Python Developer Dallas, TX

Photon•Dallas, TX

16h•$35,000 - $123,000•Onsite

About The Position

The Python Developer will play a critical role in building and enhancing our Agentic AI platform, developing intelligent systems that leverage Large Language Models (LLMs), agent orchestration frameworks, and cloud-native technologies. This role requires a strong blend of backend engineering expertise, AI application development, and problem-solving skills to deliver scalable, secure, and production-ready solutions. You will be responsible for developing AI-powered services, implementing agent workflows, integrating enterprise systems and external tools, and contributing to the evolution of the platform.

Requirements

6–9 years of experience in software development with strong expertise in Python.
Hands-on experience with Python frameworks such as FastAPI, Flask, or Django.
Strong experience in developing REST APIs, microservices, and backend applications.
Experience working with Agentic AI frameworks such as LangGraph, CrewAI, AutoGen, Agent Development Kit (ADK), or similar technologies.
Experience building and supporting RAG-based applications and AI-powered solutions.
Hands-on experience with LangChain, LlamaIndex, LangSmith, or LangFlow.
Working knowledge of LLMs including OpenAI, Gemini, Anthropic, Llama, or equivalent models.
Strong understanding of prompt engineering, function calling, tool integration, and agent orchestration patterns.
Experience with vector databases such as Pinecone, Weaviate, Chroma, or Milvus.
Proficiency in relational databases (PostgreSQL, MySQL) and NoSQL databases (MongoDB, Redis).
Experience with cloud platforms such as AWS, Azure, or GCP.
Familiarity with Docker, Kubernetes, and containerized application deployments.
Experience working with CI/CD pipelines and tools such as Jenkins, GitHub Actions, or GitLab CI.

Responsibilities

Design, develop, and maintain scalable backend services, APIs, and platform components using Python and related frameworks.
Build and implement agent orchestration workflows using modern frameworks such as LangGraph, CrewAI, AutoGen, or similar technologies.
Integrate and optimize LLM-powered capabilities using platforms such as OpenAI, Gemini, Anthropic, and open-source models.
Develop and maintain Retrieval-Augmented Generation (RAG) solutions leveraging enterprise knowledge bases and vector databases.
Create tools, connectors, and APIs that enable agents to interact with databases, business systems, and third-party applications.
Contribute to the development of scalable, resilient, and secure AI platform capabilities that support enterprise deployments.
Develop testing strategies and evaluation frameworks to measure agent accuracy, reliability, performance, and overall effectiveness.
Optimize AI workflows, token utilization, model selection, and infrastructure to improve latency and cost efficiency.