Python Developer Dallas at Photon

Job description

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. Key Responsibilities: Backend Development: Design, develop, and maintain scalable backend services, APIs, and platform components using Python and related frameworks. Agent Development: Build and implement agent orchestration workflows using modern frameworks such as LangGraph, CrewAI, AutoGen, or similar technologies. LLM Integration: Integrate and optimize LLM-powered capabilities using platforms such as OpenAI, Gemini, Anthropic, and open-source models. RAG Implementation: Develop and maintain Retrieval-Augmented Generation (RAG) solutions leveraging enterprise knowledge bases and vector databases. Tool Integration: Create tools, connectors, and APIs that enable agents to interact with databases, business systems, and third-party applications. Platform Development: Contribute to the development of scalable, resilient, and secure AI platform capabilities that support enterprise deployments. Testing & Evaluation: Develop testing strategies and evaluation frameworks to measure agent accuracy, reliability, performance, and overall effectiveness. Performance Optimization: Optimize AI workflows, token utilization, model selection, and infrastructure to improve latency and cost efficiency. Required Skills & Qualifications: • 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. Compensation, Benefits and Duration Minimum Compensation: USD 35,000 Maximum Compensation: USD 123,000 Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role. Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees. This position is not available for independent contractors No applications will be considered if received more than 120 days after the date of this post Job Description Template

Requirements

Must-haves

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.
Backend Development: Design, develop, and maintain scalable backend services, APIs, and platform components using Python and related frameworks.
Agent Development: Build and implement agent orchestration workflows using modern frameworks such as LangGraph, CrewAI, AutoGen, or similar technologies.
LLM Integration: Integrate and optimize LLM-powered capabilities using platforms such as OpenAI, Gemini, Anthropic, and open-source models.
RAG Implementation: Develop and maintain Retrieval-Augmented Generation (RAG) solutions leveraging enterprise knowledge bases and vector databases.
Tool Integration: Create tools, connectors, and APIs that enable agents to interact with databases, business systems, and third-party applications.
Platform Development: Contribute to the development of scalable, resilient, and secure AI platform capabilities that support enterprise deployments.
Testing & Evaluation: Develop testing strategies and evaluation frameworks to measure agent accuracy, reliability, performance, and overall effectiveness.
Performance Optimization: Optimize AI workflows, token utilization, model selection, and infrastructure to improve latency and cost efficiency.
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.
Compensation, Benefits and Duration
Minimum Compensation: USD 35,000

Nice-to-haves

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Keywords to mirror

pythonaillmrestawsazuregcpdockerkubernetesci/cd

Platform: oracle-cloud
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Paid Time Off