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Assistant Generative Ai Sales Jobs (NOW HIRING)

Hp

Senior ServiceNow Development Manager

Spring, TX · Remote

$48 - $66/hr

Lead the evaluation, deployment, and scaling of ServiceNow AI capabilities, including Now Assist, generative AI, AI agents, predictive intelligence, virtual agent, and intelligent workflow automation.

New

Arize AI

AI Sales Engineer, US

$140K - $210K/yr

As generative AI reshapes industries, teams need powerful ways to monitor, troubleshoot, and ... We are looking for an AI Sales Engineer (Solutions Architect) to join the good fight and get this ...

Uncountable

Platform Engineer - Generative AI

New York, NY · On-site

$120K - $160K/yr

... assistants, and more. This is a unique opportunity to join the front-line effort to accelerate ... Strong interest in Generative AI * Solid computer science and software engineering fundamentals ...

Nvidia

Solutions Architect, Generative AI

Santa Clara, CA · On-site

$74 - $97.50/hr

Serve as the primary technical domain expert for pre- and post-sale for partners, embedding deeply with them to design and deploy Generative AI solutions at scale. Maintain strong relationships with ...

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How much do assistant generative ai sales jobs pay per hour?

As of Jun 27, 2026, the average hourly pay for assistant generative ai sales in the United States is $21.20, according to ZipRecruiter salary data. Most workers in this role earn between $18.03 and $23.56 per hour, depending on experience, location, and employer.
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Assistant Generative Ai Sales jobs near you

Generative AI Engineer

Prophecy Technologies

Richardson, TX • On-site

Full-time

Posted 18 days ago

Job description

Job Summary
The Generative AI Architect will design, build, and deploy scalable Generative AI solutions leveraging large language models (LLMs), diffusion models, and advanced ML frameworks. This role focuses on architecting secure, high-performance AI platforms on cloud environments and integrating GenAI capabilities into enterprise business workflows.
Experience
  • 8+ years of overall experience in software, data, or machine learning engineering
  • 5+ years of hands-on experience in Machine Learning / AI
  • Strong recent experience in Generative AI and LLM-based solutions

Key Responsibilities
  • Design scalable, modular, and secure Generative AI architectures on AWS, Azure, and GCP
  • Implement data pipelines for training, fine-tuning, and serving large-scale AI models
  • Lead model fine-tuning efforts using custom datasets for domain-specific use cases
  • Develop and optimize prompt engineering strategies for enterprise applications
  • Integrate Generative AI models with APIs, microservices, UIs, and business workflows
  • Optimize inference pipelines for low latency, high throughput, and cost efficiency
  • Implement model versioning, monitoring, rollback, and governance strategies
  • Establish and enforce MLOps best practices, including CI/CD and automated deployments
  • Collaborate with Data Scientists, MLOps Engineers, Product Managers, and business stakeholders
  • Provide technical leadership, conduct code reviews, and promote GenAI best practices
  • Ensure compliance with data privacy, AI ethics, and regulatory standards

Required Skills & Experience
  • Strong experience designing and implementing Generative AI solutions (LLMs, diffusion models)
  • Hands-on expertise in model fine-tuning and prompt engineering
  • Deep knowledge of ML frameworks:
  • TensorFlow
  • PyTorch
  • Hugging Face Transformers
  • OpenAI APIs
  • Strong experience deploying AI solutions on AWS, Azure, and GCP
  • Solid understanding of MLOps, including CI/CD, model versioning, and automation
  • Proficiency in Python programming and scripting
  • Experience with APIs and microservices architectures
  • Experience with vector databases such as Pinecone, Weaviate, or Qdrant
  • Familiarity with GenAI orchestration frameworks (LangChain, LlamaIndex, etc.)
  • Knowledge of distributed training, hyperparameter tuning, and real-time inference systems
  • Strong background in data engineering for large-scale training datasets
  • Understanding of AI ethics, data privacy, and regulatory compliance

Competencies
  • Digital: Generative AI / Large Language Models (LLMs)
  • Digital: Machine Learning & MLOps
  • Digital: Cloud Platforms (AWS, Azure, GCP)
  • Digital: Python & AI Frameworks

Preferred Skills
  • Experience integrating chatbots, virtual assistants, and content automation solutions
  • Exposure to knowledge graphs, embeddings, and semantic search
  • Experience with low-latency inference and real-time serving
  • Contributions to open-source, research publications, or GenAI community

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