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Photon

AI Dev (Features + CHQ)_Tempe,AZ

Reposted One Month Ago
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In-Office or Remote
Hiring Remotely in United States
Senior level
In-Office or Remote
Hiring Remotely in United States
Senior level
Design and build scalable Python/FastAPI backend services integrating generative AI, LLMs, vector databases and RAG. Develop REST APIs, agent-based workflows, async/event-driven processing, and cloud-native deployments (Docker/Kubernetes). Implement security, observability, CI/CD, and production support while collaborating with cross-functional teams.
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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. 

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