Senior Software Engineer, AI

Job description

As a Senior 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. You will not only build AI applications but also shape the technical direction of AI across FloQast, establishing the platform and standards that enable distributed AI execution company-wide. ### What You'll Do - 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 ### What You'll Bring - 5+ years of professional software engineering experience with 4+ years focused on building backend for production applications - Mastery of Python, Familiarity with some AI application frameworks, context engineering, and scalable system design for AI products - Expertise in 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 lead tech product initiatives, establish 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