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Senior Generative Ai Engineer Jobs (NOW HIRING)

Futran Tech Solutions Pvt. Ltd.

Al/ML Lead

Tampa, FL

Senior Generative AI Developer Location - Dallas, TX I Tampa, FL I Jersey City, NJ (3 days WFO) Role - AI/ML Lead We are seeking an experienced Senior Generative AI Developer to design and implement ...

Futran Tech Solutions Pvt. Ltd.

Lead AI/ML Engineer

Tampa, FL · Hybrid

$93K - $122K/yr

We are seeking an experienced Senior Generative AI Developer to design and implement cutting-edge AI solutions leveraging Retrieval-Augmented Generation (RAG) techniques. The ideal candidate will ...

Genesis10

Generative AI Engineer - Remote

Genesis10 is currently seeking a Generative AI Engineer for a Regional Financial Institution located in Green Bay, WI. This expert-level role focuses on building production-grade Generative AI ...

Futran Tech Solutions Pvt. Ltd.

Lead AI/ML Engineer

Tampa, FL · On-site

$96K - $127K/yr

We are seeking an experienced Senior Generative AI Developer to design and implement cutting-edge AI solutions leveraging Retrieval-Augmented Generation (RAG) techniques. The ideal candidate will ...

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Senior Generative Ai Engineer information

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$59.5K

$126.6K

$183.5K

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

As of Jun 21, 2026, the average yearly pay for senior generative ai engineer in the United States is $126,557.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,500.00 and $143,500.00 per year, depending on experience, location, and employer.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles such as Senior Generative AI Engineers or AI Directors that offer compensation in this range, often including base salary, bonuses, and stock options. These positions usually require advanced expertise in machine learning, deep learning, and experience with large language models or generative AI tools, along with a strong track record of innovation and leadership in AI development.

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

AspectSenior Generative Ai EngineerMachine Learning Engineer
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with generative modelsBachelor's/Master's in CS, Data Science, or related; strong ML fundamentals
Work EnvironmentResearch and development focused, often in AI startups or tech companiesData analysis, model development, often across various industries
Employer & Industry UsageTech firms, AI startups, research institutionsTech, finance, healthcare, and other sectors utilizing ML solutions

The main difference is that Senior Generative Ai Engineers specialize in developing and optimizing generative models like GPT or GANs, focusing on AI creativity and content generation. Machine Learning Engineers have a broader scope, working on various ML algorithms and applications across multiple industries. Both roles require strong technical skills, but the Senior Generative Ai Engineer's expertise is more specialized in generative AI technologies.

What is the salary of senior Generative AI developer?

The salary of a senior Generative AI engineer typically ranges from $120,000 to $180,000 annually, depending on experience, location, and company size. Professionals with expertise in machine learning frameworks, deep learning, and large language models tend to earn at the higher end of this range.

What engineers make 500,000?

Senior Generative AI Engineers can earn $500,000 or more annually, especially those with advanced skills in machine learning, deep learning, and experience with large language models. Compensation often includes base salary, bonuses, and stock options, particularly in high-growth tech companies or startups focused on AI development.

What does a Senior Generative AI Engineer do?

A Senior Generative AI Engineer designs, develops, and implements advanced artificial intelligence models, particularly those focused on generating content such as text, images, or audio. They work with large datasets, build and fine-tune generative models like GPT or diffusion models, and oversee the deployment of these systems into production environments. Additionally, they collaborate with cross-functional teams to integrate AI capabilities into products, optimize model performance, and ensure ethical AI practices are followed.

What are some of the unique challenges Senior Generative AI Engineers face when deploying models in production environments?

Senior Generative AI Engineers often encounter challenges such as ensuring model reliability, addressing biases in generated outputs, and managing the significant computational resources required for deployment. There's also a strong need to collaborate with cross-functional teams, including data engineers, product managers, and domain experts, to ensure the solutions align with business goals and maintain user trust. Balancing innovation with ethical considerations and scalability is crucial in this fast-evolving field.

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

To thrive as a Senior Generative AI Engineer, you need deep expertise in machine learning, deep learning, and natural language processing, typically backed by an advanced degree in computer science or related fields. Proficiency in frameworks like TensorFlow or PyTorch, experience with cloud platforms (e.g., AWS, Azure), and familiarity with large language models are essential, along with relevant certifications. Strong problem-solving skills, creativity, and effective communication set standout engineers apart in this role. These skills and qualities are crucial for designing innovative AI solutions, collaborating across teams, and advancing the capabilities of generative models in real-world applications.

Which 3 jobs will survive AI?

For a Senior Generative AI Engineer, roles that require complex problem-solving, creativity, and human judgment are more likely to persist, such as AI research scientist, data scientist, and AI ethics specialist. These positions involve tasks that are difficult to fully automate and often require specialized expertise, critical thinking, and domain knowledge. Skills in machine learning, programming, and understanding of ethical considerations are essential for these roles to remain relevant as AI advances.
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Senior Generative Ai Engineer jobs near you
Infographic showing various Senior Generative Ai Engineer job openings in the United States as of June 2026, with employment types broken down into 82% Full Time, and 18% Contract. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $126,557 per year, or $60.8 per hour.

Al/ML Lead

Futran Tech Solutions Pvt. Ltd.

Jersey City, NJ

Other

Posted 11 days ago

Job description

Senior Generative AI Developer

Location - Dallas, TX I Tampa, FL I Jersey City, NJ (3 days WFO)

Role - AI/ML Lead

Job Description: We are seeking an experienced Senior Generative AI Developer to design and implement cutting-edge AI solutions leveraging Retrieval-Augmented Generation (RAG) techniques. The ideal candidate will have strong expertise in Python programming, FastAPI, and cloud platforms (AWS, Azure, or GCP). This role requires a deep understanding of system architecture design, scalable APIs, and end-to-end AI solution development.

Key Responsibilities:
  • Architect and develop Generative AI applications using RAG frameworks for enterprise-scale solutions.
  • Design and implement robust system architectures for AI-driven platforms ensuring scalability, security, and performance.
  • Build and optimize APIs using FastAPI for seamless integration with AI models and data pipelines.
  • Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows.
  • Implement data ingestion, preprocessing, and retrieval mechanisms for large-scale knowledge bases.
  • Ensure compliance with best practices for cloud deployment (AWS, Azure, or GCP).
  • Conduct performance tuning and optimization of AI models and APIs.
  • Stay updated with the latest advancements in Generative AI, LLMs, and RAG methodologies.
Required Skills & Qualifications:
  • 8+ years of professional experience in software development and system design.
  • Strong proficiency in Python and experience with FastAPI for API development.
  • Hands-on experience with Generative AI frameworks and RAG architectures.
  • Solid understanding of system and architecture design principles for distributed applications.
  • Experience deploying solutions on any major cloud platform (AWS, Azure, GCP).
  • Familiarity with vector databases, embedding models, and retrieval pipelines.
  • Strong problem-solving skills and ability to work in a fast-paced environment.
Preferred Qualifications:
  • Experience with LLM fine-tuning, prompt engineering, and model evaluation.
  • Knowledge of containerization (Docker) and orchestration (Kubernetes).
  • Exposure to CI/CD pipelines and DevOps practices.

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