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Freelance Generative Ai Engineer Jobs (NOW HIRING)

Generative AI Engineer

Fort Worth, TX ยท On-site

$120K - $170K/yr

Generative AI Engineer Location: Remote (U.S.) Salary Range: $120k to $170k About the Role We are seeking a highly skilled Generative AI Engineer to lead the end-to-end delivery of production-grade ...

Generative AI Engineer (Agentic AI / LLM Solutions) Location: Phoenix, AZ / New York City, NY (Hybrid/Onsite) Duration: 12+ Months Contract Interview Mode: Video Interview Position Overview We are ...

The role is for an AI Engineer focused on designing, developing, and implementing machine learning and AI models, particularly Generative AI applications and Agentic AI solutions. The engineer will ...

Senior Generative AI Engineer

Potomac, MD ยท On-site +1

$57.25 - $73.75/hr

Our client is seeking a Senior Generative AI Engineer to drive internal initiatives and provide AI engineering support for a major federal agency. The role centers on developing cloud-native ...

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How much do freelance generative ai engineer jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for freelance generative ai engineer in the United States is $47.71, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $61.78 per hour, depending on experience, location, and employer.

What are the most common challenges faced by freelance Generative AI Engineers when working with clients on custom AI solutions?

Freelance Generative AI Engineers often encounter challenges such as managing client expectations regarding project timelines and the complexity of AI models, especially when clients have limited technical knowledge. Ensuring clear communication about data requirements, model capabilities, and ethical considerations is crucial for successful project delivery. Additionally, freelancers must stay up to date with rapidly evolving AI frameworks and tools while balancing multiple projects and deadlines. Building robust documentation and maintaining transparency throughout the development process can help mitigate misunderstandings and foster long-term client relationships.

What is a Freelance Generative AI Engineer?

A Freelance Generative AI Engineer is a professional who works independently to design, build, and deploy artificial intelligence models that can generate new data, such as text, images, or music. These engineers typically specialize in technologies like generative adversarial networks (GANs), large language models (LLMs), and other machine learning frameworks. They collaborate with clients or companies on a project-by-project basis, offering expertise in AI model development, fine-tuning, and integration. Being freelance, they have the flexibility to work with multiple clients across various industries, including tech, media, and entertainment.

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

To thrive as a Freelance Generative AI Engineer, you need a deep understanding of machine learning, neural networks, and programming languages such as Python, often supported by a degree in computer science or related field. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms, and experience with AI model deployment are typically required. Strong problem-solving abilities, adaptability, and effective communication help you collaborate with clients and address evolving project needs. These skills are crucial for developing innovative AI solutions, meeting client expectations, and staying competitive in a rapidly changing field.
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Generative AI Engineer

Generative AI Engineer

Prosum Inc.

Fort Worth, TX โ€ข On-site

$120K - $170K/yr

Full-time

Posted 13 days ago


Job description

Job Description
Generative AI Engineer
Location: Remote (U.S.)
Salary Range: $120k to $170k
About the Role
We are seeking a highly skilled Generative AI Engineer to lead the end-to-end delivery of production-grade AI systems. This role is responsible for designing, building, deploying, and continuously optimizing scalable generative AI solutions that integrate seamlessly with enterprise systems. You will act as a technical authority, shaping best practices and driving innovation across AI initiatives.
What You'll Do
  • Own the full lifecycle of generative AI systems, from architecture and development to deployment, monitoring, and optimization
  • Design and build LLM-powered applications, including agent-based workflows, multi-step RAG pipelines, and enterprise AI solutions
  • Establish and enforce engineering standards across prompt design, orchestration, structured outputs, and workflow lifecycle management
  • Serve as a technical leader for GenAI, guiding architecture decisions and best practices
  • Integrate AI systems with enterprise data, internal APIs, and cloud-native services
  • Evaluate and select models, implement routing strategies, and optimize for latency, cost, and performance
  • Continuously assess emerging AI tools and improve existing systems
  • Own system performance across reliability, scalability, throughput, and cost efficiency
  • Build and maintain observability frameworks (monitoring, tracing, logging, alerting)
  • Design and manage CI/CD pipelines, including versioning and release processes
  • Lead incident response and root cause analysis, implementing long-term fixes
  • Develop evaluation pipelines for LLM outputs, including regression testing and failure analysis
  • Implement safeguards such as human-in-the-loop workflows, schema validation, and output controls
  • Ensure systems are secure against prompt injection, data leakage, and unauthorized access
  • Collaborate with leadership and cross-functional teams to define and execute AI initiatives
  • Provide hands-on technical guidance, mentoring, and code reviews
  • Promote iterative delivery with frequent releases and continuous feedback loops
Required Qualifications
  • Proven experience building and deploying production-grade LLM or generative AI systems
  • Strong expertise in prompt design, orchestration, and model tradeoffs
  • Experience developing evaluation frameworks for AI outputs and validating quality
  • Solid background in distributed systems and production software engineering
  • Experience with CI/CD pipelines, release management, and operational ownership
  • Demonstrated ability to define technical standards and influence architecture decisions
  • Experience with cloud-native systems, APIs, and event-driven architectures (Azure or similar)
  • Experience integrating AI solutions with enterprise data and security requirements
  • Bachelor's degree in a technical field or equivalent practical experience
Preferred Qualifications
  • Experience with advanced RAG pipelines and agent-based AI systems in production
  • Familiarity with cloud AI services and modern infrastructure tooling
  • Experience with Python-based AI frameworks and data pipelines
  • Experience with containerization and deploying AI workloads
  • Knowledge of responsible AI practices and governance
  • Domain experience in areas such as product data, ERP, ecommerce, or analytics platforms

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