Full Stack Engineer (Python + React)

We are seeking a skilled Full Stack Engineer to develop and deliver production-quality applications for our client. In this role, you will take full ownership of features from backend services built with FastAPI to frontend interfaces using React and TypeScript. You will also integrate these applications with large language model (LLM)-driven agentic workflows operating on Databricks. The ideal candidate approaches model output as inherently uncertain and implements robust safeguards to ensure reliability and accuracy.

Key Responsibilities

- Design, develop, and deploy full-stack features using Python/FastAPI on the backend and React/TypeScript on the frontend.
- Integrate applications with LLM-driven agentic workflows, including prompt engineering, structured tool schemas, and tool-calling pipelines.
- Implement production safeguards around model behavior, such as retry and salvage strategies for truncated outputs, validation of model-generated data, and guardrails to mitigate unreliable responses.
- Create clear and maintainable API contracts between the user interface, backend services, and AI components, ensuring comprehensive error handling and observability.
- Work with Databricks technologies including Unity Catalog, SQL Warehouses, Lakehouse Federation, and the Genie Conversational API to build conversational analytics solutions.
- Diagnose and resolve platform-level issues related to permission boundaries, compute and network limitations, and federated-query governance, translating findings into long-term fixes.
- Participate actively in code reviews, technical design discussions, and release planning while collaborating closely with onsite teams and client stakeholders.

Required Qualifications

- 5 to 7 years of professional software engineering experience.
- Proven track record of building and shipping production-grade full-stack applications with a Python/FastAPI backend and React/TypeScript frontend.
- Hands-on experience integrating applications with LLM-driven agentic workflows.
- Expertise in designing LLM prompt and tool-calling pipelines with production safeguards, including retry and salvage mechanisms for truncated model outputs, structured tool schemas, and guardrails against unreliable model-generated data.
- Strong foundation in API design, testing methodologies, version control, and CI/CD best practices.
- Excellent written and verbal communication skills, with the ability to collaborate effectively across distributed teams and with client stakeholders.

Preferred Qualifications

- Experience working with Databricks components such as Unity Catalog, SQL Warehouses, Lakehouse Federation, and the Genie Conversational API.
- Background in business intelligence, analytics, or conversational data product development.

This position offers the opportunity to work on cutting-edge AI-driven applications within a collaborative and innovative environment, contributing to impactful solutions that leverage advanced data and conversational technologies.