# Staff Software Engineer, AI at Floqast

- Company: Floqast
- What the company does: AI agents that automate reconciliations, close workflows, and journal entries — fully auditable, human-approved every step. Trusted by 3,500+ teams worldwide. Backed by Insight, Norwest and ICONIQ.
- Company website: https://floqast.com/
- Type: Startups (AI role)
- Level: Senior
- Location: San Jose, California
- Work setup: Hybrid
- Posted: 2025-10-07
- Apply by: 2026-10-08
- Apply: https://jobs.lever.co/floqast/1bdd0327-986d-4cc5-826f-6f130e2db5d0
- Page: https://www.1752.vc/careers/jobs/floqast-staff-software-engineer-ai/

## About the role

As a Staff AI Engineer on our Core AI team, you will be a cornerstone of FloQast's AI transformation. You will architect, build, and scale the AI products that power our accounting automation platform and enable our vision of an AI accountant teammate. This role requires deep expertise in production AI systems and a passion for solving complex accounting workflow challenges.

## What they're looking for

- Architect and lead development of production AI products including intelligent chatbots, document processing systems, and agentic workflows using Python and modern AI frameworks
- Design and implement our centralized AI platform including model routing, provider management, vector search, and AI application frameworks with seamless MCP (Model Context Protocol) integrations
- Build scalable AI products that integrate with diverse technologies including accounting systems, document repositories, and external APIs while maintaining robust monitoring and observability
- Master context engineering and system design for AI applications, ensuring optimal information retrieval, context assembly, and multi-turn conversation management
- Collaborate with Product, Engineering, and Security teams to ensure AI products are robust, compliant, and aligned with business objectives in the regulated accounting space
- Provide technical leadership and mentorship to the growing AI team, establishing best practices for AI product development, deployment, and governance

Tags: Engineering