What You'll Do
Contribute to the architecture 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 components of 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
Implement 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 guidance and mentorship to other engineers on the growing AI team, promoting best practices for AI product development, deployment, and governance
What You'll Bring
7+ years of professional software engineering experience with 3+ years focused on building backend for production applications
Strong proficiency in Python, alongside familiarity with AI application frameworks, context engineering, and scalable system design for AI products
Experience designing products that integrate with multiple technologies, APIs, and data sources in cloud-native environments (AWS preferred)
Strong desire to develop deep hands-on experience with LLM APIs, retrieval-augmented generation (RAG), conversational AI, document processing, and MCP integrations
Proven ability to own tech product initiatives, drive technical standards, and communicate complex system designs to both technical and business stakeholders
Nice To Haves/Other
Experience building chatbots or conversational AI products in production
Background in system integration, API design, or enterprise software platforms
Familiarity with accounting workflows and financial data processing
Experience with AI observability, debugging tools, and production AI monitoring
Hands-on experience with advanced RAG architectures, reranking systems, and retrieval optimization techniques
Knowledge of reinforcement learning from human feedback (RLHF) or other RL techniques for improving AI product performance
Experience building AI platform components like embedding pipelines, semantic search systems, or multi-modal processing frameworks
Here’s Why You Should Apply
- What is engineering working on? Our FQ Engineering Blog showcases a number of our recent efforts straight from the engineers working on them. Check it out!Skills Required
- 7+ years professional software engineering experience
- 3+ years focused on building backend for production applications
- Strong proficiency in Python
- Familiarity with AI application frameworks, context engineering, and scalable AI system design
- Experience designing products that integrate with multiple technologies, APIs, and data sources in cloud-native environments (AWS preferred)
- Experience or strong desire to develop hands-on experience with LLM APIs, retrieval-augmented generation (RAG), conversational AI, document processing, and MCP integrations
- Proven ability to own technical product initiatives, drive technical standards, and communicate complex system designs to technical and business stakeholders
- Experience building chatbots or conversational AI products in production
- Background in system integration, API design, or enterprise software platforms
- Familiarity with accounting workflows and financial data processing
- Experience with AI observability, debugging tools, and production AI monitoring
- Hands-on experience with advanced RAG architectures, reranking systems, and retrieval optimization techniques
- Knowledge of reinforcement learning from human feedback (RLHF) or other RL techniques
- Experience building AI platform components like embedding pipelines, semantic search systems, or multi-modal processing frameworks
What the Team is Saying
%20(1).jpg)
%20(1).jpg)
FloQast Compensation & Benefits Highlights
-
Healthcare Strength — Health coverage includes multiple medical plan options with some 100% employer‑paid, plus dental/vision, mental‑health access, and income‑protection coverage. Options are described as generous, with fully paid plans available for employees and in some cases families.
-
Parental & Family Support — Parental support features paid leave commonly cited around 16 weeks for birthing parents, alongside fertility benefits via Carrot and a subsidized SNOO rental. Adoption assistance and broader family‑forming support are also referenced as part of the package.
-
Leave & Time Off Breadth — Time away includes an unlimited PTO framework, generous vacation and sick time, and company‑wide Catch‑Up Days to recharge. Additional paid holidays and flexible time off constructs are highlighted.
FloQast Insights
What We Do
By automating and streamlining common accounting workflows to make them more efficient, FloQast is where accounting teams want to work so they can focus on what matters most, even when that’s just logging off on time. Whether automating reconciliations, documentation requests, or streamlining recurring accounting processes, such as the month-end close, financial reporting, or payroll, FloQast's platform enhances the way accounting teams already work to help them operate more efficiently.
Why Work With Us
Our cloud-based, AI-enhanced software is trusted by more than 3,000 accounting teams, including those at Twilio, Gong, Instacart, and The Golden State Warriors - and still growing! We aspire to forever elevate accounting and improve both the practice and perceptions of the profession.
Gallery
FloQast Teams
FloQast Offices
Remote Workspace
Employees work remotely.
FloQast's Employee Choice policy allows employees to choose to be hybrid or remote!
