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Video Prompt Engineer Jobs in Raleigh, NC (NOW HIRING)

... prompt engineering, and context management. • Experience integrating GenAI with Azure OpenAI, AWS ... or video generation. • Familiarity with DevOps and IaC tooling (GitHub Actions, Jenkins ...

Frontend Developer - Angular

Durham, NC

$94.20K - $109.60K/yr

For a brief 1 minute video about us, you can check Front End Engineer - Angular Developer | Dallas ... Effectively prompt and refine LLM outputs for coding tasks, debugging, refactoring, and improving ...

New

Network Services Lead

Morrisville, NC · On-site

$94.90K - $131K/yr

... and prompt and efficient service desk support. The Network Services Lead is responsible for ... Unified Communications and Video Teleconferencing : * Support the configuration and provisioning of ...

Network Services Lead

Morrisville, NC · On-site

$94.90K - $131K/yr

... and prompt and efficient service desk support. The Network Services Lead is responsible for ... Unified Communications and Video Teleconferencing : * Support the configuration and provisioning of ...

Content Strategy, Systems, and Workflow Engineering * Lead and evolve the company's content ... Build and maintain content templates, prompt libraries, and structured workflows for campaigns ...

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Video Prompt Engineer information

See Raleigh, NC salary details

$29.6K

$85.8K

$135.6K

How much do video prompt engineer jobs pay per year?

As of Jun 3, 2026, the average yearly pay for video prompt engineer in Raleigh, NC is $85,838.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,200.00 and $105,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Video Prompt Engineer, and why are they important?

To thrive as a Video Prompt Engineer, you need expertise in video production, scripting, and an understanding of AI prompt engineering, often supported by experience with media editing tools and a background in computer science or related fields. Familiarity with platforms like Adobe Premiere, After Effects, and generative AI systems such as OpenAI, Runway, or Synthesia is typically required. Strong creativity, attention to detail, and effective communication skills help in crafting prompts that yield high-quality, contextually relevant video outputs. These abilities are crucial for bridging the gap between technical AI capabilities and compelling visual storytelling, ensuring that generated video content meets project objectives.

What are some typical challenges Video Prompt Engineers face when collaborating with creative teams?

Video Prompt Engineers often work closely with creative teams to develop prompts that yield visually engaging and contextually accurate video outputs from generative AI models. One common challenge is translating creative concepts into precise, technical prompts that the AI can interpret effectively. Balancing the creative vision with the technical constraints of the model requires strong communication and iterative problem-solving. Additionally, staying updated on the latest advancements in generative video technology is essential to ensure the prompts leverage new capabilities while maintaining high-quality results.

What is a Video Prompt Engineer?

A Video Prompt Engineer is a professional who designs and optimizes prompts to guide artificial intelligence (AI) systems in generating or editing video content. They work closely with AI models to fine-tune instructions, ensuring the resulting videos meet specific creative, technical, or business goals. Their responsibilities often include scripting effective prompts, testing AI outputs, and collaborating with developers and creatives to enhance video quality and relevance. As AI video tools become more advanced, the role of a Video Prompt Engineer is becoming increasingly important in industries like advertising, entertainment, and digital content creation.

What is the difference between Video Prompt Engineer vs AI Content Creator?

AspectVideo Prompt EngineerAI Content Creator
Required CredentialsKnowledge of AI models, prompt engineering, multimedia toolsCreativity, familiarity with AI tools, content development
Work EnvironmentTech companies, media agencies, AI startupsDigital media, marketing firms, content platforms
Industry UsageAI-driven video production, multimedia projectsSocial media, advertising, online content
Search & Comparison IntentUnderstanding roles in AI video creationCreating AI-generated content for digital platforms

The main difference is that a Video Prompt Engineer specializes in designing prompts for AI models to generate videos, focusing on technical prompt optimization. An AI Content Creator develops digital content using AI tools, often across various media types. While both roles involve AI and creativity, the Video Prompt Engineer is more technical and focused on video-specific prompts, whereas the AI Content Creator emphasizes content production and storytelling across platforms.

What are popular job titles related to Video Prompt Engineer jobs in Raleigh, NC? For Video Prompt Engineer jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Video Prompt Engineer jobs in Raleigh, NC look for? The top searched job categories for Video Prompt Engineer jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Video Prompt Engineer jobs? Cities near Raleigh, NC with the most Video Prompt Engineer job openings:
Gen AI Solution Engineer

Gen AI Solution Engineer

Infosys

Raleigh, NC • On-site

Full-time

Posted 8 days ago


Infosys rating

7.6

Company rating: 7.6 out of 10

Based on 57 frontline employees who took The Breakroom Quiz

90th of 203 rated it services


Job description

Job Summary:
Infosys is a global leader in next-generation digital services and consulting. They are seeking a Gen AI Solution Engineer to work with cutting-edge technologies in generative AI, focusing on building and deploying scalable analytics solutions to drive business insights and innovation.
Responsibilities:
• Review data preparation tasks, and plans to address patterns or anomalies, while ensuring data readiness for advanced modeling and AI.
• Review models for complex use cases (e.g., forecasting models, LLM-based solutions), and refine algorithms to meet business needs.
• Review plan for smooth deployment into scalable, production-ready solutions.
• Review test plans and test results for analytics use cases, while defining optimization standards for model accuracy and stability, in alignment with business goals.
• Build models and analytics solutions tailored to business needs.
• Ensure quality and scalability across client engagements while actively contributing to knowledge assets and innovation streams.
• Leverage tools like SAS and R/Python to create reusable customizations for non-ML, ML, and deep learning algorithms, while enhancing analytics including LLMs, and create innovative, cost-effective solutions.
• Review and refine analytics problems; identify data sources and extract from diverse environments.
• Oversee analysis execution and drive business insights.
• Create monitoring strategies across multiple projects, embedding governance frameworks to ensure robustness, reliability, and risk awareness.
• Review monitoring frameworks, refine documentation/reporting templates, and present insights on anomalies or slippages to stakeholders.
• Refine documentation strategy across teams, ensuring transparency and reproducibility of complex analytics solutions.
• Collaborate with cross-functional teams, ensuring alignment between analytics delivery and business strategy.
• Review analytics outputs for adherence to quality frameworks and project commitments.
• Recommend improvements to quality metrics and guide team members to align with standards.
• Identify and recommend model changes needed for successful deployment.
• Engage in creation and refinement of IP assets such as analytics prototypes and accelerators.
• Develop insights, whitepapers, and proof-of-concept summaries that highlight innovative thinking.
• Review innovative models and applications in non-ML, ML, deep learning, or LLM areas.
• Support participation in forums and internal knowledge exchanges.
• Deliver training sessions on technical and analytics-specific topics.
• Collaborate on content creation and mentor team members through hands-on guidance in live projects.
• Provide input for segment and unit-level business plans.
Qualifications:
Required:
• Enterprise GenAI and Agentic AI solutions across RAG, AI agents, conversational AI, enterprise search, workflow automation, document intelligence, and AI copilots; comfortable with planner-executor, reflection, multi-agent, and graph-based orchestration patterns.
• Hands-on with orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI) and vector databases (Pinecone, Weaviate, Milvus, pgvector, FAISS, ChromaDB, Azure AI Search); working knowledge of grounding, prompt 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.
• Command of AI governance, LLMOps, evaluation, observability, guardrails, model safety, compliance, and cloud-native deployment.
• Ability to define reference architectures, lead solutioning discussions, drive architecture reviews, and collaborate with enterprise architects, business stakeholders, and engineering teams.
• Bachelor’s degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
• This position may require relocation and/or travel to work/project location.
• Candidates authorized to work for any employer in the United States without employer-based visa sponsorship are welcome to apply. Infosys is unable to provide immigration sponsorship for this role now or in the future.
Preferred:
• Exposure to open-source LLM ecosystems — Hugging Face, PyTorch, LoRA, QLoRA, PEFT — and models such as Llama, Mistral, Gemma, DeepSeek, and Falcon.
• Familiarity with multimodal AI, including vision-language models, speech and audio models, and image or video generation.
• Familiarity with DevOps and IaC tooling (GitHub Actions, Jenkins, Terraform, Helm, Kubernetes) and awareness of front-end stacks (React, Angular, TypeScript, GraphQL) used in copilot interfaces.
Company:
Infosys is a technology company that offers consulting, outsourcing, cloud infrastructure, program management, and software services. Founded in 1981, the company is headquartered in Bangalore, IND, with a team of 10001+ employees. The company is currently Late Stage.

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