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Entry Level Generative Ai Engineer Jobs (NOW HIRING)

Onsite About the Role We are seeking a highly skilled AWS AI Engineer with strong hands-on experience in Kubernetes, EKS, and Generative AI systems. The ideal candidate will have deep expertise in ...

Role: Agentic AI/AI Engineer - Generative AI & Machine Learning Location:โ€ฏ Schaumburg, IL (Hybrid - 3 Days Onsite per Week) Long Term Contract Job Summary: We are seeking a highly motivated and ...

AI Engineer Intern - AI Center of Excellence (CoE) Location: Plano, Texas, USA Internship Duration ... This role offers hands-on experience building enterprise-grade Generative AI solutions across ...

AI Engineer

San Francisco, CA ยท On-site +1

$100K - $300K/yr

Join to apply for the AI Engineer role at Chima 1 year ago Be among the first 25 applicants Join to ... Build high-quality generative AI features and ship quickly. * Experiment and improve our AI ...

AI Engineer

Irving, TX ยท On-site

We are seeking a talented AI Engineer with hands-on experience building Generative AI applications and intelligent agent systems. The ideal candidate will have practical expertise working with Large ...

We are seeking a Generative AI (GenAI) Design Engineer to join our team and drive innovation in AI-powered solutions. This role involves designing, developing, and optimizing generative AI models and ...

SR GEN AI Engineer

Manhattan, NY ยท On-site

$87/hr

US-Citizen, H-1B, OPT-EAD, GC-EAD We are looking for a skilled Generative AI Engineer with strong Python expertise to design, develop, and deploy AI-driven solutions. The ideal candidate will have ...

The Role Capco is seeking a Generative AI Engineer to help design, develop, and deploy intelligent applications powered by Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and ...

Title: AI Engineer/Developer Location: Austin, TX (Hybrid) Duration: 6 months (possibility of ... vision, generative AI/LLMs, recommendation systems) * Build and maintain data pipelines for ...

New

Generative AI Data Engineer III

Atlanta, GA ยท On-site

$110K - $132K/yr

Share this job: Share: Share Generative AI Data Engineer III with Facebook Share Generative AI Data Engineer III with LinkedIn Share Generative AI Data Engineer III with Twitter Caution against ...

Job Summary : Perfict is seeking a Junior AI Engineer with strong Python skills and a solid understanding of Machine Learning, NLP, Generative AI, and Large Language Models (LLMs). The ideal ...

Role: Generative AI/ML Engineer Duration 6 Months Location: NYC, NY Position Overview: The Gen AI Specialist will leverage advanced Generative AI models and Azure OpenAI services to develop ...

We are hiring an AI Engineer specializing in LLMs (Large Language Models), Retrieval Augmented ... Develop Generative AI solutions, including chatbots, summarization, and content creation tools.

Generative AI: Practical experience with LLMs, prompt engineering, and/or RAG-based architectures. * Backend Development: Experience building APIs using FastAPI, Flask, or Node.js (TypeScript)

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Entry Level Generative Ai Engineer information

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$30K

$69.4K

$118K

How much do entry level generative ai engineer jobs pay per year?

As of Jul 11, 2026, the average yearly pay for entry level generative ai engineer in the United States is $69,362.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,500.00 and $78,500.00 per year, depending on experience, location, and employer.

What are common challenges faced by entry level Generative AI Engineers, and how can they be addressed?

Entry level Generative AI Engineers often encounter challenges such as mastering complex machine learning frameworks, understanding the nuances of training large models, and keeping up with rapidly evolving research. Collaborating closely with more experienced team members through code reviews and pair programming can accelerate learning. It's also helpful to engage in continuous education through online courses and participate in team discussions to stay updated on the latest advancements and best practices in the field.

What is the difference between Entry Level Generative Ai Engineer vs Data Scientist?

AspectEntry Level Generative Ai EngineerData Scientist
Required CredentialsBachelor's in CS, AI, or related field; basic knowledge of machine learning and programmingBachelor's or higher in CS, Statistics, or related; knowledge of data analysis and modeling
Work EnvironmentTech companies, AI startups, research labs focusing on AI model developmentVarious industries including finance, healthcare, marketing; analyzing data to inform decisions
Employer & Industry UsagePrimarily in AI and tech sectors developing generative modelsAcross multiple sectors using data to solve business problems

While both roles require a background in data and programming, Entry Level Generative Ai Engineers focus on developing AI models like generative adversarial networks, whereas Data Scientists analyze data to generate insights. The former is more specialized in AI model creation, while the latter covers broader data analysis tasks.

What are entry level generative AI engineers?

Entry level generative AI engineers are professionals who work with artificial intelligence technologies focused on creating new content such as images, text, audio, or code. They typically assist in developing, training, and fine-tuning machine learning models like GPT or GANs under the supervision of senior engineers. These roles usually require a strong foundation in programming, mathematics, and machine learning concepts, but may not demand extensive industry experience. Tasks often include data preprocessing, model evaluation, and contributing to research or product development involving generative AI.

What are the key skills and qualifications needed to thrive as an Entry Level Generative AI Engineer, and why are they important?

To thrive as an Entry Level Generative AI Engineer, you need a solid background in computer science, mathematics, and machine learning fundamentals, typically supported by a relevant degree or coursework. Familiarity with Python, deep learning frameworks like TensorFlow or PyTorch, and version control systems such as Git is important, along with any foundational certifications in AI or data science. Strong problem-solving ability, curiosity, and effective teamwork skills will help you stand out in this collaborative and innovative field. These skills and qualities are crucial for developing, testing, and improving generative AI models in a rapidly evolving technical landscape.
More about Entry Level Generative Ai Engineer jobs
What cities are hiring for Entry Level Generative Ai Engineer jobs? Cities with the most Entry Level 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 Entry Level Generative Ai Engineer jobs? States with the most job openings for Entry Level Generative Ai Engineer jobs include:
AWS AI Engineer

AWS AI Engineer

Merican

Herndon, VA โ€ข On-site

Full-time

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Role: AWS AI Engineer
Location: Herndon, VA
Work Mode: Onsite
About the Role
We are seeking a highly skilled AWS AI Engineer with strong hands-on experience in Kubernetes, EKS, and Generative AI systems. The ideal candidate will have deep expertise in deploying, scaling, and maintaining AI/ML workloads in production environments, along with experience in modern AI frameworks and platform engineering.
Certification Requirements (At least one required)
  • Active AWS Solutions Architect Certification
  • AWS Certified AI Foundations or AWS Certified AI Professional
  • Certified Kubernetes Administrator (CKA) - Active certification
Key Responsibilities
  • Deploy, manage, and troubleshoot Kubernetes clusters, including disconnected installations
  • Design, deploy, and upgrade Amazon EKS clusters in production environments
  • Perform advanced troubleshooting for EKS and Kubernetes-based systems
  • Implement and manage LLMOps workflows, including deployment, monitoring, and scaling of Generative AI systems
  • Build and maintain agent-based workflows using frameworks like LangChain, CrewAI, or AutoGen
  • Manage and optimize vector databases (e.g., Pinecone, Weaviate, Milvus)
  • Design and optimize Retrieval-Augmented Generation (RAG) pipelines for performance and scalability
  • Implement AI governance frameworks, including security guardrails and cost optimization strategies
  • Build and support Internal Developer Platforms (IDP) for AI use cases
Must-Have Skills
  • Strong Kubernetes expertise (installation, administration, troubleshooting)
  • Extensive hands-on experience with Amazon EKS (deployment, upgrades, troubleshooting)
  • Proven experience with LLMOps and production-grade Generative AI systems
  • Experience with agentic AI frameworks (LangChain, CrewAI, AutoGen)
  • Hands-on experience with vector databases and RAG architectures
  • Knowledge of AI governance, security guardrails (e.g., NeMo Guardrails), and cost control for LLMs
  • Experience building AI-focused Internal Developer Platforms

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About Merican

Sourced by ZipRecruiter

Merican is a IT Service consulting firm, specialized in Digital adoption and Business automation. With our diverse collection of skilled and committed consultants, technology companies, businesses and digital experts, we provide our subject expertise and our unique client service approach, a best-in-class global model of delivery suited to the business demands of our clients. We ensure that we implement future-oriented solutions for our clients via investments in people, solutions, technologies, competencies and infrastructure.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Columbia , MD, US

Year founded

2020

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