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Gpt Engineer Jobs (NOW HIRING)

Staffingine LLC

GenAI Engineer

Redmond, WA · On-site

GenAI Engineer Job Location: Redmond, WA Job Type: Contract * Design and implement RAG pipelines ... Fine-tune and evaluate LLMs (e.g., GPT, LLaMA, Ollama) for tasks such as QA, summarization, NER ...

AHEAD

Forward Deployed Engineer

Charleston, WV · Remote

$160K - $190K/yr

The Forward Deployed Engineer (FDE) is a hands-on role embedded within AHEAD's internal AI ... You will design, build, and run production AI applications on enterprise GPT platforms, including ...

AHEAD

Forward Deployed Engineer

The Forward Deployed Engineer (FDE) is a hands-on role embedded within AHEAD's internal AI ... You will design, build, and run production AI applications on enterprise GPT platforms, including ...

Noblesoft Technologies

AI/ML Engineer

Minneapolis, MN · Remote

$106K - $131K/yr

AI/ML Engineer Location: Minneapolis, MN(Remote) 1. Design, develop, test, document, and deploy ... AI/ML integration with Salesforce CRM (Einstein/Einstein GPT and external technologies like Python ...

Raks Group

QA Engineer with Gen AI

Chicago, IL

We are seeking a highly skilled and innovative AI Solutions Engineer who possesses deep expertise in GenAI-based application development leveraging Large Language Models (LLMs) such as GPT, Claude ...

TMS

AI/ ML Engineer

New York, NY · Remote

$60 - $62/hr

Design and develop GenAI solutions using LLMs (GPT, Claude, LLaMA, etc.) * Implement prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning techniques * Build and integrate AI ...

Whiztek Corp

Gen AI Engineer

Chicago, IL · On-site

... GPT-40 and Google Gemini technologies. You will work exclusively on hands-on development ... Programming Skills: Expertise in Python and tools like Hugging Face, Langchain, and OpenAI API.

AMSYS Talent

Azure OpenAI / AI Cloud Engineer

Houston, TX · On-site

$50.25 - $67.25/hr

Deploy and manage Azure OpenAI services (GPT models, embeddings, etc.) * Build and optimize Azure ... Collaborate with data science and cloud engineering teams to operationalize AI models Required ...

CYNET SYSTEMS

Prompt Engineering Specialist

Hartford, CT · On-site

$55 - $60/hr

Pay Range: $55/hr - $60/hr Requirement/Must Have: * 1+ years of hands-on experience with LLMs (GPT ... Prompt engineering. * Snowflake Cortex. * Healthcare domain knowledge. * LLMs. * GPT. * Prompt ...

Vy Systems

Fullstack AI Engineer

Washington, DC · On-site

Proven expertise (5+ years) in full stack AI engineering, including design, development, and ... Hands-on experience with LLMs (e.g., GPT-based models), GenAI frameworks, or Copilot tools for AI ...

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Gpt Engineer information

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

To thrive as a GPT Engineer, you need a solid background in machine learning, natural language processing (NLP), and proficiency in programming languages such as Python, typically supported by a degree in computer science or a related field. Familiarity with deep learning frameworks like TensorFlow or PyTorch, as well as experience with large language models (LLMs) and cloud platforms, is highly valuable. Strong problem-solving, communication, and collaboration skills help you navigate complex projects and effectively work within interdisciplinary teams. These skills and qualifications are crucial for developing, fine-tuning, and deploying advanced AI models that meet real-world needs and ensure ethical, high-performance outcomes.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as an AI researcher, machine learning engineer, or AI director, often requiring advanced skills in programming, data analysis, and deep learning. These roles usually involve leadership, innovation, and significant responsibility, and they may be found in large tech companies or specialized AI firms with competitive compensation packages. Such salaries are often associated with seniority, expertise, and the ability to lead complex projects.

What is a GPT Engineer?

A GPT Engineer is a specialist who designs, develops, and optimizes applications using Generative Pre-trained Transformers (GPT) like those created by OpenAI. Their work involves integrating GPT models into software products, fine-tuning models for specific business needs, and ensuring the responsible and efficient use of AI technologies. GPT Engineers often collaborate with data scientists, product managers, and other developers to build innovative AI-driven solutions across various industries.

What is the difference between Gpt Engineer vs AI Developer?

AspectGpt EngineerAI Developer
Required CredentialsKnowledge of NLP, machine learning, programming skillsComputer science degree, programming, machine learning expertise
Work EnvironmentFocus on language models, API integration, fine-tuning GPT modelsBroader AI projects, including computer vision, robotics, and data analysis
Industry UsagePrimarily in tech, startups, and companies utilizing NLP solutionsWide range of industries including tech, healthcare, finance, and research

Gpt Engineers specialize in developing and fine-tuning language models like GPT, focusing on NLP applications. AI Developers have a broader scope, working on various AI technologies across multiple industries. While Gpt Engineers focus on language-specific AI, AI Developers handle diverse AI projects, making Gpt Engineer a specialized role within the larger AI development field.

What engineer makes $500,000 a year?

Senior software engineers, especially those working in high-demand fields like artificial intelligence, machine learning, or at major tech companies, can earn $500,000 or more annually through base salary, bonuses, and stock options. Achieving this level typically requires extensive experience, advanced skills, and often leadership roles or specialized expertise in cutting-edge technologies.

How do GPT Engineers typically collaborate with data scientists and product teams during the model development process?

GPT Engineers frequently work alongside data scientists to refine training datasets, evaluate model outputs, and implement prompt engineering strategies. They also coordinate with product teams to understand user requirements, integrate GPT models into applications, and ensure a seamless user experience. Regular cross-functional meetings and collaborative problem-solving are standard, making strong communication skills essential for success in this role.

What does gpt engineer do?

A GPT engineer designs, develops, and fine-tunes AI language models based on the GPT architecture. They work with large datasets, implement model training, optimize performance, and may use tools like Python and machine learning frameworks to create applications such as chatbots or content generators.

How much do GPT prompt engineers make?

GPT prompt engineers typically earn between $70,000 and $150,000 annually, depending on experience, location, and the complexity of tasks. Senior roles or those with specialized skills in AI and machine learning can command higher salaries, especially in tech hubs or companies focusing heavily on AI development.
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Gpt Engineer jobs near you
Infographic showing various Gpt Engineer job openings in the United States as of July 2026, with employment types broken down into 95% Full Time, 2% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.
GenAI Engineer

GenAI Engineer

Staffingine LLC

Redmond, WA • On-site

Contractor

Posted 24 days ago

Job description

Job Title: GenAI Engineer
Job Location: Redmond, WA
Job Type: Contract

Job Description:

  • Design and implement RAG pipelines using hybrid search, vector, keyword, semantic ranking, and metadata enrichment
  • Apply chunking strategies (fixed-size, recursive, semantic, agentic) to optimize document segmentation for retrieval and embedding
  • Fine-tune and evaluate LLMs (e.g., GPT, LLaMA, Ollama) for tasks such as QA, summarization, NER, and sentiment analysis
  • Build multi-agent systems
  • Integrate AI capabilities into enterprise applications using Azure OpenAI, Cognitive Search, Azure Functions, and Power Automate
  • Collaborate with stakeholders to translate business needs into scalable AI solutions
  • Ensure model reliability, performance, and ethical compliance across deployments