Python developer - Dallas, Tx

Photon•Dallas, TX

16h•$39,000 - $137,000•Onsite

About The Position

The Senior Python Developer will play a key role in designing, developing, and scaling our Agentic AI platform. This role requires deep expertise in Python development, AI-driven application architectures, and cloud-native technologies to build robust, scalable, and production-ready agentic solutions. You will be responsible for developing backend services, implementing agent orchestration workflows, integrating LLMs and external tools, and building resilient platforms that support enterprise AI use cases.

Requirements

10+ years of experience in software engineering with strong expertise in Python development.
Strong experience developing REST APIs, microservices architectures, and event-driven systems.
Hands-on experience with Agentic AI frameworks such as LangGraph, CrewAI, AutoGen, or Agent Development Kit (ADK).
Experience building and supporting RAG-based applications and enterprise AI solutions.
Strong knowledge of LangChain, LlamaIndex, LangSmith, and LangFlow.
Experience working with LLMs including OpenAI, Gemini, Anthropic, Llama, or similar models.
Deep understanding of prompt engineering, function calling, tool integration, agent orchestration, and evaluation techniques.
Experience with vector databases such as Pinecone, Weaviate, Chroma, or Milvus.
Strong proficiency in PostgreSQL, MySQL, MongoDB, Redis, and database optimization techniques.
Experience with cloud platforms (AWS, Azure, or GCP) and cloud-native application development.
Familiarity with Docker, Kubernetes, and containerized deployment patterns.
Experience implementing CI/CD pipelines using tools such as Jenkins, GitHub Actions, or GitLab CI.
Experience with monitoring, logging, and observability tools for production systems.

Responsibilities

Design, develop, and maintain scalable backend services and APIs using Python and modern development frameworks.
Build and support agent orchestration workflows that enable autonomous decision-making, task execution, and multi-step reasoning.
Develop integrations with LLM providers such as OpenAI, Gemini, Anthropic, and open-source models to power AI-driven applications.
Build and optimize Retrieval-Augmented Generation (RAG) pipelines leveraging vector databases and enterprise knowledge sources.
Develop resilient, high-performance platform services that support secure and scalable AI deployments.
Create Python-based tools and connectors that enable agents to interact with APIs, databases, enterprise applications, and external services.
Implement automated testing, evaluation frameworks, and quality controls to ensure reliability and consistency of AI systems.
Optimize application performance, latency, scalability, and infrastructure utilization across AI workloads.