Recruiting & Site Growth: Actively recruit, interview, and retain top-tier AI engineering talent to build out FloQast's Core AI capabilities in India.
Global Collaboration: Collaborate effectively with product managers, QA, architecture, security, and global engineering leaders to design and implement our centralized AI platform (model routing, provider management, vector search).
Process & Culture: Cultivate an engineering culture of innovative, egoless, high-trust problem solving. Champion lean software development, Agile principles, and robust LLMOps/DevOps practices for AI systems.
- Production Excellence: Ensure your team builds robust, compliant, and observable AI products that integrate seamlessly with diverse technologies (accounting systems, external APIs) in a B2B SaaS environment.
- What You'll Bring
- 5+ years of software engineering management experience, with a track record of leading teams to deliver complex backend or AI products to a paying customer base.
5+ years of experience as an individual contributor as a software engineer, with a strong background in Python, backend development, and cloud-native environments (AWS preferred).
Production AI Experience: Familiarity with LLM APIs, retrieval-augmented generation (RAG), conversational AI, and scalable system design for AI products.
Distributed Team Leadership: Proven experience leading and managing teams that are geographically distributed, driving alignment across time zones.
Recruiting & Mentorship: Hands-on experience recruiting and interviewing engineering personnel, alongside a strong track record of managing individuals' performance and career growth.
Agile & Delivery Mastery: 5+ years working on teams using Agile methodologies (Scrum, Kanban) with a strong commitment to automated testing, CI/CD, and DevOps practices.
- Communication & Alignment: Strong ability to communicate complex system designs and AI strategies to both technical and business stakeholders.
- Nice To Haves
- Experience managing managers of software engineering teams.
Hands-on experience with advanced RAG architectures, reranking systems, semantic search systems, or AI observability/monitoring tools.
Experience working on B2B SaaS products, particularly in the financial or accounting space.
Familiarity with our broader web stack (MongoDB, Express, React, and Node) to facilitate seamless integration between AI services and core applications.
Knowledge of model context protocols (MCP) or reinforcement learning techniques (RLHF).
