{"schemaVersion":"jobsearcher.job.v1","id":"14e49fee48a724099f353add","url":"https://jobsearcher.com/jobs/14e49fee48a724099f353add","canonicalUrl":"https://jobsearcher.com/jobs/14e49fee48a724099f353add","title":"Python + Gen AI Developer - Dallas, TX","description":"Role Summary:\nWe are seeking a Generative AI Engineer to build, optimize, and scale production-ready AI applications. You will design complex multi-agent systems, implement advanced RAG pipelines, and manage the deployment of both frontier and local LLMs. The ideal candidate blends deep machine learning expertise with modern software engineering practices.\n\nTechnical Stack:\n\nLLMs: Gemini, OpenAI, Claude, Llama, and Local Model deployment.\n\nFrameworks: LangChain, LlamaIndex, and Hugging Face.\n\nOrchestration: LangGraph and Multi-Agent Systems (MAS).\n\nDevelopment: Python, FastAPI, and Asynchronous Programming.\n\nRAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies.\n\nML/DL: PyTorch, TensorFlow, and Model Fine-tuning.\n\nDeployment: Docker, Production API management, and LLM monitoring.\n\nTools: Prompt Engineering, Workflow Design, and GenAI Optimization.\n\nKey Responsibilities:\n\nDevelop and orchestrate sophisticated AI workflows using LangGraph and multi-agent architectures.\n\nBuild and maintain Advanced RAG systems utilizing LlamaIndex and vector databases for high-accuracy retrieval.\n\nIntegrate and swap diverse LLMs (commercial and open-source) based on performance and cost requirements.\n\nDesign and deploy high-performance, scalable backend services using FastAPI and Async Python.\n\nFine-tune large language models (LLMs) using PyTorch/TensorFlow to improve domain-specific performance.\n\nOptimize GenAI workflows for latency, cost, and reliability using advanced prompt engineering and monitoring tools.\n\nContainerize and deploy AI services via Docker to production environments.\n\nRequired Qualifications:\n\n7+ years of hands-on experience building and deploying GenAI applications in a production setting.\n\nStrong proficiency in Python and the modern AI library ecosystem (LangChain, LlamaIndex, etc.).\n\nExperience with vector search, embedding models, and advanced data retrieval patterns.\n\nKnowledge of model fine-tuning techniques and local LLM quantization/hosting.\n\nFamiliarity with production-grade monitoring, API security, and CI/CD for ML.","company":"Photon","rawCompany":"photon","city":"Dallas","state":"TX","isRemote":false,"isActive":false,"createdAt":"2026-09-17T10:11:48.249Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Python + Gen AI Developer - Dallas, TX","description":"Role Summary:\nWe are seeking a Generative AI Engineer to build, optimize, and scale production-ready AI applications. You will design complex multi-agent systems, implement advanced RAG pipelines, and manage the deployment of both frontier and local LLMs. The ideal candidate blends deep machine learning expertise with modern software engineering practices.\n\nTechnical Stack:\n\nLLMs: Gemini, OpenAI, Claude, Llama, and Local Model deployment.\n\nFrameworks: LangChain, LlamaIndex, and Hugging Face.\n\nOrchestration: LangGraph and Multi-Agent Systems (MAS).\n\nDevelopment: Python, FastAPI, and Asynchronous Programming.\n\nRAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies.\n\nML/DL: PyTorch, TensorFlow, and Model Fine-tuning.\n\nDeployment: Docker, Production API management, and LLM monitoring.\n\nTools: Prompt Engineering, Workflow Design, and GenAI Optimization.\n\nKey Responsibilities:\n\nDevelop and orchestrate sophisticated AI workflows using LangGraph and multi-agent architectures.\n\nBuild and maintain Advanced RAG systems utilizing LlamaIndex and vector databases for high-accuracy retrieval.\n\nIntegrate and swap diverse LLMs (commercial and open-source) based on performance and cost requirements.\n\nDesign and deploy high-performance, scalable backend services using FastAPI and Async Python.\n\nFine-tune large language models (LLMs) using PyTorch/TensorFlow to improve domain-specific performance.\n\nOptimize GenAI workflows for latency, cost, and reliability using advanced prompt engineering and monitoring tools.\n\nContainerize and deploy AI services via Docker to production environments.\n\nRequired Qualifications:\n\n7+ years of hands-on experience building and deploying GenAI applications in a production setting.\n\nStrong proficiency in Python and the modern AI library ecosystem (LangChain, LlamaIndex, etc.).\n\nExperience with vector search, embedding models, and advanced data retrieval patterns.\n\nKnowledge of model fine-tuning techniques and local LLM quantization/hosting.\n\nFamiliarity with production-grade monitoring, API security, and CI/CD for ML.","datePosted":"2026-09-17T10:11:48.249Z","dateModified":"2026-09-17T10:11:48.249Z","hiringOrganization":{"@type":"Organization","name":"Photon","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Dallas","addressRegion":"TX","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"14e49fee48a724099f353add"},"url":"https://jobsearcher.com/jobs/14e49fee48a724099f353add"}}