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Genai Engineer Jobs (NOW HIRING)

... engineering, and context management. • Experience integrating GenAI with Azure OpenAI, AWS Bedrock, Vertex AI, OpenAI, Anthropic, and Gemini, along with enterprise APIs, middleware, and data ...

Self-motivated individual with a passion for solving hard problems using AI/GenAI. Must have ... Programming Skills: Expertise in Python and tools like Hugging Face, Langchain, and OpenAI API.

... engineering, and context management. • Experience integrating GenAI with Azure OpenAI, AWS Bedrock, Vertex AI, OpenAI, Anthropic, and Gemini, along with enterprise APIs, middleware, and data ...

Trinity Industries is searching for an GenAI Engineer to join our Service Analytics organization, supporting rail optimization and shipper decisioning solutions. In this role, you will use Claude and ...

Role: GenAI Engineer AWS Bedrock Location: Plano, TX-Hybrid Type: 12+Months Required Skills * 8+ years of software development experience. * 3+ years of hands-on experience in Generative AI/LLM ...

WI · On-site

$110 - $160/hr

... engineering, and context management. * Experience integrating GenAI with Azure OpenAI, AWS Bedrock, Vertex AI, OpenAI, Anthropic, and Gemini, along with enterprise APIs, middleware, and data ...

GenAI Engineer

Charlotte, NC · On-site

$90 - $150/hr

... engineering, and context management. Experience integrating GenAI with Azure OpenAI, AWS Bedrock, Vertex AI, OpenAI, Anthropic, and Gemini, along with enterprise APIs, middleware, and data platforms.

Ltd. is seeking a GenAI Engineer to join their Apple Content Solutions Team, focusing on a project centered around Generative AI. The role requires a strong foundation in Java and Python, as well as ...

... engineering, and context management. • Experience integrating GenAI with Azure OpenAI, AWS Bedrock, Vertex AI, OpenAI, Anthropic, and Gemini, along with enterprise APIs, middleware, and data ...

... engineering, and context management. • Experience integrating GenAI with Azure OpenAI, AWS Bedrock, Vertex AI, OpenAI, Anthropic, and Gemini, along with enterprise APIs, middleware, and data ...

... engineering, and context management. • Experience integrating GenAI with Azure OpenAI, AWS Bedrock, Vertex AI, OpenAI, Anthropic, and Gemini, along with enterprise APIs, middleware, and data ...

... engineering, and context management. • Experience integrating GenAI with Azure OpenAI, AWS Bedrock, Vertex AI, OpenAI, Anthropic, and Gemini, along with enterprise APIs, middleware, and data ...

... engineering, and context management. • Experience integrating GenAI with Azure OpenAI, AWS Bedrock, Vertex AI, OpenAI, Anthropic, and Gemini, along with enterprise APIs, middleware, and data ...

... GenAI models and services into existing applications using APIs Education: · Bachelor's Degree in Computer Science, Mathematics, Engineering or a related field. · Masters or Doctorate degree may ...

NY · On-site

$120 - $180/hr

Strong proficiency in programming languages such as Python, Java, Spring, Maven, JSON. Object ... Understanding of AI observability, performance monitoring, and ethical guidelines in GenAI systems.

Showing results 21-40

Genai Engineer information

What is a GenAI engineer?

A GenAI Engineer is a professional who specializes in designing, developing, and deploying generative artificial intelligence (AI) models and applications. This role involves working with advanced machine learning techniques, such as large language models and generative adversarial networks, to create systems that can generate text, images, code, or other content. GenAI Engineers collaborate with data scientists, software engineers, and product teams to integrate AI capabilities into products and services, ensuring ethical use and scalability. They also stay updated on the latest developments in AI research to continually improve model performance and effectiveness.

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

To thrive as a GenAI Engineer, you need expertise in machine learning, deep learning, and programming languages such as Python, along with a solid understanding of generative models like GANs and transformers. Familiarity with frameworks such as TensorFlow or PyTorch, and experience with cloud platforms and MLOps tools, are highly valuable; advanced degrees or certifications in AI or data science are often preferred. Strong problem-solving, creativity, and communication skills help GenAI Engineers design innovative solutions and effectively collaborate with multidisciplinary teams. These skills ensure the development of robust, scalable generative AI systems that address complex real-world challenges.

What are some typical challenges a GenAI engineer faces when deploying AI models in production environments?

GenAI Engineers often encounter challenges such as ensuring model scalability, addressing bias in generated outputs, and maintaining performance consistency in real-world applications. Deploying generative AI models requires careful monitoring to prevent unexpected or inappropriate outputs, as well as efficient resource management to handle large-scale computations. Collaborating closely with data engineers, product managers, and ML operations teams is essential to streamline deployment pipelines and quickly resolve issues that arise in live environments.

What is the difference between Genai Engineer vs Data Scientist?

AspectGenai EngineerData Scientist
Required CredentialsDegree in Computer Science, AI, or related fields; experience with AI/ML frameworksDegree in Data Science, Statistics, or related fields; strong programming skills
Work EnvironmentDevelops AI models, fine-tunes generative AI systems, collaborates with AI teamsAnalyzes data, builds predictive models, interprets complex datasets
Employer & Industry UsageTech companies, AI startups, research labs focusing on generative AIFinance, healthcare, marketing, and tech firms analyzing data for insights

While both roles require strong technical skills and a background in data or AI, Genai Engineers focus on developing and deploying generative AI models, whereas Data Scientists analyze data to extract insights and build predictive models. The roles often overlap but serve different primary functions within AI and data-driven organizations.

More about Genai Engineer jobs

What cities are hiring for Genai Engineer jobs?

Cities with the most Genai Engineer job openings:

What states have the most Genai Engineer jobs?

States with the most job openings for Genai Engineer jobs include:

Infographic showing various Genai Engineer job openings in the United States as of August 2026, with employment types broken down into 93% Full Time, 3% Part Time, and 4% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution.

GenAI Engineer (Agentic AI)

Anagha Techno Soft

Manhattan, NY • On-site

Other

Posted 4 days ago


Job description

We are looking for a hands-on GenAI Engineer to build and scale agent-based AI applications, with a strong focus on Claude Agent SDK (Anthropic). 
 
The role centers on developing intelligent, production-grade workflows for document processing, onboarding, and operational automation, integrating GenAI capabilities into enterprise platforms. 

 
Key Responsibilities 
 

  • Build agent-driven applications using Claude Agent SDK and similar frameworks 
  • Design and implement agentic workflows (multi-step reasoning, tool use, orchestration) 
  • Integrate GenAI solutions into enterprise systems 
  • Develop and refine prompts and evaluation approaches 
  • Ensure solutions are production-ready, reliable, and auditable 

 
Requirements 
 

  • Strong hands-on experience with Claude (Anthropic) and agentic / autonomous workflows 
  • Strong programming skills in Python 
  • Experience with LLM APIs/frameworks (OpenAI or similar as secondary) 
  • Proven experience building end-to-end GenAI applications for production use 
  • Solid understanding of prompt engineering and model behavior 

 
Nice to Have 
 

  • Experience in financial services or onboarding domains 
  • Exposure to enterprise-scale AI deployments (regulated environments, audit requirements) 
  • Familiarity with cloud platforms (Azure, AWS) for AI deployments 
  • Experience working in cross-functional teams (Ops + Tech + Compliance)