
1001 - 5000 employees
âď¸ SaaS
đ¸ Finance
đ˘ Enterprise
đ° $798.6M Private Equity Round - insightsoftware on 2021-07
SaaS ⢠Finance ⢠Enterprise
insightsoftware is a provider of financial and operational reporting software and data analytics solutions for the Office of the CFO. Its cloud-enabled platform and pre-built connectors integrate with major ERPs (Oracle, SAP, Microsoft and 140+ others) to deliver financial reporting, budgeting/planning, consolidation, tax and lease lifecycle management, embedded analytics, and automation tools. The company serves finance, accounting, and operations teams with AI-enabled features, data virtualization, and turnkey templates to accelerate reporting, planning, and compliance.
đĽ 0 minutes ago
đşđ¸ United States â Remote
đľ $124k - $156k / year
â° Full Time
đ Senior
â Product Manager
đŚ H1B Visa Sponsor
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1001 - 5000 employees
âď¸ SaaS
đ¸ Finance
đ˘ Enterprise
đ° $798.6M Private Equity Round - insightsoftware on 2021-07
SaaS ⢠Finance ⢠Enterprise
insightsoftware is a provider of financial and operational reporting software and data analytics solutions for the Office of the CFO. Its cloud-enabled platform and pre-built connectors integrate with major ERPs (Oracle, SAP, Microsoft and 140+ others) to deliver financial reporting, budgeting/planning, consolidation, tax and lease lifecycle management, embedded analytics, and automation tools. The company serves finance, accounting, and operations teams with AI-enabled features, data virtualization, and turnkey templates to accelerate reporting, planning, and compliance.
⢠Define and maintain the AI Services strategy, roadmap, and quarterly priorities for agentic workflows, the tool and connector layer, and AI quality infrastructure ⢠Make trade-off decisions on sequencing, scope, and technical direction, supported by evidence ⢠Specify multi-step agent behavior, including planning, tool selection, memory, human-in-the-loop checkpoints, fallback paths, and guardrails ⢠Translate ambiguous business problems into reliable agent designs for finance users ⢠Own the Model Context Protocol surface and tool-interface roadmap ⢠Decide which company data, actions, and product capabilities are exposed to agents and third-party assistants ⢠Define contracts, versioning, and access controls for tool and connector interfaces ⢠Build and own evaluation frameworks using golden datasets, offline and online evaluations, regression harnesses, accuracy and hallucination measurement, and production observability ⢠Set AI quality bars that gate releases ⢠Support portfolio product managers and engineering teams through intake, integration documentation, reference implementations, adoption guidance, and adoption measurement ⢠Partner with the chief architect and engineering manager on design reviews, technical trade-offs, model and vendor selection, cost, and latency management ⢠Participate in sprint planning and refinement and unblock product decisions ⢠Define metrics including product-line adoption, agent task success rates, evaluation scores, cost per task, latency, and incident rates ⢠Report outcomes and recommendations to senior leadership ⢠Work with security, legal, and compliance on data handling, model governance, auditability, and customer trust concerns
⢠8 or more years in product management ⢠At least two years owning AI products as a hands-on individual contributor ⢠Demonstrated experience shipping large language model applications to production ⢠Working technical fluency in agentic architectures, including orchestration and planning patterns, tool and function calling, retrieval-augmented generation, context management, and prompt engineering ⢠Hands-on experience with the Model Context Protocol or comparable tool and plugin interfaces for connecting agents to enterprise systems ⢠Practical experience building or operating evaluation frameworks for AI systems, including dataset construction, metric selection, and result interpretation ⢠Experience delivering a shared platform or API-based service where other product teams are the primary consumers ⢠Ability to read code, reason about system design, and participate in architecture discussions with senior engineers ⢠Strong command of Agile delivery ⢠Ability to influence cross-functional teams and senior stakeholders without formal authority ⢠Excellent written communication ⢠Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience ⢠Preferred: experience taking AI capabilities to market in a B2B enterprise SaaS environment ⢠Preferred: background in enterprise finance, accounting, ERP, or business intelligence domains ⢠Preferred: experience managing inference cost, latency, and model routing across multiple providers at scale ⢠Preferred: familiarity with AI security, data residency, and regulatory considerations ⢠Preferred: prior experience as the first product hire on a team ⢠Preferred: contributions to open source AI tooling, published evaluation work, or an active public presence in the agentic AI community
⢠Additional bonus eligibility may apply ⢠Equal employment opportunity workplace ⢠Confidential handling of applicant information ⢠Background checks required for employment, where permitted by country, state/province
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