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Remote Generative Ai Engineer Jobs in Coppell, TX

AI Engineer

Addison, TX · On-site +1

$110K - $140K/yr

Flexible work options, including remote and hybrid opportunities, if eligible * Retirement Plan ... Develop generative AI solutions for text generation, summarization, audio-to-text transcription ...

AI Lead Engineer (Remote)

Dallas, TX · Remote

$104K - $138K/yr

AI Lead Engineer Dallas, TX (REMOTE) 15+ Years Must-Have Skills * Artificial Intelligence (AI ... Deep Learning * Generative AI (GenAI) * Large Language Models (LLMs) * Prompt Engineering

AI Lead Engineer

Dallas, TX · On-site +1

$101K - $133K/yr

AI Lead Engineer Dallas, TX (REMOTE) 15+ Years Must-Have Skills Artificial Intelligence (AI) & Machine Learning (ML) Deep Learning Generative AI (GenAI) Large Language Models (LLMs) Prompt ...

AI Lead Engineer

Dallas, TX · On-site +1

$101K - $133K/yr

AI Lead Engineer Dallas, TX (REMOTE) 15+ Years Must-Have Skills * Artificial Intelligence (AI) & Machine Learning (ML) * Deep Learning * Generative AI (GenAI) * Large Language Models (LLMs) * Prompt ...

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... Generative AI. In this role, you will craft and refine AI-driven solutions, turning innovative ...

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Showing results 1-20

Remote Generative Ai Engineer information

See Coppell, TX salary details

$35.1K

$107K

$176.8K

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

As of Aug 27, 2026, the average yearly pay for remote generative ai engineer in Coppell, TX is $106,962.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,600.00 and $139,900.00 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 job categories do people searching Remote Generative Ai Engineer jobs in Coppell, TX look for?

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

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

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

Infographic showing various Remote Generative Ai Engineer job openings in Coppell, TX as of August 2026, with employment types broken down into 25% Full Time, 50% Part Time, and 25% Contract. Highlights an 100% Remote job distribution, with an average salary of $106,962 per year, or $51.4 per hour.

AI Engineer

Addison, TX • On-site, Remote

Confie
Insurance Services • 1 - 5K employees

$110K - $140K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 17 days ago


Job description

Pay Range:
  • $110000 - $140000 / year

Our Perks & Benefits:_
  • Comprehensive benefits package including medical, dental, vision, and life insurance
  • Performance-based bonuses to reward your contributions*
  • Paid time off to recharge and maintain a healthy work-life balance
  • Flexible work options, including remote and hybrid opportunities, if eligible
  • Retirement Plan (401k) with company-matched contributions
  • Education Advancement, for employees and qualified dependents, via the Confie Enablement Scholarship Fund
  • Fitness Reimbursement - up to $15/month for gym memberships
  • Inclusive workplace through a strong commitment to Diversity, Equity, and Inclusion
  • Employee Assistance Program - confidential support for personal or professional challenges, at no cost
  • Extra Perks - optional plans for disability, hospital indemnity, health advocate program, universal life, critical illness, accident insurance, and even pet insurance

Purpose
Responsible for designing, developing, and deploying production-grade AI solutions including autonomous agents, generative AI applications, and RAG-based systems. You will leverage large language models (LLMs), agentic frameworks, and advanced machine learning techniques to automate workflows, improve customer experiences, and drive business innovation.
Essential Duties & Responsibilities
Design and deploy autonomous AI agents using frameworks like LangGraph, AutoGen, CrewAI, or OpenAI Assistants API for multi-step reasoning and task execution.
Implement function calling, tool use, and API integrations enabling LLMs to interact with enterprise systems, databases, and external applications.
Design agent memory systems including conversational memory, long-term knowledge retention, and context management strategies.
Build advanced RAG systems with vector databases, hybrid search (dense + sparse retrieval), and reranking for domain-specific chatbots and knowledge retrieval.
Develop generative AI solutions for text generation, summarization, audio-to-text transcription, and call center conversation insights using LLMs.
Develop advanced prompting strategies including chain-of-thought reasoning, few-shot learning, and structured output generation.
Integrate with AI platforms including Snowflake Cortex, OpenAI, Azure AI Studio, AWS Bedrock, and Anthropic Claude.
Implement AI observability, guardrails, and evaluation frameworks (RAGAs, TruLens, DeepEval) to ensure quality, safety, and reliability.
Conduct experiments and fine-tune models using techniques like LoRA and QLoRA to optimize performance for domain-specific use cases.
Deploy production solutions using containerization (Docker, Kubernetes), CI/CD pipelines, and cloud-native architectures.
Continuously monitor the performance of AI solutions and implement improvements.
Create high-level and detailed design documentation for AI solutions, including architecture diagrams and technology selection rationale.
Collaborate with cross-functional teams to identify and prioritize high-impact AI opportunities that drive significant business value.
Mentor and provide guidance to junior team members; participate in code reviews and maintain high-quality engineering standards.
Keep updated with advances in AI technology and find opportunities to upgrade existing solutions.
Adhere to best practices in data privacy and security when working with sensitive data.
Qualifications and Education Requirements
Minimum of 3 years of professional experience in AI engineering or related roles.
3+ years experience developing AI/ML solutions on platforms such as Snowflake, Azure, AWS , OpenAI, Databricks, or similar.
2+ years hands-on experience with Generative AI including LLM application development, RAG systems, and production deployments.
Experience with agentic AI frameworks (LangGraph, AutoGen, CrewAI, OpenAI Assistants API) and multi-agent orchestration.
Proficiency in Python, LangChain/LlamaIndex, and vector databases (Pinecone, Weaviate, Chroma, pgvector, Snowflake).
Expertise in prompt engineering including chain-of-thought, few-shot learning, and structured outputs (JSON mode, function calling).
Experience with evaluation frameworks for Generative AI (RAGAs, TruLens, DeepEval) in the context of text generation.
Understanding of AI safety concepts including guardrails, content filtering, hallucination mitigation, and red-teaming.
Experience with data preprocessing, feature engineering, and model evaluation techniques.
Solid understanding of software engineering principles and best practices.
Experience bringing GenAI projects through production and implementation with measurable business impact.
Soft Skills
Strong analytical and problem-solving skills.
Excellent communication skills with ability to articulate complex technical concepts to both technical and non-technical stakeholders.
Highly motivated and self-driven with ability to work independently and in collaborative team environments.
Ability to think creatively about applying AI to solve business problems.
Effective time management and organizational skills to manage multiple projects simultaneously.
Continuous learning mindset and ability to adapt to new technologies in the fast-evolving AI landscape.
Preferred Skills
Bachelor's or Master's degree in Computer Science, Data Science, or a related field is preferred.
Relevant certifications in AI/ML platforms (AWS, Azure, Google Cloud) or related areas are a plus.
Familiarity with the call center environments and operational insurance platforms is preferred
Other Duties
This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice
Notice
As permitted by applicable law and from time-to-time, Confie may use a computer system that has elements of artificial intelligence to help make decisions about your employment, including recruitment, hiring, renewal of employment, or the terms and conditions of your employment. Employees with questions about Confie's use of these computer systems should contact Human Resources at talent@confie.com
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws.
For further information, please review the Know Your Rights notice from the Department of Labor.

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About Confie

Sourced by ZipRecruiter

Industry

Insurance services

Company size

1,001 - 5,000 Employees

Headquarters location

Huntington Beach, CA, US

Year founded

2008