Hire the Top 2% of
Remote Prompt Engineering Developers

Krishna V.

Vetted Prompt Engineering developer in the United States (UTC-5)

• Experienced AI professional and researcher with extensive experience in implementing projects across Generative AI, Machine Learning, Agentic AI, Deep Learning, Computer Vision, Natural Language Processing, Predictive Analytics, and Conversational AI. • Currently working with Microsoft on designing and implementing solutions using LLM, AI Agents, MCP and driving ec2 advancements in NLP, Gen AI for the organization. • Designed and deployed scalable AI solutions using AWS Bedrock, Azure Foundry utilizing its managed service for deploying and running generative AI models, enabling faster and more efficient model deployment. • Developed and deployed scalable models leveraging LoRA and QLoRA for natural language processing tasks, improving accuracy and efficiency in real-world applications. • Managed and optimized large datasets within Google BigQuery, leveraging its distributed architecture to ensure fast and cost-effective data analysis for AI-driven applications. • Implemented Guardrails for AI models to ensure compliance with privacy regulations, including automatic PII redaction, to protect sensitive information during model inference. • Utilized LangGraph to visualize agent behavior and logic flow, ensuring transparency and effective management of decision trees for complex LLM-based agents. • Developed and deployed Generative AI models using TensorFlow, PyTorch, and Keras, creating high-quality text, image, and audio generation systems for various applications. • Built and maintained Python-based AI services using LangChain and CrewAI, implementing RAG-based retrieval and Agentic AI workflows to enhance data retrieval and decision-making processes. • Integrated OpenAI, Bard, Claude, and Azure OpenAI APIs, optimizing model performance by fine-tuning temperature, top-p, and max tokens, reducing hallucinations through embedding-based retrieval

Victor N.

Vetted Prompt Engineering developer in the United States (UTC-4)

With a unique blend of expertise in front-end engineering and AI technologies, I specialize in designing intuitive user interfaces and training large language models (LLMs). Over the last 5 years, I have honed my skills in UI/UX design, application development, and system architecture, while now also focusing on creating datasets, fine-tuning, and developing prompts to optimize LLM performance. My experience bridges the gap between technology and user experience, whether it’s crafting visually engaging, responsive front-end interfaces or advancing AI models to deliver cutting-edge solutions. I’m passionate about driving innovation and delivering impactful results through collaboration and forward-thinking design. I bring the value of 3 special skills to table. Striving for more.

Jijun T.

Vetted Prompt Engineering developer in France (UTC+2)

**Senior AI Engineer and Backend Developer specializing in AI agents, Generative AI, data platforms, and distributed systems. Experienced in building production AI applications and large-scale data systems using Python, TypeScript, Node.js, PostgreSQL, Kafka, Kubernetes, and cloud platforms.** **Hands-on experience with agentic AI, RAG, LLM applications, machine learning, OCR, and cloud-based data pipelines across AWS, Azure, and GCP. Strong background in designing scalable backend services, AI workflows, ETL/streaming platforms, and full-stack interfaces, with a focus on reliable production systems and real-world business impact.**

Priya S.

Vetted Prompt Engineering developer in Singapore (UTC+8)

A highly accomplished professional leader, mentor, and guide, renowned for establishing numerous Data Validation and Quality Assurance teams across diverse industry domains including Media Application, ECommerce/Retail, and Telecom. Building High-Performing Teams: Proven track record of building and leading Data Validation and Quality Assurance teams from the ground up across Media Applications, E-commerce, and Telecom. Successfully managed teams of up to 30 Data Analysts, Testers, and Automation professionals, driving quality and efficiency in complex, high-stakes environments. Driving Innovation in Search & Personalization: Led a team of Market Insight and Search Language Analysts for Apple Media Products, focusing on data annotation, judgment ratings, and auditing. Optimized search and personalization features through offline data validation, NLP, LLMs, and AI/ML algorithms using human-centered insights. Domain Expertise: Recognized expert in Search and Personalization for Digital Media Products, with a strong focus on Human Factors and Trust & Safety. Extensive experience in Software Quality Assurance across E-commerce, Digital Publishing, Payments, and Telecom, ensuring optimal user experiences and system reliability. Agile Champion: Successfully implemented Agile methodologies to enhance team productivity and streamline testing processes during my tenures in DFS, SPH and Apple. Strategic Vendor Management: Proven ability to formulate effective vendor contracts (RFI/RFPs, MSAs, SOWs) alongside managing project budgets (CAPEX/OPEX) and overseeing invoicing processes. Exceptional People Leader: Demonstrated excellence in global team management, talent acquisition, performance & compensation planning, and mentoring large software and data validation teams.

Jason .

Vetted Prompt Engineering developer in the United States (UTC-4)

Great coders - replaced by AI circa late 2025. Great dev ops - replaced by AI circa mid 2026. Great software engineers - not yet! I am all three, and have been for many years. I solve problems, fast. Is yours next? Checkr background fully green. AI Systems Architect, GTME, CSA, SRE, and Fractional CTO helping organizations leverage custom AI, autonomous agents, and cloud infrastructure to build products faster, automate operations, and scale efficiently. Expert in custom AI model development, fine-tuning, RAG implementations, multi-agent systems, AI-powered workflow automation, LLM integration, cloud architecture, cybersecurity, and high-availability SaaS operations. With decades of hands-on engineering experience and deep expertise in modern AI tooling, I bridge the gap between traditional software engineering and next-generation AI systems. I build production-ready AI solutions that deliver measurable business outcomes—not demos, prototypes, or hype. From custom AI platforms and autonomous agent ecosystems to cloud-native SaaS infrastructure and mission-critical production environments, I help organizations deploy secure, scalable systems that create immediate operational leverage. Extensive NDA obligations limit what I can publicly share, but my experience spans startups, growth-stage companies, enterprise organizations, and large-scale SaaS platforms operating under demanding uptime, privacy, and security requirements.

Nick R.

Vetted Prompt Engineering developer in Greece (UTC+3)

I am a Senior Software Engineer with experience in developing enterprise-grade e-commerce and content management platforms, leading cross-functional teams, architecting scalable microservices, and implementing AI-powered solutions.

Justin .

Vetted Prompt Engineering developer in Ireland (UTC+1)

I have a background in computer science and have’ experience in machine learning，deep learning and AI, working across domains like e-commerce, fintech, healthcare, transportation, and ad-tech. I’ve worked on projects including recommendation systems, dynamic pricing, image search, NLP classification, LLM prompting ,fine-tuning and retrieval-augmented generation. In doing so, I’ve handled full ML lifecycles—from data processing and model training to deployment and monitoring—collaborating closely with product, engineering, and analytics teams. Technically, I’m comfortable with Python, PyTorch, TensorFlow, Hugging Face, Spark, SQL, Docker, Kafka,  Airflow and Prefect, gcp, aws.

Gabriel O.

Vetted Prompt Engineering developer in the United States (UTC-4)

I am a full-stack engineer with over 15 years of experience building modern web applications, backend systems, and API-driven platforms. My expertise includes JavaScript, TypeScript, React.js, Vue.js, Angular, Node.js, Express.js/Nest.js, Python, and database technologies such as PostgreSQL, MongoDB, and MySQL. Throughout my career, I have worked on applications requiring secure transactions, authentication, data integrity, and complex business logic, including e-commerce platforms, healthcare systems, financial solutions, and enterprise applications. I have extensive experience designing and integrating REST APIs, building backend services, and connecting applications with third-party platforms and distributed systems. In recent years, I have expanded my work into AI-powered applications, LLM workflows, and agent-based systems. I have hands-on experience designing AI-enabled SaaS applications using OpenAI APIs, LangChain, Python, Node.js, Supabase, and PostgreSQL. I have built intelligent workflows involving LLM orchestration, prompt engineering, semantic search, AI recommendations, automated decision support, and API-driven tool integrations. I have experience designing secure multi-tenant SaaS platforms with Supabase and PostgreSQL, including implementing Row-Level Security (RLS) policies for tenant-level data isolation, role-based permissions, authentication workflows, and secure data governance. I understand the importance of controlling AI agent actions through permission models, audit logging, human approval workflows, and structured application rules. My full-stack background allows me to architect complete AI products, from user-facing interfaces and backend services to AI orchestration layers, external model integrations, and cloud infrastructure using AWS and Supabase.

Michael A.

Vetted Prompt Engineering developer in the United States (UTC-7)

Data Scientist | Machine Learning Engineer with 9+ years of experience developing scalable Machine Learning, Artificial Intelligence (AI), Computer Vision, and Predictive Analytics solutions across enterprise and financial environments. Hands-on experience in Computer Vision and real-time vision systems, including hand tracking, gesture and hand-pose classification, image/video processing, and low-latency inference for VR/XR applications. Experienced working directly with raw image and video data across preprocessing, feature extraction, model training, inference, evaluation, and performance optimization, with a focus on building responsive Computer Vision pipelines rather than solely consuming pre-built SDK outputs. Extensive expertise across the end-to-end Machine Learning lifecycle, including data acquisition, feature engineering, exploratory data analysis (EDA), model development, hyperparameter tuning, model evaluation, deployment, MLOps, model monitoring, and performance optimization. Experienced with Machine Learning, Deep Learning, Natural Language Processing (NLP), Large Language Models (LLMs), and Computer Vision using Python, SQL, Scikit-learn, XGBoost, Random Forest, Support Vector Machines (SVMs), Convolutional Neural Networks (CNNs), Apache Spark, Apache Airflow, Apache Kafka, AWS, Azure, and Databricks. Hands-on experience building ETL/ELT pipelines and processing large-scale structured, semi-structured, image, video, and real-time streaming data while implementing workflow orchestration, statistical analysis, anomaly detection, predictive modeling, data quality frameworks, and production-grade AI systems. Holds a Master of Science in Data Science from Boston University and the AWS Certified Machine Learning Engineer – Associate certification, with applied experience spanning Computer Vision, hand tracking, gesture recognition, VR/XR applications, Natural Language Processing, Generative AI, phishing detection, image classification, and predictive modeling.

Abubakar O.

Vetted Prompt Engineering developer in the United States (UTC-5)

Machine Learning Engineer with 5 years of experience delivering production ML and applied AI systems for healthcare, insurance, enterprise, and government clients, specializing in document intelligence, multimodal extraction, retrieval and ranking, classification, and conversational analytics across AWS and Databricks. Owns evaluation, observability, and reliable production behavior. Delivered outcomes including 95% automation of manual coding work, 10+ engineering hours saved per week, and 25% lower customer churn in insurance retention workflows.