Senior Product Manager, AI

What You'll Do:

• Own the vision, strategy, and roadmap for FloQast's Core AI Platform, establishing it as the foundational layer for all AI initiatives across the companyPartner closely with senior Product and Engineering leadership to align the platform roadmap with company-wide AI goals and emerging customer needsIdentify opportunities to consolidate redundant AI work (e.g., Document parsing, RAG implementations) into shared platform capabilities
• Serve as the AI infrastructure partner for product teams across FloQast, understanding their AI use cases and translating them into platform requirementsConduct discovery sessions with internal teams to identify common AI patterns, pain points, and opportunities for shared solutionsBuild a platform that enables non-AI engineers to leverage sophisticated AI capabilities through intuitive APIs and templatesCreate the "paved road" for AI development—making it easier to do AI the right way than to build custom solutions
• Design and prioritize platform components including RAG frameworks, agent orchestration systems, model evaluation pipelines, state management, and monitoring toolsEnsure the platform supports enterprise-grade requirements: audibility, explainability, reliability, and securityDefine success metrics for platform adoption and AI feature quality across the organization
• Bring deep technical understanding of AI systems—their capabilities, limitations, and operational challenges—to guide platform architecture decisionsEstablish evaluation frameworks and quality standards for AI features built on the platformPartner with Engineering to make sound long-term technical investments while delivering near-term valueChampion AI best practices including prompt engineering, model evaluation, human-in-the-loop workflows, and responsible AI principles
• Act as the primary evangelist for the Core AI Platform, building internal awareness and driving adoption across product teamsDevelop documentation, tutorials, and enablement materials that make the platform accessible to diverse technical audiencesMeasure and communicate platform impact through metrics like reduction in time-to-market for AI features, consistency of AI quality, and engineering efficiency gains

What You'll Bring:

• 3+ years of hands-on experience with AI/ML systems, including:
• Production experience with LLMs, RAG architectures, or agentic AI systems
• Understanding of prompt engineering, model evaluation, and AI system observability
• Knowledge of AI infrastructure challenges: latency, cost optimization, reliability, and quality control
• Familiarity with AI development frameworks and tools (LangChain, LlamaIndex, or similar)
• 5+ years in B2B SaaS product management, with at least 2 years building developer-facing platforms, infrastructure products, or internal tooling
• Experience defining platform abstractions that balance flexibility and ease-of-useTrack record of driving adoption of internal platforms across multiple teams, including partnering on product requirements discoveryUnderstanding of API design principles and developer experience considerations
• Ability to engage deeply with engineering teams on technical architecture, make informed tradeoffs, and guide complex technical decisions
• Comfort reading code and understanding system design patterns
• Experience with data pipelines, APIs, and enterprise integration patterns
• Understanding of evaluation methodologies for AI systems (deterministic vs. non-deterministic approaches)
• Proven ability to identify high-impact opportunities, prioritize ruthlessly, and build roadmaps that align platform capabilities with business outcomesExperience balancing competing priorities from multiple internal stakeholders
• Skill in "T-shirt sizing" technical initiatives and communicating tradeoffs

Preferred Qualifications

• Experience with enterprise accounting, financial close processes, ERP systems (SAP, Oracle, NetSuite, Workday), or accounting platforms (BlackLine, HighRadius, FloQast)
• Background in enterprise-scale data processing, document intelligence, workflow automation, or low/no code platforms
• Experience building AI products in regulated or audit-intensive industries
• Prior experience as a technical founder, engineer, or solutions architect transitioning to product management
• Familiarity with agentic AI architectures, multi-step reasoning systems, or compound AI patterns