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Generative Ai Salary Jobs (NOW HIRING)

Prosum Inc.

Generative AI Engineer

Fort Worth, TX · On-site

$120K - $165K/yr

DFW preferred or open to candidates working remotely in EST/CST timezones Salary Range: $120k to $165k About the Role We are seeking a highly skilled Generative AI Engineer to lead the end-to-end ...

Stackruit Ltd.

Generative AI Engineer

Dallas, TX · On-site

$100 - $130/hr

Work on various project phases, from ideation to deployment, across generative AI and traditional ... Competitive salary, benefits package, and training opportunities. * Be part of a team that values ...

Judge Group, Inc.

Generative AI Engineer

Buffalo, NY · On-site

$65 - $75/hr

Buffalo, NY Salary: $65.00 USD Hourly - $75.00 USD Hourly Description: Title : Generative Ai Engineer Contract Length: Up to 18 Months W2 Contract Location: Buffalo, NY Remote Travel: Potential ...

Hearst

Senior Engineer, Generative AI

New York, NY · On-site

$114K - $157K/yr

Design and develop Generative AI applications and features using modern LLM APIs and open-source ... A final decision on the successful candidate's starting salary will be based on a number of ...

Figure

Helix AI Engineer, Generative AI

San Jose, CA

$200K - $400K/yr

Figure is an AI robotics company developing autonomous general-purpose humanoid robots. Our goal is ... Publication record in machine learning, computer vision, or generative modeling The US base salary ...

Innodata Inc.

Generative AI Associate

$15/hr

We provide a range of transferable solutions, platforms, and services for Generative AI / AI ... Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for ...

Figure

Helix AI Engineer, Generative AI

San Jose, CA · On-site

$200K - $400K/yr

Figure is an AI robotics company developing autonomous general-purpose humanoid robots. Our goal is ... Publication record in machine learning, computer vision, or generative modeling The US base salary ...

Citigroup, Inc.

Lead Generative AI Developer

New York, NY · On-site

$176K - $265K/yr

About the Role We are looking for a Lead Generative AI Developer to join our COO Technology ... New York New York United States Primary Location Full Time Salary Range: $176,720.00 - $265,080.00 ...

Citigroup Inc.

Lead Generative AI Developer

Manhattan, NY · On-site

$177 - $265/hr

About the Role We are looking for a Lead Generative AI Developer to join our COO Technology ... New York New York United States Primary Location Full Time Salary Range: $176,720.00 - $265,080.00 ...

Innodata Inc.

Generative AI Associate

$15/hr

We're on the lookout for smart, savvy, and curious Generative AI Specialist to join our global ... Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for ...

@Orchard

Senior Azure Generative AI Engineer

Dallas, TX · On-site

$95/hr

Senior Azure Generative AI Engineer Dallas TX @Orchard LLC is seeking a Senior Azure Generative AI ... The anticipated range for a base salary for this role is between $95-115K. There may be some ...

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Generative Ai Salary information

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$30K

$113.1K

$164.5K

How much do generative ai salary jobs pay per year?

As of Sep 2, 2026, the average yearly pay for generative ai salary in the United States is $113,102.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,000.00 and $154,000.00 per year, depending on experience, location, and employer.

What is the average salary for a generative AI professional?

The average salary for a professional working in Generative AI varies depending on experience, role, and location. In the United States, entry-level positions typically start around $120,000 per year, while experienced engineers and researchers can earn between $180,000 and $300,000 or more, especially at leading tech companies. Factors such as educational background, specialization in areas like natural language processing or computer vision, and industry demand can significantly influence compensation. Additionally, many roles offer bonuses, stock options, or other benefits that add to total compensation.

What are some common challenges faced by professionals working in generative AI roles?

Professionals in generative AI roles often encounter challenges such as staying current with rapidly evolving technologies and research, managing large and complex datasets, and ensuring that generated outputs are both ethical and high-quality. Additionally, effective collaboration with cross-functional teams—such as data scientists, software engineers, and product managers—is crucial to successfully integrate generative models into real-world applications. These roles require continuous learning and adaptability to address new technical and ethical considerations as the field progresses.

What are the key skills and qualifications needed to thrive as a generative AI engineer, and why are they important?

To thrive as a Generative AI Engineer, you need a strong background in machine learning, deep learning, and programming (especially Python), often supported by a degree in computer science or related fields. Familiarity with frameworks like TensorFlow, PyTorch, and experience using cloud computing platforms are typically required, along with knowledge of generative models such as GANs and transformers. Creative problem-solving, collaboration, and effective communication are key soft skills that set top performers apart in this role. These skills ensure engineers can design innovative AI models, work seamlessly in teams, and drive successful AI solutions from concept to deployment.

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

AspectGenerative Ai SalaryMachine Learning Engineer Salary
Required CredentialsDegree in Computer Science, AI, or related fields; experience with AI modelsDegree in Computer Science, Data Science, or related fields; programming skills
Work EnvironmentTech companies, AI startups, research labsTech firms, finance, healthcare, and other industries
Industry UsageDeveloping AI models like chatbots, image generatorsBuilding predictive models, data analysis, system deployment

Generative AI specialists focus on creating models that generate content, while Machine Learning Engineers develop algorithms for predictive analytics. Both roles require strong technical skills and often overlap in AI projects, but their core responsibilities differ. Salary ranges vary based on experience, location, and industry demand.

Is Generative AI a good career path?

Generative AI is a growing field with increasing demand for professionals skilled in machine learning, deep learning, and neural networks. Careers in this area often require knowledge of programming languages like Python and familiarity with AI frameworks such as TensorFlow or PyTorch. It offers opportunities in research, development, and deployment across various industries, making it a promising career choice for those interested in AI technology.
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Generative Ai Salary jobs near you
Infographic showing various Generative Ai Salary job openings in the United States as of August 2026, with employment types broken down into 86% Full Time, 7% Part Time, and 7% Contract. Highlights an 66% In-person, 7% Hybrid, and 27% Remote job distribution, with an average salary of $113,102 per year, or $54.4 per hour.

Generative AI Engineer

Prosum Inc.

Fort Worth, TX • On-site

$120K - $165K/yr

Other

Re-posted 8 days ago

Job description

Job Description
Generative AI Engineer
Location: DFW preferred or open to candidates working remotely in EST/CST timezones
Salary Range: $120k to $165k
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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