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Genai Engineer Jobs (NOW HIRING)

Accenture LLP

Cleared GenAI Engineer

Washington, DC · On-site

G, Prompt Engineering Expertise, Large Language Model Expertise (Selection, fine tuning, and deployment) and GenAI Use Case evaluation. You will collaborate with a community of GenAI leaders ...

Danaher

Senior Staff GenAI Engineer

Sunnyvale, CA

$200K - $235K/yr

The Senior Staff GenAI Engineer leads the design, development, and deployment of scalable, reliable generative AI systems, driving agentic automation and integration to deliver highimpact ...

Danaher

Senior Staff GenAI Engineer

Sunnyvale, CA · On-site

$200K - $235K/yr

The Senior Staff GenAI Engineer leads the design, development, and deployment of scalable, reliable generative AI systems, driving agentic automation and integration to deliver high-impact ...

Precision Technologies Corp

Sr. Data/GenAI Engineer

Irving, TX · On-site

$101K - $138K/yr

Role : Sr. Data/GenAI Engineer Location : Irving, TX (Hybrid) Contract * Project Mission : To lead the design and execution of the data ingestion and preparation pipeline, which forms the knowledge ...

Vkore Solutions

GenAI Engineer-W2

Austin, TX · On-site

We are looking for a GenAI Ops Engineer to train, fine-tune, and deploy Generative AI models (LLMs, Diffusion Models, Transformers, etc.). You will optimize model performance, manage training ...

State Farm

Lead GenAI Engineer (LLM)

Bloomington, IL · On-site

$97K - $128K/yr

Design & Deploy AI/GenAI Solutions - Architect and implement LLM-powered applications, agentic ... Engineer Data & Analytics Pipelines - Build pipelines that feed AI/ML systems with clean, governed ...

Quest Global

GenAI engineer

Houston, TX · On-site

$100K - $120K/yr

Quest Global delivers world-class end-to-end engineering solutions by leveraging our deep industry knowledge and digital expertise. By bringing together technologies and industries, alongside the ...

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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.

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Genai Engineer jobs near you
Infographic showing various Genai Engineer job openings in the United States as of August 2026, with employment types broken down into 94% Full Time, 2% Part Time, and 4% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution.

Cleared GenAI Engineer

Accenture Federal Services

Washington, DC • On-site

Full-time

Re-posted 28 days ago

Accenture Federal Services rating

8.7

Company rating: 8.7 out of 10

Based on 20 frontline employees who took The Breakroom Quiz

47th of 492 rated business services

Job description

Job Summary:
Accenture Federal Services is dedicated to helping the US federal government improve national security and public safety. They are seeking a Cleared GenAI Engineer to develop generative AI models and solutions that address mission-critical problems for clients, collaborating with a diverse team of experts in AI and software engineering.
Responsibilities:
• Design and build GenAI use cases based on client's needs and specific data
• Understanding of Agentic AI frameworks and design and when they are appropriate for use
• Develop and deploy generative AI models using platforms such as Amazon Kendra, Google Vertex AI, and AWS Bedrock.
• Implement large language models (LLMs) and transformer models to create advanced AI applications.
• Integrate solutions with cloud-based AI services such as Google Cloud Document AI, Google Cloud Gemini, Google Cloud Gemma, and Google Cloud Generative AI Language Models.
• Utilize NVIDIA AI Foundations and OpenAI ChatGPT to develop and refine AI applications.
• Leverage Databricks LLM and Databricks Mosaic AI for data analysis and AI model development.
• Show your curiosity, motivation, and passion for experimentation and continuous learning to drive AI innovation that is applicable across enterprise client domains.
Qualifications:
Required:
• Experience working with modern generative AI capabilities including large language models, transformer models, and retrieval-augmented generation
• Expertise in AI platforms (e.g., Amazon Kendra, Google Vertex AI, AWS Bedrock, and Azure AI, etc.)
• Experience with Google Cloud services (e.g., Document AI, Gemini, Gemma, Generative AI Language Models)
• Experience building RAG systems with vector databases (e.g., Pinecone, Weaviate, ChromaDB, FAISS)
• Experience using modern software languages (e.g., Python, SQL, Go) to develop generative AI solutions
• Active Top Secret or TS/SCI or TS/SCI with polygraph clearance
Preferred:
• Strong understanding of AI ethics, responsible AI, and generative AI data ethics
• Experience in LLM fine-tuning and LLMOps
• Ability to author and validate prompts for AI models
• Familiarity with NVIDIA AI Foundations and OpenAI ChatGPT
• Experience with AI-assisted development platforms (e.g., Cursor, Windsurf, Claude, etc.)
• Experience implementing tool-using AI agents to assist in API integration - enabling agent access to external data sources and web services
• Experience using deployment/virtualization tools in containerized environments (e.g., VMware, Docker, Kubernetes)
• Proficiency in scripting with Linux Bash, PowerShell, or equivalent automation tools
Company:
Accenture Federal Services is a leading US federal services company and subsidiary of Accenture. Founded in 1989, the company is headquartered in Arlington, USA, with a team of 10001+ employees. The company is currently Late Stage.

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