Hire the Best Prompt Engineers

More than 3,000 reviews on G2
Rating is 4.5 out of 5.
4.5/5
of Upwork by G2 peer reviewers
Kamran Ali S.

Gilgit, Pakistan

$15/hr
4.9
35 jobs

I help startups, SaaS companies, and e-commerce brands turn data and AI into real business results — smarter predictions, faster automation, and high-impact AI content. With 100% Job Success Score and Top Rated Badge across 26 projects on Upwork, I deliver production-ready solutions across five high-growth AI and data disciplines: MACHINE LEARNING ENGINEERING I design, train, and deploy predictive models for churn prediction, demand forecasting, lead scoring, recommendation engines, and anomaly detection. Stack: Python, Scikit-learn, XGBoost, PyTorch, TensorFlow, MLflow. DATA SCIENCE & ANALYTICS End-to-end data pipelines, exploratory analysis, experiment design (A/B testing), KPI dashboards, and clear reports that non-technical teams can act on. Tools: Python, Pandas, NumPy, SQL, Matplotlib, Seaborn. AI & PROMPT ENGINEERING I build LLM-powered workflows, RAG chatbots, and multi-agent systems using GPT-4/4o, Claude, LLaMA, LangChain, Hugging Face, and vector databases (Pinecone, ChromaDB, Neo4j). Prompt libraries, FAQ bots, research copilots, and AI-driven content automation integrated with your existing tools (Slack, Notion, Shopify, CRM). AI VIDEO SPECIALIST I produce AI-generated video content — product explainers, training modules, and social media clips — using AI avatars, voice synthesis, and prompt-driven scripts. AI video grew 329% year over year on Upwork in 2025 and I stay current with the latest tools to deliver fast, scalable content packages. CYBERSECURITY-AWARE AI SYSTEMS I build AI and ML solutions with security best practices baked in — controlled data access, secure API usage, and audit-friendly pipelines aligned to your organization's policies. TYPICAL DELIVERABLES - ML models: forecasting, classification, regression, anomaly detection - NLP pipelines: sentiment analysis, topic modeling, document Q&A - LLM apps: RAG chatbots, AI agents, prompt libraries, workflow automation - AI video: short-form clips, product demos, training videos - Dashboards and reports stakeholders can use without a data background Why clients work with me again: Clear communication | Business-first thinking | Fast turnaround Share your goal and I will propose a concrete plan with timeline, deliverables, and milestones.

  • Deep Learning
  • Generative AI
  • LangChain
  • Hugging Face
  • LLM Prompt Engineering
  • Large Language Model
  • Computer Vision
  • AI Chatbot
  • Machine Learning
  • Python
  • Data Science
  • Natural Language Processing
  • Prompt Engineering
  • Data Analytics
  • Data Visualization
  • MLOps
  • Artificial Intelligence
  • Cybersecurity Management
  • AI Video Generation
  • Data Mining
Abiodun I.

Lagos, Nigeria

$10/hr
5.0
43 jobs

"I am available for a new project." Experienced in designing tailored recruitment and HR technology processes that align with startup-specific features such as industry demands, budget constraints, cultural nuances, and mission alignment. Skilled at creating agile solutions to attract, engage, and retain top talent while optimizing for growth and scalability. Additionally, proficient in Virtual Assistant duties, including managing schedules, coordinating communications, handling administrative tasks, and leveraging digital tools to streamline operations. Adept at balancing multiple priorities, ensuring seamless team support, and driving efficiency in both HR and virtual assistance functions. Passionate about helping startups build robust, high-performing teams while maintaining operational excellence. I have worked with organizations among the Fortune 500, Not-for-profit, Sales, Advertising, BPO, Digital Marketing, AI Devs, Manufacturing, Engineering, Tech, EV orgs, Accounting/CPA, hospitality, and Oil and Gas. I am open to a long-term contract or a contract to hire. Tech Skills: ATS, ChatGPT, Deepseek, and other AI agents, HRIS, CRMs, Slack, Skype, monday.com, Click-Up, Trello, Odoo ERP. Asana, #available #opentowork #recuiter #employeeengagement #trainer

  • Boolean Search
  • Recruiting
  • Human Resource Management
  • Staff Recruitment & Management
  • Candidate Interviewing
  • LinkedIn Recruiting
  • HR System Management
  • Executive Search
  • Employee Relations
  • Compensation & Benefits
  • Administrative Support
  • Communications
  • HRM Labs HRIS
  • Accounts Receivable
  • Intuit QuickBooks
Tilmann B.

Mountain View, California

$100/hr
5.0
14 jobs

I’m a PhD in Computer Science and a hands-on AI architect with 30+ years of experience building and delivering AI systems at global scale. I’ve held leadership roles at PayPal, Intuit (Credit Karma), Eventbrite, and Sun Microsystems, creating mission-critical AI platforms that served millions of users and generated hundreds of millions in revenue. I don’t just design systems, I build them end to end. At Credit Karma, I led development of the recommendation engine for 130M members, driving $400M+ annually from 40B predictions per day. I also optimized cloud infrastructure to cut $20M in costs each year, proving that strong AI is about business results as much as algorithms. What I Bring - Generative AI / LLMs - I build practical AI solutions using large language models, including chatbots, RAG systems, fine-tuned models, and multimodal AI. - Personalization & Recommendations - I’ve delivered large-scale engines that serve millions daily, turning data into smarter user experiences and measurable revenue. - AI Cost Savings - I optimize models and cloud systems to cut costs while boosting speed and accuracy, saving enterprises millions. - End-to-End AI Delivery - From idea to launch, I take ownership of the full process to ensure systems are reliable, scalable, and production-ready. - Proven Innovation - I hold 22 US patents in search, recommendations, and fraud detection, showing decades of applied problem-solving in AI. I deliver through Helix Logic, my AI agency, where I pair with senior ML engineers to move from architecture to production quickly. Unique Advantage Most AI experts focus on either theory or code. I combine deep technical skills with a proven record of business impact. My work has generated hundreds of millions in revenue, saved millions in costs, and powered AI systems used daily by millions worldwide. If you're looking for a team that combines deep AI expertise with a proven record of business impact, I'd be glad to talk.

  • Generative AI
  • AI Platform
  • Software Architecture
  • Project Delivery
  • Multimodal Large Language Model
  • Recommendation System
  • AI Agent Development
  • Knowledge Graph
  • Retrieval Augmented Generation
  • Accuracy Verification
  • Python
  • AWS Development
  • Google Cloud Platform
  • Prompt Engineering
  • Machine Learning
Ronak P.

Ahmedabad, India

$25/hr
5.0
2 jobs

Healthcare AI built by an engineer who knows buyers are right to filter out generalists. Medical imaging on DICOM, clinical NLP that handles negation and hedging, HIPAA-aware PHI pipelines, patient-facing apps that respect privacy for hospitals, radiology centres, pharma R&D, CROs, medical device makers, health-tech teams. I work with the Brainy Neurals team as the healthcare-AI engineer. My focus sits between "we have clinical data" and "validated AI helping clinicians" model design, PHI handling under your BAAs, on-prem vs cloud, validation against radiologist ground truth, shipping into EHR or device workflow. WHAT I BUILD / IN HEALTHCARE Medical imaging AI — DICOM ingestion, de-identification per Safe Harbor, organ and lesion segmentation on CT and MRI, abnormality detection, NIfTI and ITK pipelines, 3D Slicer. Built on MONAI, nnU-Net, TotalSegmentator, RadImageNet, validated against radiologist consensus. Clinical NLP and document AI note summarisation, ICD and SNOMED mapping, negation and hedging, family-vs-patient history disambiguation, medication extraction, lab-report parsing, prescription OCR. The grammar of clinical text is its own thing; I treat it accordingly. Pharma and clinical research clinical protocol to eCRF extraction (demographics, vitals, inclusion-exclusion, study-arm), systematic review using RoB2, GRADE, PRISMA, citation validation, batch record digitisation, evidence assembly. Patient-facing apps GI symptom-trackers with AI food and lifestyle recommendations, diabetic and gut-condition dish-suggestion, telehealth onboarding, chronic-care intake, mental-health support. Flutter or React Native fronts, FastAPI backends. Hospital workflow AI appointment automation, triage, hand-hygiene monitoring, fall-detection in wards (pose-based, no face recognition), bed-occupancy. THE STACK / FOR MEDICAL & PHARMA Imaging: MONAI, DICOM, NIfTI, ITK, 3D Slicer, nnU-Net, TotalSegmentator, RadImageNet, modality fusion. Clinical NLP and docs: Docling for medical PDFs, DocTR and TR-OCR for prescription and lab OCR, GPT-4o multimodal for complex layouts, Claude and Gemini for clinical reasoning, regex and Pydantic validation, NegEx-style negation with LLM verification. Knowledge: Neo4j for clinical knowledge graphs (drug-drug interaction, condition-symptom, contraindications). pgvector or Qdrant for medical literature. RAG over institutional protocols, authoritative sources only. Infrastructure: FHIR and HL7 v2 with EHRs, OMOP CDM for research, FastAPI for clinical APIs, Flutter and React Native for patient apps, AWS and Azure inside client BAAs, on-prem Ollama and vLLM where data cannot leave. WHO I BUILD FOR Hospitals and clinics radiology AI, patient-flow analytics, EHR decision support, ward-safety. Radiology centres, DICOM pipelines, organ and lesion segmentation, second-read AI, reporting integration. Pharma R&D and CROs clinical protocol extraction, systematic review, eCRF generation, evidence assembly. Medical device (pre-clearance) model prototyping, validation harnesses, dataset curation. I do not claim FDA-cleared deliverables; I build the substrate that goes through your regulatory team. Telehealth and health-tech patient intake, AI triage, multilingual symptom-checker. Specialty practices dental, dermatology, gastroenterology, oncology, mental health. Specialty-tuned models on small datasets. Health insurance claim review, prior-auth triage, appeals support, evidence extraction. HOW I WORK / WITH HEALTHCARE BUYERS Discovery is a 30-minute call: data sources, clinical workflow, compliance posture (HIPAA, GDPR, local). By the end I tell you whether the use case is feasible, validation plan, where ground truth comes from, how PHI flows. If it touches a regulated device pathway, I tell you what is in scope for me and what your regulatory team owns. Pricing is fixed-scope per milestone feasibility, dataset and PHI design, model build, validation, integration handoff. Hourly only for maintenance after deploy. THE BRAINY NEURALS BACKING I work with the Brainy Neurals team 15 AI engineers, NVIDIA Inception Partner, AWS Activate, Microsoft for Startups. When a project needs ward-monitoring cameras, edge deployment on hospital hardware, RAG over clinical docs, or workflow automation around the AI, that capacity sits with the team I bring them in cleanly, you do not manage multiple vendors. For pure healthcare model and clinical-NLP work I lead end to end myself. LET'S TALK / IF You are inside healthcare or pharma, you have a clinical workflow AI can genuinely help with, you understand the validation and compliance work this requires, and you want a senior engineer who has built medical imaging, clinical NLP, and patient-facing apps before not a generalist learning HIPAA on your project. Tell me your data, workflow, compliance. I reply within 24 hours with feasibility, validation approach, milestones.

  • Artificial Intelligence
  • Generative AI
  • Computer Vision
  • Prompt Engineering
  • LLM Prompt Engineering
  • LangChain
  • Vision-Language Model
  • Edge AI
  • AI Agent Development
  • AI App Development
  • Retrieval Augmented Generation
  • AI Development
  • AI Implementation
  • AI Video Generator
  • AI Chatbot
Ajay J.

Mohali, India

$75/hr
4.9
55 jobs

🚀Principal AI/ML Engineer — 13 years · Expert-Vetted (Top 1% on Upwork) I build production AI systems end to end — from the bare-metal GPU infrastructure all the way up to the product your users actually touch. Not prototypes that die in a notebook: real, deployed, monitored systems that hold up under load. For 13 years I've designed, trained and shipped AI across large language models, generative AI, computer vision, speech and NLP — for clients in insurance, healthcare, finance, public safety and media. Today I run the on-prem GPU infrastructure behind a national AI platform, serving a 753-billion-parameter language model (GLM-5.2) across a 32-GPU NVIDIA B200 cluster that handles 1,000+ users at once. ⭐ What I can do for you 🔹 LLM serving & cost optimization — Kill your per-token API bill. Self-host open models (GLM, Qwen, Llama, Mistral, Kimi) on your hardware or cloud with vLLM/SGLang: tensor and expert parallelism, FP8 quantization, high concurrency, low latency, predictable cost. 🔹 Fine-tuning & custom models — SFT, LoRA / QLoRA and full fine-tunes tailored to your domain and language, including hard low-resource languages. (I fine-tuned Whisper for Uzbek to 10.5% WER and built custom neural TTS voices from scratch.) 🔹 RAG & knowledge systems — RAG with hybrid dense+sparse retrieval, rerankers, vector and graph DBs (Qdrant, Pinecone, Neo4j, NebulaGraph), plus evaluation so you can prove it got better. 🔹 Computer vision — Vision and speech, not just chatbots. Face analytics, object detection and tracking, OCR and document pipelines, health-from-video (heart rate, SpO2, BMI), real-time multi-camera video, streaming voice agents, AI calling systems, voice cloning, image and video generation. 🔹 AI agents & automation — Multi-agent systems, document processing, LLM-powered classification and extraction, and end-to-end workflow automation. 🔹 Generative AI — Image and video generation, avatars, voice cloning, text-to-speech and speech-to-text. GPU infrastructure that stays up. Bare-metal and cloud clusters, CUDA, multi-node inference, autoscaling, load balancing, monitoring, CI/CD. The layer most freelancers leave you holding. 🚦 HOW ENGAGEMENTS START • Cost audit — I look at what you spend on tokens or cloud GPUs and tell you what self-hosting or a smaller fine-tune would actually cost. • Prototype-to-production rescue — it works in a notebook or a demo; I make it survive real users, real load, real uptime. • Build from zero — model choice, infra, backend, deployment, monitoring, handover docs. ✳️ HOW I WORK • We agree on the target first: latency, cost per request, accuracy, concurrency. Numbers, not vibes. • I build inside your environment: your cloud or your hardware, your repo, your keys. You own all of it. • You get infrastructure-as-code, a runbook and working monitoring, not a model file and good luck. • You talk to the person writing the code. No account manager, no team behind me. • Straight answers. If a smaller model, cheaper hardware or no AI at all is the right call, I say so before you spend. 🛠️ STACK LLM/RAG: GPT-4.1/4o/o3, Claude 4, Gemini 2.5, Llama 3.x, Qwen 3, DeepSeek, Mistral, GLM, fine-tuning, hybrid and semantic search, prompt and context engineering, structured output, knowledge-graph RAG Agents: LangGraph, LangChain, LlamaIndex, CrewAI, AutoGen, OpenAI Agents SDK, DSPy, Haystack, MCP, function calling, long-term memory, human-in-the-loop Serving & GPU: vLLM, SGLang, Ollama, NVIDIA NIM, CUDA, quantization, autoscaling, load balancing, cluster ops ML: PyTorch, TensorFlow, Hugging Face, Transformers Speech: Whisper, Faster-Whisper, speech recognition, TTS, speaker recognition, real-time voice Vision & generative AI: YOLO, ViT, OCR, segmentation, medical imaging, multimodal, image and video generation, avatars Backend: Python, FastAPI, Django, Flask, REST/GraphQL/WebSockets/gRPC, Celery, Redis, Kafka, RabbitMQ, Airflow Data: PostgreSQL, MySQL, MongoDB, Elasticsearch, Neo4j, Pinecone, Weaviate, Qdrant, Milvus, ChromaDB, FAISS Infra: AWS, GCP, Azure, RunPod, Hetzner, Vast.ai, Docker, Kubernetes, Helm, NGINX, Traefik, GitHub Actions, Linux Integrations: OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Twilio, WhatsApp Business, Slack, Salesforce, HubSpot, Stripe, OAuth2/JWT 📦 TYPICAL BUILDS Enterprise assistants and internal copilots · RAG and knowledge platforms · support, sales and SDR bots Voice assistants and AI calling · document AI and OCR pipelines · medical and financial AI Predictive analytics and recommenders · computer vision apps · workflow automation · AI dashboards 📩 Send me a message with what you're building and where it's stuck. One paragraph is enough. I'll tell you honestly whether I can help and exactly how I'd approach it, before you spend a dollar. If I'm not the right person, I'll say so.

  • Machine Learning
  • Natural Language Processing
  • Deep Learning
  • Python
  • Data Science
  • AI Model Development
  • TensorFlow
  • Artificial Intelligence
  • Google Cloud Platform
  • Stable Diffusion
  • Hugging Face
  • AI-Generated Art
  • Flask
  • LLM Prompt Engineering
  • Machine Learning Model
Uttamkumar T.

Surat, India

$40/hr
4.5
41 jobs

✅ AWS Certified Machine Learning Specialist 🟢 𝗧𝗼𝗽 𝗥𝗮𝘁𝗲𝗱 𝗣𝗹𝘂𝘀 🟢 𝗠𝗖𝗣, 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀, 𝗥𝗔𝗚, 𝗩𝗼𝗶𝗰𝗲 𝗔𝗴𝗲𝗻𝘁𝘀 🟢 7+ 𝗬𝗲𝗮𝗿 🟢 Available now 🟢 Top Rated Plus 🔴 Top 1% Talent on Upwork 🟢 𝗠𝗖𝗣, 𝗔𝟮𝗔, 𝗢𝗽𝗲𝗻𝗖𝗹𝗮𝘄, 𝗖𝗹𝗮𝘂𝗱𝗲 𝗖𝗼𝗱𝗲, 𝗟𝗮𝗻𝗴𝗚𝗿𝗮𝗽𝗵 ✅ Tech Stack & Expertise ❇️ AI & ML: Deep Learning, TensorFlow, PyTorch, Neural Networks, Generative AI, Data Science, NLP ❇️ LLM Engineering: OpenAI, ChatGPT API, LLaMA 3, Mistral, Mixtral, LoRA, QLoRA, DPO, RLHF, PEFT, Prompt Engineering, Vector DBs (Pinecone, Weaviate, FAISS), RAG Pipelines ❇️ AI Agents: AI Chatbots, Bots, Classifiers, Voice AI, TTS, STT, CrewAI, AutoGen ❇️ Agentic AI & Protocols: MCP (Model Context Protocol), A2A, OpenClaw, Claude Code, Cursor AI, Windsurf, AG-UI, Pydantic AI, Google ADK, OpenAI Agents SDK ❇️ Agent Frameworks: LangGraph, OpenAgents, Haystack, Microsoft Agent Framework, Anthropic Agent SDK ❇️ Latest Models: Claude 4.5/4.6 Opus, GPT-4o, o1/o3, Gemini 2.5 Pro, DeepSeek, LLaMA 3.3, Kimi K2.5 ❇️ AI Coding: Claude Code, Cursor IDE, Windsurf, Lovable, Replit AI, GitHub Copilot ❇️ Voice AI: Hume AI, Deepgram Nova-3, PlayHT, Bland AI, ElevenLabs Conversational AI ❇️ Python: Flask, FastAPI, Django, GPT APIs, Pytest, BeautifulSoup, Selenium ❇️ Fullstack: JavaScript, React.js, Node.js, Express.js, MongoDB ❇️ DevOps & Cloud: Docker, Kubernetes, Ansible, GitLab CI/CD, AWS, Azure, GCP, DigitalOcean ❇️ APIs: RESTful APIs, OpenAI Embeddings, Webhooks, Microservices, Stripe, Binance, Telegram, BetFair, OddsJam, Interactive Brokers 📌 Services I Offer ⚙️ Web Scraping, Data Extraction, Crawling & Mining ⚙️ ML Model Development & AI Implementation ⚙️ Deep Learning & AI Model Training ⚙️ AI Chatbots, Bots & Agent Development ⚙️ NLP, AI Classifier & Generative AI Applications ⚙️ Financial Dashboard, Market Analysis & Automation ⚙️ Interactive Brokers / Binance / Telegram Bot Development ⚙️ Data Cleaning, Processing, Analysis & Visualization ⚙️ Voice AI: Text to Speech, Speech to Text Integration ⚙️ Workflow Automation & Python-based Optimization ⚙️ MCP Server Development & Agentic AI Integration ⚙️ OpenClaw Setup, Custom Skills & Personal AI Agent Deployment ⚙️ A2A Protocol for Multi Agent Communication ⚙️ Agent Orchestration with LangGraph, CrewAI & OpenAgents ⚙️ AI Coding Agent Setup (Claude Code, Cursor, Windsurf) 🤖 LLM & AI Engineering ➜ Neural Networks, TensorFlow, PyTorch, Generative AI Apps ➜ LLM Fine-Tuning: Persona bots, Q&A, Legal/Medical NLP using LLaMA 3, Mistral ➜ Synthetic Data Generation & ML Model Training ➜ Prompt Engineering & Evaluation Pipelines ➜ OpenAI API, ChatGPT API, OpenAI Embeddings Integration ➜ Cloud AI Deployment: SkyPilot on AWS, GCP, RunPod ➜ Inference: vLLM, TGI with AWQ, GPTQ, GGUF, GGML ➜ MCP Server/Client Development, A2A Protocol, AG-UI ➜ OpenClaw Agent: Setup, AgentSkills, WhatsApp/Telegram/Slack ➜ Multi Agent Orchestration: LangGraph, CrewAI, OpenAgents ➜ Reasoning Models: OpenAI o1/o3, Claude Reasoning ➜ AI Coding Agents: Claude Code, Cursor, Windsurf 🔌 API Integration ✔️ ChatGPT API, OpenAI API & Vector Database Integration ✔️ RESTful Architecture, OAuth, Token Auth, Rate Limiting ✔️ Real-time Data, Webhooks, Cloud Functions ✔️ Scalable Microservices for AI Applications ✔️ MCP Server Development for Claude, ChatGPT & Custom AI Apps ✔️ A2A Protocol for Agent Interoperability ✔️ OpenClaw Custom Skills & Plugin Development 🧠 AI Agent & LLM Skillset Voice AI: CrewAI, AutoGen, Deepgram, Amazon Polly LLM Fine-Tuning: PEFT, LoRA, QLoRA, RLHF, DPO Tools: HuggingFace AutoTrain, Axolotl, Unsloth NLP: Prompt Engineering, RAG Pipelines, AI Classifiers GenAI: AI Chatbots, Bots, App Development, Automation Agentic Protocols: MCP, A2A, AG-UI Personal Agents: OpenClaw, Autonomous Workflow Automation Orchestration: LangGraph, OpenAgents, Pydantic AI, Google ADK AI Coding: Claude Code, Cursor, Windsurf, GitHub Copilot Models: Claude 4.5/4.6, GPT-4o, o1/o3, Gemini 2.5 Pro, DeepSeek, Kimi K2.5 💡 I build scalable AI applications, automate workflows, and develop advanced ML and Deep Learning models with seamless API integration. I deliver WEB SCRAPING, DATA MINING, and AUTOMATION solutions using Python, BeautifulSoup, Selenium, and Playwright with anti-detect browsers and proxies. For Data Science projects, I use Pandas, NumPy, Scikit-Learn, and TensorFlow. 🏆 40+ AI projects delivered. Clients see up to 60% less manual work and 3x faster processing after my AI and automation solutions. 📈 Looking for Python + AI/ML, Chatbots, AI Agents, or API Integration? Message me and let us get started. Thanks, Uttam

  • Artificial Intelligence
  • AI Agent Development
  • Machine Learning
  • Generative Model
  • Natural Language Generation
  • LLM Prompt Engineering
  • Amazon SageMaker
  • Retrieval Augmented Generation
  • Multimodal Large Language Model
  • LangChain
  • Large Language Model
  • Transformer Model
  • AI App Development
  • OpenAI API
  • ChatGPT

How it works

Post a job for freePost a job

Tell us what you need. Create your own job post or generate one with AI then filter talent matches.

Hire top talent fast

Consult, interview, and hire quickly, so you can meet the freelancers you're excited about.

Collaborate easily

Use Upwork to chat or video call, share files, and track project progress right from the app.

Payment simplified

Manage payments in one place with flexible billing options. Only pay for approved work, hourly or by milestone.

Don't just take our word for it

Prompt engineer hiring guide

Prompt engineers design and optimize the instructions that allow artificial intelligence systems to deliver accurate, consistent, and cost-effective results. These specialists combine technical knowledge of large language models with strategic thinking to solve business problems like automating customer service workflows and building AI-powered development tools. Whether you're integrating AI into existing operations or launching new products, skilled prompt engineers can help you harness the full potential of generative AI technologies.

What does a prompt engineer do?

A prompt engineer designs, refines, and optimizes the text prompts that allow large language models (LLMs) to generate specific outputs, helping AI output match business goals. They do this using advanced techniques like few-shot and chain-of-thought prompting to guide large language models through logical reasoning, working to minimize errors and hallucinations.

Beyond writing text, prompt engineers play a significant role in system optimization. Because LLMs often charge based on tokens, a skilled engineer crafts concise prompts that reduce token usage without sacrificing quality, directly lowering operational costs. They also rigorously test prompts against edge cases to ensure safety, a process known as red teaming.

Furthermore, prompt engineers collaborate with developers (i.e., ChatGPT developers) to integrate prompts into larger software architectures, working with frameworks like LangChain to build autonomous agents that perform multi-step tasks.

How to hire a prompt engineer on Upwork

Upwork makes it easy to find and hire freelance prompt engineers, with many skilled candidates available to meet your timeline and budget needs. To streamline your hiring process, just follow these four simple steps.

Step 1: Post a job

A well-constructed job post serves as your first filter, helping attract prompt engineers with the skills your project demands. In your post:

  • Outline your project goals and expected deliverables

  • Describe specific skills you may need such as few-shot or chain-of-thought prompting, or retrieval-augmented generation (RAG) 

  • Request specific experience with frameworks like LangChain or Semantic Kernel

  • Cover logistical details such as timeline and budget

To create a tailored job post quickly, try the Job Post Generator powered by Uma™, Upwork’s Mindful AI. Describe what you need in a few sentences, and Uma will craft a job post in seconds. You can also review job description templates for inspiration.

Step 2: Evaluate candidates

Prompt engineering is a relatively new field in which experience showing measurable results matters more than education or even certifications. As you receive proposals:

  • Have Uma give instant video interviews and side-by-side comparisons

  • Use Upwork’s filters to find candidates by rate, location, and experience

  • Review proposals for signs that the candidate has understood your job post and has the skills to meet your needs

  • Review portfolios for before-and-after prompt improvements with measurable results

  • Check for experience in your specific domain and evidence of working with complex system prompts

Step 3: Interview your top choices

Quick video interviews give you the chance to ask any questions you have left for your top candidates, and to get a feel for what a collaboration with them might be like.

  • Schedule and conduct interviews within Upwork messaging to get instant transcripts and summaries from Uma

  • Ask the candidates to walk you through past work from their portfolio, focusing on aspects that are similar to your project and challenges they overcame

  • Have candidates walk you through a hypothetical scenario in which an AI system is failing; ask how they would diagnose and fix it

  • Ask about their approach to ethical guardrails and preventing biased outputs

You can refer to common interview questions for freelancers to help keep your conversations focused and productive. You might also adapt AI engineer interview questions to assess a candidate’s technical knowledge.

Step 4: Agree on scope and begin work

Once you’ve found the right person, you can send a contract directly through the Upwork marketplace. A solid contract protects both parties and helps collaborations be successful from beginning to end.

  • Use Upwork's contract workroom, messaging, and payment protection for secure collaboration

  • Choose fixed-price contracts for projects with clear deliverables, such as refining a single core system prompt

  • Break large projects into milestones, such as dataset preparation, prompt tuning, and API integration

  • Choose hourly contracts for ongoing work or projects without clear deliverables, such as ongoing testing and optimization 

After the contract starts, be sure to give the prompt engineer everything they need to succeed, including appropriate access to the necessary files, AI models, and project management tools.

Upwork is not affiliated with and does not sponsor or endorse any of the tools or services discussed in this article. These tools and services are provided only as potential options, and each reader and company should take the time needed to adequately analyze and determine the tools or services that would best fit their specific needs and situation.

The rates and information provided in this article are based on current data and industry sources available at the time of publication. Freelance rates can vary depending on factors such as experience, location, project scope, and market conditions. Readers are encouraged to conduct their own research to confirm current rates and trends, as this information may change over time.

How much does hiring a prompt engineer cost?

Independent professionals on Upwork base their rates according to market demand, the scope and complexity of the project, and their own skills and experience. An experienced prompt engineer may command higher fees but typically works faster, brings specialized expertise, and delivers higher-quality results. Conversely, engineers building their client base may offer more competitive pricing. The right choice depends on your project's complexity, timeline, and quality requirements.

The following chart lists the typical price range for common projects prompt engineers handle.

Single task prompt optimization

$100-$300/project

Entry-level
  • Refinement of one core system prompt
  • A/B testing of 3 variations
  • Output formatting (e.g., JSON or Markdown)

Workflow automation and chaining

$400-$1,200/project

Mid-level
  • Multistep prompt chains for complex tasks
  • Integration with Zapier or API workflows
  • Error handling and fallback logic

RAG system and chatbot architecture

$1,500-$4,000/project

Expert-level
  • Retrieval-augmented generation setup
  • Context window management strategies
  • Comprehensive evaluation dataset creation

Enterprise model fine-tuning strategy

$5,000+/project

Expert-level
  • Dataset preparation for fine-tuning
  • Custom model evaluation and rigorous testing
  • Security guardrails and compliance auditing

FAQs about prompt engineers

Frequently asked questions

Is hiring a prompt engineer worth it?

Yes, hiring a prompt engineer is worth it when AI outputs directly impact your product quality or operational efficiency. If you're building customer-facing AI features, processing sensitive data, or making business decisions based on AI outputs, a prompt engineer provides strong ROI through enhanced reliability.

Are prompt engineers still in demand?

Yes, demand for prompt engineers continues to grow as more businesses integrate generative AI into their operations. As companies move from AI experimentation to production deployments, the need for specialists who can optimize, secure, and maintain these systems is growing.

What is replacing prompt engineering?

Prompt engineering is developing into specialized disciplines like AI product design, model evaluation, and fine-tuning strategy. Advanced capabilities like autonomous agents actually increase the need for skilled engineers who can architect complex AI systems.

Do prompt engineers need coding skills?

Professional prompt engineers typically do benefit from being able to code, particularly in Python, to interact with APIs, manage testing data, and use frameworks like LangChain, often working alongside API developers for deeper integrations.

What's the difference between prompt engineering and model fine-tuning?

Prompt engineering involves crafting input text to guide a pretrained model without changing it, whereas fine-tuning involves retraining the model on a specific dataset. Prompt engineering is generally faster and cheaper, while fine-tuning is reserved for specialized use cases.


Can a prompt engineer help reduce AI costs?

Yes, a skilled prompt engineer can significantly reduce operational costs. By optimizing prompts to be more concise, engineers reduce tokens processed. Over millions of API calls, this optimization can result in substantial savings.

How do prompt engineers measure success?

Prompt engineers measure success through rigorous evaluation metrics, often by creating datasets of ideal answers and comparing the AI's output against them. They look for semantic similarity, factual accuracy, and adherence to formatting rules.

Is prompt engineering a long-term role or a one-time fix?

Prompt engineering is typically a long-term, ongoing role for products relying heavily on AI. AI models are frequently updated, which requires reoptimization. And as user behaviors change and new edge cases are discovered, prompts have to be continuously refined.