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Senior Generative Ai Engineer Jobs (NOW HIRING)

OpenDataJobs

Senior Generative AI Engineer

Washington, DC · On-site +1

$62.50 - $80.75/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 ...

OpenDataJobs

Senior Generative AI Engineer

Potomac, MD · Remote

$56.50 - $73/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 ...

OpenDataJobs

Senior Generative AI Engineer

Potomac, MD · 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 ...

Programmers.io

Senior Generative AI Developer

Irving, TX · On-site

$116.70K - $157K/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 ...

AMSYS Talent

Sr Gen AI Engineer

Houston, TX · On-site

$99.70K - $137K/yr

Senior Generative AI Engineer (Azure / RAG / LLM) We're looking for a hands-on Senior AI Engineer to build and deploy production-grade generative AI solutions. This role focuses on taking use cases ...

Hearst

Senior Engineer, Generative AI

Manhattan, NY · On-site

$114.80K - $157.70K/yr

We are seeking a dynamic and innovative Senior Generative AI Engineer to join our team, reporting directly to Hearst's Chief Product & AI Strategist. This role sits at the intersection of software ...

Hearst

Senior Engineer, Generative AI

Manhattan, NY

$114.80K - $157.70K/yr

We are seeking a dynamic and innovative Senior Generative AI Engineer to join our team, reporting directly to Hearst's Chief Product & AI Strategist. This role sits at the intersection of software ...

Hearst

Senior Engineer, Generative AI

Manhattan, NY

$114.80K - $157.70K/yr

We are seeking a dynamic and innovative Senior Generative AI Engineer to join our team, reporting directly to Hearst's Chief Product & AI Strategist. This role sits at the intersection of software ...

Hearst

Senior Engineer, Generative AI

New York, NY

$114.30K - $157K/yr

We are seeking a dynamic and innovative Senior Generative AI Engineer to join our team, reporting directly to Hearst's Chief Product & AI Strategist. This role sits at the intersection of software ...

Light and Wonder, Inc.

Senior Generative AI Engineer

Austin, TX · On-site

$121.40K - $160.10K/yr

Position Summary About the Team We are building a tight-knit, senior engineering group based in ... Our mission is to design, deliver, and scale production-grade Agentic AI workflows that execute ...

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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 May 31, 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 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.

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 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 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.

More about Senior Generative Ai Engineer jobs
What cities are hiring for Senior Generative Ai Engineer jobs? Cities with the most Senior Generative Ai Engineer job openings:
What are the most commonly searched types of Generative Ai Engineer jobs? The most popular types of Generative Ai Engineer jobs are:
What states have the most Senior Generative Ai Engineer jobs? States with the most job openings for Senior Generative Ai Engineer jobs include:
What job categories do people searching Senior Generative Ai Engineer jobs look for? The top searched job categories for Senior Generative Ai Engineer jobs are:
Senior Generative Ai Engineer jobs near you
Infographic showing various Senior Generative Ai Engineer job openings in the United States as of May 2026, with employment types broken down into 90% Full Time, 4% Part Time, and 6% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution, with an average salary of $126,557 per year, or $60.8 per hour.

Senior Generative AI Engineer

SBT Global, Inc.

Ridgefield Park, NJ • On-site

$10.95K/mo

Full-time

Posted 21 days ago

Job description

Company Description
On-Site
1yr contract
$10950/month
Job Description
About the Role
We are seeking a Senior Generative AI Engineer to design, build, and deploy production-grade AI applications powered by large language models (LLMs). In this role, you will lead the end-to-end development of Generative AI solutions, including LLM-powered applications, retrieval-augmented generation (RAG) systems, agentic workflows, model evaluation pipelines, and production infrastructure.
You will work cross-functionally with product, finance, data, and business stakeholders to translate real-world business problems into scalable AI systems that deliver measurable value.
Job Description:
  • Design and develop algorithms for generative models using deep learning techniques
  • Design and build LLM-powered applications for internal and/or customer-facing use cases
  • Develop and productionize RAG pipelines using enterprise data sources, vector databases, and retrieval systems
  • Build and optimize AI agents / agentic workflows for task automation, reasoning, and orchestration
  • Integrate model providers such as OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, and open-source models where appropriate
  • Create robust evaluation frameworks for response quality, factuality, latency, safety, and reliability
  • Implement prompt engineering, structured outputs, tool calling, and model optimization strategies
  • Deploy scalable AI services to cloud environments using modern software engineering and MLOps practices
  • Build monitoring, observability, and feedback loops for model and application performance in production
  • Establish and maintain guardrails, responsible AI practices, and security controls for enterprise AI systems
  • Collaborate with product managers, designers, and business stakeholders to identify high-impact AI opportunities
  • Mentor other engineers and contribute to architecture, technical direction, and engineering best practices

Qualifications
Required Qualifications
  • Bachelor's degree in Computer Science, Engineering, Machine Learning, or a related field
  • 5+ years of software engineering, machine/deep learning engineering, or applied AI experience
  • 2+ years of hands-on experience building and deploying Generative AI / LLM-based systems in production
  • Strong programming skills in Python and experience with backend/API development
  • Experience with LLM application development, including prompt engineering, RAG, tool use, and structured output design
  • Experience in optimizing RAG pipelines using both structured and unstructured data
  • Experience with orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent
  • Experience in generative AI techniques such as GANs, and VAEs
  • Hands-on experience with vector databases / retrieval systems such as Pinecone, Weaviate, Chroma, FAISS, Elasticsearch, or Azure AI Search
  • Experience with cloud platforms such as AWS, GCP, or Azure
  • Experience with Docker, Kubernetes, CI/CD, and production deployment practices
  • Strong understanding of software architecture, scalability, reliability, and distributed systems
  • Experience building evaluation, testing, and monitoring for AI systems
  • Strong communication skills and ability to work closely with technical and non-technical stakeholder

Preferred Qualifications
  • Experience fine-tuning or adapting open-source LLMs
  • Advanced knowledge of natural language processing for text generation tasks
  • Experience with PyTorch, TensorFlow, JAX, or related ML frameworks
  • Experience with MLOps tools such as MLflow, SageMaker, Vertex AI, Azure ML, Kubeflow, or similar
  • Experience building multi-agent systems or advanced orchestration workflows
  • Experience with AI safety, guardrails, red-teaming, privacy, and governance
  • Familiarity with search, ranking, recommendation, conversational AI, or enterprise knowledge systems
  • Experience in customer-facing or enterprise SaaS products
  • Experience in semiconductor/manufacturing, retail and e-commerce sectors

Additional Information
All your information will be kept confidential according to EEO guidelines.

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