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Remote Generative Ai Engineer Jobs in Prosper, TX

Tanium

Corporate AI Engineer

Addison, TX · On-site +1

$154K - $200K/yr

Hands-on experience implementing AI-enabled solutions, including generative AI concepts such as prompt engineering, embeddings, or RAGwith best-in-class AI technologies from OpenAI, Anthropic ...

The Mutual Group

Lead AI Engineer - AWS Platform

Dallas, TX · On-site +1

$130K - $190K/yr

... AI and Generative AI across core insurance platforms (Policy, Claims, Billing, and Enterprise ... Flexible work schedules and hybrid/remote options for eligible positions * Educational assistance ...

Cloudelligent

AWS Solutions Architect- AI/ML

Dallas, TX · Remote

$64 - $84/hr

AWS Solutions Architect- AI/ML Employment Time: Full-Time This Is a fully remote position with ... Design and implement cloud solutions that integrate data engineering, Generative AI, and machine ...

ZipStaff Inc.

Senior Lead AI Developer

Irving, TX · Remote

$56 - $60/hr

Location: Remote (U.S.). Employment Type: Contract (W2 through ZipStaff). About the Opportunity ... Design and implement Generative AI, Machine Learning, automation, and complex agentic workflow ...

Hirekeyz Inc

AI/Full Stack Engineer

Irving, TX · Remote

Role: AI/Full Stack Engineer Location: Irving, TX (Remote) Job Type: Contract We are rapidly ... Exposure to Generative AI concepts and their practical application. A strong focus on Applied AI ...

Bread Financial

Senior Staff Agentic AI Engineer

Frisco, TX · On-site +1

$99K - $134K/yr

... ML, Generative AI, or agentic systems (e.g., LLM-powered applications, LangChain, LangGraph ... Normal office environment. (Remote or Hybrid), 3 to 4 days per month are required in office if ...

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All JobsGenerative Ai Engineer JobsRemote Generative Ai Engineer JobsRemote Generative Ai Engineer Jobs in Prosper, TX

Remote Generative Ai Engineer information

See Prosper, TX salary details

$34.8K

$106.1K

$175.4K

How much do remote generative ai engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for remote generative ai engineer in Prosper, TX is $106,107.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,000.00 and $138,700.00 per year, depending on experience, location, and employer.

What is a remote generative AI engineer?

A Remote Generative AI Engineer is a technology professional who specializes in developing, training, and deploying artificial intelligence models that can generate new content—such as text, images, audio, or video—while working from a remote location. These engineers typically work with advanced machine learning techniques like deep learning, neural networks, and large language models. Their responsibilities often include designing algorithms, optimizing model performance, and collaborating with distributed teams to build innovative AI-driven solutions. The remote aspect allows them to perform their duties from anywhere with internet access, offering flexibility and access to global opportunities.

What are the key skills and qualifications needed to thrive as a remote generative AI engineer?

To thrive as a Remote Generative AI Engineer, you need a solid background in computer science, machine learning, and deep learning, typically with a relevant degree and experience in building AI models. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (such as AWS or Azure), and version control systems like Git is essential. Strong problem-solving, self-motivation, and effective remote communication set outstanding engineers apart in this role. These skills are crucial for developing innovative AI solutions, collaborating across distributed teams, and delivering impactful results in a remote work environment.

How do remote generative AI engineers typically collaborate with cross-functional teams to deliver AI-driven solutions?

Remote Generative AI Engineers often work closely with data scientists, product managers, and software engineers to integrate generative AI models into products or services. Collaboration is usually facilitated through virtual meetings, code repositories, and project management tools, enabling seamless communication across different time zones. Regular check-ins and sprint reviews help ensure alignment on goals, while documentation and clear communication are essential for maintaining project momentum. This collaborative environment not only fosters innovation but also allows engineers to gain exposure to a variety of perspectives and expertise.

What is the difference between Remote Generative Ai Engineer vs Remote Machine Learning Engineer?

AspectRemote Generative Ai EngineerRemote Machine Learning Engineer
Required CredentialsBachelor's or higher in CS, AI, or related; experience with generative modelsBachelor's or higher in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentCollaborates on AI model development, focuses on generative models like GPT, GANsDevelops and deploys ML models for various applications, including predictive analytics
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, and data-driven industries

While both roles involve AI and machine learning, a Remote Generative Ai Engineer specializes in creating models that generate content, such as text or images, using generative techniques. In contrast, a Remote Machine Learning Engineer works on a broader range of ML models for predictive or classification tasks. The roles often overlap but differ in focus and application.

How much does a remote generative AI engineer make?

A remote generative AI engineer typically earns between $100,000 and $160,000 annually, depending on experience, skills, and the company's location. Senior roles or those with specialized expertise in machine learning and deep learning can command higher salaries, especially with proficiency in tools like TensorFlow or PyTorch.

What are the best remote generative AI engineer jobs?

Remote generative AI engineer jobs are available across technology companies, research institutions, and startups, often requiring skills in machine learning frameworks like TensorFlow or PyTorch and experience with natural language processing or computer vision. These roles typically involve developing and deploying AI models remotely, with some positions offering flexible schedules and requiring certifications or advanced degrees in computer science or related fields.

What is the average salary of a remote generative AI engineer?

The average salary for a remote generative AI engineer typically ranges from $100,000 to $150,000 annually, depending on experience, skills in machine learning frameworks, and the complexity of projects. Senior roles or those with specialized expertise in deep learning and large language models can earn higher compensation. Remote positions often offer competitive pay comparable to on-site roles in the tech industry.

What are the most commonly searched types of Generative Ai Engineer jobs in Prosper, TX?

The most popular types of Generative Ai Engineer jobs in Prosper, TX are:

What are popular job titles related to Remote Generative Ai Engineer jobs in Prosper, TX?

For Remote Generative Ai Engineer jobs in Prosper, TX, the most frequently searched job titles are:

What job categories do people searching Remote Generative Ai Engineer jobs in Prosper, TX look for?

The top searched job categories for Remote Generative Ai Engineer jobs in Prosper, TX are:

What cities near Prosper, TX are hiring for Remote Generative Ai Engineer jobs?

Cities near Prosper, TX with the most Remote Generative Ai Engineer job openings:

Remote Generative Ai Engineer jobs near you

Generative AI Leader/Architect

Tiger Analytics Inc.

Dallas, TX • Remote

Full-time

Re-posted 13 days ago

Job description

Tiger Analytics is looking for experienced GenAI Architect to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

We are looking for a hands-on Engineering Lead with deep expertise in Generative AI (GenAI), Large Language Models (LLM) / Small Language Models (SLM) who can lead the design, development, and integration of AI-powered components into real-world, production-grade applications. This role demands strong engineering leadership and best practices, a practical approach to application development and system design with applied AI, fluency in modern AI tools, frameworks, cloud-native application stacks, and preferably knowledge of healthcare domain intricacies. You will lead the technical delivery of AI-powered features for a variety of horizonal and vertical healthcare use cases— all while ensuring compliance with enterprise integration standards.

Requirements

Responsibilities

    • Lead the architecture, design, and implementation of GenAI/Agentic AI based solutions into real-world enterprise-ready applications.
    • Collaborate with AI/ML teams to operationalize models using APIs, embeddings, vector databases, and prompt engineering techniques.
    • Own full-stack development and integration of GenAI features into web/mobile applications.
    • Establish best practices for scalable, secure, and maintainable AI-powered application development.
    • Optimize application performance, latency, and reliability of AI features in production.
    • Drive DevOps practices for continuous delivery and monitoring of AI-enabled services in production.
    • Mentor engineers and guide code reviews, architectural decisions, and DevOps practices.
    • Guide engineering teams in code quality, architectural reviews, and technical mentoring.
    • Evaluate emerging GenAI tools and LLM frameworks (OpenAI, LangChain etc.) and make build-vs-buy recommendations.
    • Oversee application-level development, testing, and deployment.

Requirements

  • 10+ years of full-stack application engineering experience, with at least 2 years leading cross-functional teams.
  • Architect agentic AI systems using LangChain/LangGraph, CrewAI, and OpenAI Agentic SDK
  • Design RAG architectures with hybrid search, vector databases, and knowledge graphs
  • Optimize multi-agent workflows using reinforcement learning, dynamic orchestration, and memory management.
  • Deploy scalable AI solutions on AWS/GCP (SageMaker, Vertex AI, Bedrock API).
  • An Ideal Candidate would be of someone who has-
    8+ years in AI/ML engineering with large-scale deployment expertise.
    Proficient in prompt engineering (zero-shot, chain-of-thought) and LLM evaluation.
    Strong background in insurance/financial domains (preferred)
    Agile collaborator with GitHub/VS Code proficiency

Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.