Python Developer

Python Developer Onsite role | Phoenix, AZ

Responsibilities

• Contribute to the design and implementation of LLM-powered and agentic product features.

• Build and extend agentic AI workflows that reason over context, call tools, and perform actions under guidance from senior engineers.

• Help implement and maintain retrieval-augmented generation (RAG) pipelines over financial data, with an emphasis on correctness and safety.

• Contribute to shared AI infrastructure such as LLM services, orchestration components, and evaluation or monitoring tooling.

• Participate in operating AI systems in production, including monitoring, debugging, and improving reliability and performance.

• Collaborate closely with product and design partners, learning to translate customer needs into technical solutions.

Technical Environment

We don t hire to a narrow checklist, but candidates should be excited to grow in a modern, enterprise-scale engineering environment with a focus on agentic AI.

Core engineering stack

• Languages: Python

• Cloud and infrastructure: AWS and/or Google Cloud Platform, Kubernetes

• APIs and services: REST, gRPC

• Distributed systems: event-driven architectures, including Kafka

Agentic AI and ML

• Commercial and open-source LLMs integrated into agentic workflows

• Tooling for agent orchestration, retrieval-augmented generation, vector storage, and evaluation

• Schema validation and structured data handling

AI-assisted development

• Use of AI-assisted and agentic development tools for design, implementation, testing, debugging, and refactoring

• Learning how to apply these tools responsibly while maintaining production-quality standards

• All systems are built to meet high standards for reliability, security, and auditability, reflecting the responsibility of deploying autonomous AI in a financial services environment.

Preferred Qualifications

• Exposure to LLM tooling, prompt engineering, RAG, or agent frameworks through work, coursework, or personal projects.

• Internship or early-career experience in fintech or other regulated environments.

• Contributions to open-source projects, hackathons, or side projects related to AI or developer tooling.