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Home Based Prompt Engineering Jobs in Arizona (NOW HIRING)

Build and implement agent-based workflows including multi-step execution, tool integrations, and AI ... Understanding of AI governance, prompt engineering, and AI evaluation frameworks.

Build and implement agent-based workflows including multi-step execution, tool integrations, and AI ... Understanding of AI governance, prompt engineering, and AI evaluation frameworks.

Principal Agentic Software Engineer

Scottsdale, AZ · On-site

$136K - $182K/yr

Hands-on depth with the Model Context Protocol, prompt engineering for code, and AI building blocks such as Azure AI Foundry, RAG, LangChain, or graph-based data technologies like GraphRAG and ...

Principal Agentic Software Engineer

Scottsdale, AZ · On-site

$136K - $182K/yr

Hands-on depth with the Model Context Protocol, prompt engineering for code, and AI building blocks such as Azure AI Foundry, RAG, LangChain, or graph-based data technologies like GraphRAG and ...

Showing results 41-60

Home Based Prompt Engineering information

What is the difference between Home Based Prompt Engineering vs Remote AI Content Specialist?

AspectHome Based Prompt EngineeringRemote AI Content Specialist
Required CredentialsBasic understanding of AI prompts, no formal certification neededExperience in content creation, possibly some AI tool familiarity
Work EnvironmentHome-based, flexible hoursHome-based, project or task-based
Industry UsageAI development, chatbot training, prompt optimizationContent marketing, social media, digital content creation
Common Search IntentJobs involving AI prompt design from homeRemote content creation roles involving AI tools

Home Based Prompt Engineering focuses on designing and refining prompts for AI models, often requiring technical understanding of AI systems. In contrast, Remote AI Content Specialists create digital content using AI tools, emphasizing content skills. Both roles are home-based and industry-related but differ in technical depth and primary tasks.

Are home based prompt engineers still in demand?

Home-based prompt engineering is an emerging field within AI and natural language processing, with demand increasing as organizations seek expertise in designing effective prompts for AI models. Skills in AI tools, machine learning, and strong communication are valuable, and remote work opportunities are growing in this area. However, the field is still developing, and demand may vary based on industry adoption and technological advancements.
What are the most commonly searched types of Prompt Engineering jobs in Arizona? The most popular types of Prompt Engineering jobs in Arizona are:
What are popular job titles related to Home Based Prompt Engineering jobs in Arizona? For Home Based Prompt Engineering jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Home Based Prompt Engineering jobs in Arizona look for? The top searched job categories for Home Based Prompt Engineering jobs in Arizona are:

AI Dev (Features + CHQ)_Tempe,AZ

Photon

Anthem, AZ • On-site

Full-time

Re-posted 11 days ago


Job description

Summary 

Photon is seeking a skilled AI Developer (Platform + Backend) to support the design, development, and implementation of AI-powered employee support platform. 

The enterprise AI platform built to streamline support for frontline and HQ teams through intelligent automation, workflow orchestration, and AI-driven resolution experiences. The platform combines Generative AI, enterprise integrations, backend services, and workflow automation to improve operational efficiency and employee productivity. 

The AI Developer will be responsible for building scalable backend services using Python and FastAPI, integrating AI capabilities, developing APIs, and supporting AI orchestration workflows across the platform. The role requires strong hands-on experience in backend engineering, cloud-native development, API integrations, and modern AI application development. 

Responsibilities 

  • Design, develop, and maintain scalable backend services using Python and FastAPI. 

  • Build and integrate AI-powered services, APIs, and workflow orchestration components. 

  • Develop RESTful APIs and microservices for frontend, mobile, and enterprise integrations. 

  • Integrate Generative AI services, LLMs, vector databases, and semantic search capabilities. 

  • Build and implement agent-based workflows including multi-step execution, tool integrations, and AI-driven decision flows. 

  • Work with enterprise systems including HR, IT, identity, and operational platforms. 

  • Develop secure, scalable, and high-performance backend architectures. 

  • Implement asynchronous processing, event-driven communication, and API integrations. 

  • Collaborate with frontend, mobile, DevOps, product, and AI engineering teams. 

  • Support cloud-native deployments using containers and Kubernetes. 

  • Write clean, maintainable, and testable code with proper documentation and testing practices. 

  • Participate in code reviews, debugging, monitoring, and production support activities. 

  • Contribute to CI/CD pipelines, automated testing, and engineering best practices. 

  • Implement logging and monitoring for AI workflows including request tracing, latency tracking, and error analysis. 

Qualifications 

Need to Have 

  • 5+ years of experience in backend or platform engineering. 

  • Strong hands-on expertise in Python and FastAPI development. 

  • Experience building REST APIs, microservices, and backend integration services. 

  • Experience working with Generative AI, LLM APIs, AI orchestration frameworks, or AI-powered applications. 

  • Strong understanding of distributed systems and cloud-native application development. 

  • Experience with databases such as PostgreSQL, MongoDB, Redis, or vector databases. 

  • Knowledge of asynchronous programming and event-driven architectures. 

  • Experience with Docker, Kubernetes, CI/CD pipelines, and cloud platforms such as AWS, Azure, or GCP. 

  • Strong understanding of API security, authentication, and authorization mechanisms. 

  • Familiarity with Git-based workflows and Agile development practices. 

  • Strong debugging, problem-solving, and communication skills. 

  • Experience with RAG pipelines, vector databases, and semantic search. 

Good to Have 

  • Exposure to LangChain, LlamaIndex, OpenAI APIs, or similar AI frameworks. 

  • Experience with Kafka, RabbitMQ, or messaging/event-streaming platforms. 

  • Familiarity with Flutter/mobile integrations and frontend-backend communication. 

  • Experience in QSR, retail, hospitality, or enterprise digital platforms. 

  • Exposure to workflow automation and enterprise orchestration systems. 

  • Experience with observability, monitoring, and logging tools. 

  • Understanding of AI governance, prompt engineering, and AI evaluation frameworks.