Python Developer- Phoenix, AZ

Role Descriptions: Python &

• API Engineering Strong hands-on experience with Python 3.11 and production backend development. Strong experience building secure| scalable REST APIs and microservices using FastAPI; familiarity with Flask/Django isuseful. Strong understanding of asynchronous Python| API design| validation| error handling| authentication/authorization| andenterprise integration patterns.Generative AI| RAG &
• Knowledge Infrastructure Hands-on production experience building enterprise Generative AI applications using LLMs| RAG| semantic search|embeddings| and vector databases; ideally 2 years of recent GenAI/RAG experience. Strong hands-on experience with LangChain and/or LangGraph for agentic workflows| orchestration| tool calling| multi-stepexecution| and controlled agent runtimes. LangGraph experience is preferred for stateful agent orchestration.

Experience designing knowledge ingestion| document chunking| embedding generation| metadata enrichment|retrieval/reranking| context assembly| grounded generation| and response validation pipelines.

Experience with PostgreSQL and vector search. pgvector experience is highly desirable but not mandatory. Strong understanding of prompt engineering| AI agents| guardrails| human-in-the-loop patterns| AI evaluation| responsibleAI| and secure enterprise data access.

Platform

Engineering| DevOps &

• Observability Strong hands-on experience with Docker and Kubernetes for production AI services.

Experience with Git and CI/CD pipelines using GitHub Actions| Jenkins| or equivalent tools for automated build| test| and deployment.

Experience with production monitoring and observability using OpenTelemetry| Prometheus| Grafana| Splunk/ELK| or equivalent tools. Ability to troubleshoot performance| reliability| retrieval quality| API| infrastructure| and production issues across distributed AI systems. Strong analytical| problem-solving| documentation| and cross-functional communication skills.

Preferred / Good-to-Have Skills LangGraph for stateful agent orchestration and reusable agent-runtime patterns. PostgreSQL pgvector or equivalent production vector-database experience.

Model Context

Protocol (MCP)| tool integration protocols| or reusable agent-tool interfaces. OpenTelemetry and production AI/agent observability

• GitHub Actions experience.

Experience with automated RAG/agent evaluation| regression datasets| retrieval-quality metrics| and grounded-response validation.Roles &

• ResponsibilitiesKnowledge Base &
• AI Platform Engineering Design| develop| maintain and evolve enterprise knowledge-base infrastructure and AI-enabled backend services usingPython and FastAPI. Build and optimize ingestion| chunking| embedding| vector indexing| semantic retrieval| reranking| context construction andgrounded RAG pipelines.

Develop

LangChain and/or LangGraph-based agent workflows and reusable agent-runtime capabilities including toolcalling| state management| retr Essential Skills: Python &

• API Engineering Strong hands-on experience with Python 3.11 and production backend development. Strong experience building secure| scalable REST APIs and microservices using FastAPI; familiarity with Flask/Django isuseful. Strong understanding of asynchronous Python| API design| validation| error handling| authentication/authorization| andenterprise integration patterns.Generative AI| RAG &
• Knowledge Infrastructure Hands-on production experience building enterprise Generative AI applications using LLMs| RAG| semantic search|embeddings| and vector databases; ideally 2 years of recent GenAI/RAG experience. Strong hands-on experience with LangChain and/or LangGraph for agentic workflows| orchestration| tool calling| multi-stepexecution| and controlled agent runtimes. LangGraph experience is preferred for stateful agent orchestration.

Experience designing knowledge ingestion| document chunking| embedding generation| metadata enrichment|retrieval/reranking| context assembly| grounded generation| and response