you with talent who truly fit your needs.
We handpick top candidates who are pre-vetted for technical skills, remote readiness, and who meet the requirements you set.
Review candidate profiles, ask questions, or schedule interviews. You stay in control of the final decision.
Once you’re ready, kick off the collaboration. With our Managed Hire full-time model, you get a 30-day risk-free trial.
We’ll match you with vetted Prompt Engineer that suits your requirements. It typically takes 2 working days, allowing you to focus on growth instead of hiring.
Our rigorous vetting process combines Advanced AI assessments with expert human evaluation to ensure only top talent makes it through.
Our 30-day trial lets you work with experts before a longer-term commitment. Plus, cancel or replace the talent anytime without fee.
We handle everything from contracts and compliance to payments and performance tracking, allowing you to focus on your project.
Prompt engineers are at the core of making AI usable, accurate, and aligned with business needs. As AI products become mainstream, having someone who can direct LLM behavior is critical. These professionals fine-tune natural language inputs to control and improve AI model outputs. Hiring prompt engineers enables better performance from tools like ChatGPT, Claude, and Gemini—boosting productivity and output quality across departments.
Prompt engineering has evolved beyond experimentation and is now embedded in production workflows. Engineers in this field shape the tone, accuracy, and structure of AI output. The role is essential for:
Chatbots and virtual assistants that handle complex interactions
Content generation pipelines for marketing, writing, and coding
Data querying interfaces using natural language
Agent workflows using tools like LangChain or LlamaIndex
With AI models often behaving unpredictably, prompt engineers give companies a tactical edge. They create consistency, reduce errors, and increase product velocity. Prompt engineers give companies tighter control over generative AI behavior. They improve reliability, reduce hallucination, and shorten iteration cycles—giving your business faster AI adoption with better results.
Prompt engineers are the translators between business intent and AI action. They design, test, and optimize instructions for large language models (LLMs). They use tools like OpenAI's playground, Anthropic's console, and structured templates to guide model behavior. Their role blends UX, product design, and technical writing with an understanding of AI systems.
Prompt engineers bring different levels of autonomy and specialization. Here’s what to expect at each tier:
Use templates to create prompt drafts
Evaluate output consistency and identify issues
Document test results and edge cases
Design multi-step and role-based prompts for business use cases
Test prompts across models (GPT-4, Claude, Gemini)
Collaborate with developers and product teams on prompt integration
Lead athe rchitecture of prompt workflows and AI logic
Own prompt libraries, versioning, and performance benchmarking
Build reusable prompt strategies across teams and tools
Prompt engineers require varying levels of direction depending on experience. Junior engineers need a clear framework and iterative feedback. Mid-levels can operate independently across teams. Senior engineers define strategies and mentor others on prompt design, safety, and performance.
A strong understanding of how LLMs work is essential to effective prompt design. Engineers should know how these models interpret context, manage memory, and process structured vs. unstructured inputs. Understanding how large language models interpret context, format inputs, and handle memory is critical. Familiarity with token limits, embeddings, and role messages is essential.
Prompt engineers should master several foundational strategies to shape AI behavior reliably. These include:
Zero-shot, few-shot, and chain-of-thought prompting
System instruction tuning for assistant behavior control
Role-play and tool-use prompting for structured agent flows
Prompts must be measured and improved over time. Engineers should apply rigorous testing across multiple models and output types.
Human evaluationsa using rating rubrics for relevance and clarity
Output regression testing for prompt consistency across model versions
Model comparison across GPT, Claude, and open-source tools
These are the environments where prompts are tested, deployed, and optimized. Familiarity here means faster iteration and better outcomes.
OpenAI Playground / Anthropic Console – For testing LLM prompts
LangChain / LlamaIndex – For chaining prompts and retrieval-based flows
Datasets & Benchmarks – BLEU, ROUGE, GPTScore, or human metrics
Prompt engineers often work inside technical products, not just in research. They need the skills to ship safely and collaboratively.
Work with dev teams to implement prompts in production systems
Use Git or Notion for prompt version control
Coordinate with QA to track bugs and prompt failures
Great prompt engineers are strong communicators and experimenters. Their work sits between design, dev, and end-user experience.
Clear writing – Instructions must be precise, readable, and reusable
Experimentation – Comfortable iterating, testing, and comparing prompts
Cross-functional collaboration – Work with devs, designers, and PMs
More: Universal Behavioral Competencies | Teamwork Template
Hiring models for prompt engineers depends on project complexity, team structure, and time-to-market needs. Here’s how they compare:
Freelancers are ideal for audit projects or rapid experimentation with LLMs. They are a good fit for early-stage or experimental work.
Pros: Low cost, fast engagement
Cons: Inconsistent output, no long-term ownership
If AI is core to your product, full-time prompt engineers bring sustained quality and system knowledge. Full-timers contribute to long-term quality and scale prompt systems.
Pros: Deep product knowledge, better collaboration
Cons: Smaller talent pool, competitive market
Agencies are ideal for product companies needing fast delivery with minimal overhead. You get proven talent and admin handled.
Pros: Pre-vetted experts, flexible contracts, no admin overhead
Cons: Higher hourly rates than freelancers
Top prompt engineers work in emerging AI communities and often build open-source or shared prompt libraries. Here's where to look:
These platforms help you access pre-qualified talent with LLM experience.
FatCat Remote – Pre-vetted prompt engineers for LLM and GenAI products
Many skilled prompt engineers are active contributors in these spaces.
OpenAI Community, Prompt Engineering Discord, Hugging Face Spaces
GitHub prompt repos, r/PromptEngineering, AI alignment circles
Ask product and research leaders working on AI initiatives. Prompt engineers often come from writing, UX, or dev backgrounds.
Prompt engineers need both analytical precision and creative thinking. Your process should reflect both.
A structured prompt design challenge reveals a candidate’s skill and approach.
Assign a structured prompting task (e.g., build a summarization, chatbot, or search agent prompt)
Review for consistency, output quality, and iteration reasoning
Use these to probe for real-world understanding and prompt architecture expertise.
How do you guide an LLM to return structured data (e.g., JSON)?
What is the role of few-shot examples?
How do you handle hallucinations in LLMs?
Compare GPT-4 and Claude for summarization or reasoning.
How would you debug a prompt that yields inconsistent tone?
Describe a time when a prompt failed in production.
How do you maintain prompt libraries across teams?
What are the limitations of retrieval-augmented generation?
Explain how token limits affect prompt design.
How do you balance creativity vs. control in prompt output?
These questions reveal adaptability, collaboration, and product thinking.
Tell me how you collaborate with non-technical teammates.
Describe a time you improved prompt performance through iteration.
Learn more:
Prompt engineering is an emerging field with strong demand. Compensation varies based on LLM expertise and deployment experience.
Junior: $90,000–$120,000
Mid-Level: $120,000–$160,000
Senior: $160,000–$200,000+
Junior: $40–$60/hour
Mid-Level: $60–$90/hour
Senior: $90–$130/hour
This region offers high-quality LLM talent with excellent communication.
$45–$90/hour – Fluent in English and highly skilled in LLM usage
Compare: Developer Rates Comparison
Prompt engineering unlocks real business outcomes from AI tools. It’s about getting better results, faster and cheaper.
Better AI quality without model retraining
More consistent outputs across tools and users
Faster product iteration and better time-to-value for GenAI features
Reduced errors and hallucinations in production
Any business embedding generative AI benefits from skilled prompt design. These industries rely on it the most:
SaaS – AI copilots, user-facing generative tools, automation
Legal & Compliance – Summarization, document parsing, citation generation
Content & Marketing – SEO writing, copy tuning, brand tone control
FatCat Remote helps you hire high-quality prompt engineers fast. We handle the hiring risk so you can focus on AI product delivery.
Speed: Start with a prompt engineer in 48 hours
Trial: 30-day no-risk trial
Vetted Talent: Only engineers with proven LLM and prompt ops experience
Flexibility: Hire part-time, full-time, or on demand
Compliance: We handle contracts, IP, and payroll globally
Pricing: Flexible hiring models that suits your business needs
Our work-proven Prompt Engineers are ready to join your remote team today. Choose the one that fits your needs and start a 30-day trial.
Read answers to the most common questions about hiring Prompt Engineers.
Companies hire prompt engineers to optimize their interactions with AI models and ensure that these models deliver accurate, relevant, and efficient results. Here are some specific reasons why companies might hire prompt engineers:
Maximize AI Capabilities: AI models are powerful tools, but they require well-crafted prompts to deliver their full potential. Prompt engineers help in crafting these inputs so that the models work more effectively.
Increase Efficiency: By designing effective prompts, businesses can streamline operations, enhance productivity, and reduce time spent on trial-and-error approaches in AI applications.
Improve Accuracy and Relevance: Prompt engineers help ensure that the AI models provide outputs that are precise and aligned with the company’s needs, which improves the reliability and usefulness of the AI’s output.
Customization and Personalization: Companies might want AI outputs tailored to specific brand voices or tailored customer interactions. Prompt engineers can create prompts that achieve these personalized results.
Cost Optimization: Using AI efficiently can reduce costs, and having prompt engineers can further optimize these savings by minimizing the need for extensive manual adjustments or refinements.
Innovation and Development: Prompt engineers can explore new ways to utilize AI within a company, leading to innovative solutions and competitive advantages.
In essence, prompt engineers play a vital role in harnessing the potential of AI technologies effectively and aligning them with business goals and strategies.
The 30-day trial period for hiring an rompt engineer on FatCat Remote allows clients to test our service with minimal risk. During this trial, which lasts up to 160 working hours or 30 calendar days (whichever comes first), you have the flexibility to cancel the engagement or request a developer replacement without significant financial consequences. To cancel, you must provide a detailed written notice (via email) at least five working days before the cancellation date, outlining reasons for dissatisfaction such as unmet goals, technical issues, or poor communication.
To hire a Prompt Engineer at FatCat Remote, simply fill out our request form with your project needs. We will then connect you with a qualified Prompt Engineer who can best meet your requirements, whether for short-term projects or ongoing support.
Our Prompt Engineers stand out due to their deep understanding of AI models and their ability to craft effective, efficient prompts that drive optimal results. They have extensive experience working with cutting-edge AI technologies and know how to tailor prompts for various applications, ensuring high-quality outputs every time.
Yes, we offer both hourly and project-based options for hiring Prompt Engineers. Whether you need ongoing assistance or help with a specific project, we can provide a flexible solution that suits your needs.
Prompt engineering is crucial because it directly influences the quality and relevance of the AI-generated content. Well-crafted prompts enable AI models to produce more accurate, insightful, and useful results, helping businesses save time and resources while maximizing the impact of AI-driven processes.
Prompt engineering refers to the process of designing and refining prompts to effectively elicit desired responses from language models like me. It involves crafting inputs in a way that guides the model to generate relevant, accurate, and useful outputs. This can include specifying the context, style, or structure of the response and may also involve iterating on prompts to improve results.
The practice is used to optimize interactions with AI and can be applied in various fields such as software development, customer service, content creation, and more. Prompt engineering is an essential skill for getting the most out of AI models and ensuring they perform tasks as intended