Senior FP&A Manager, Technology (Product & Engineering)

CreatorIQ•Los Angeles, CA

15d•$150,000 - $188,000•Hybrid

About The Position

CreatorIQ is looking for a Senior FP&A Manager, reporting to the VP of FP&A, to serve as the embedded finance partner to our Product and Engineering organizations. This is a hands-on, high-visibility role for someone who has done technology finance partnership before. You'll own the financial lens on how CreatorIQ builds our product, on resourcing decisions across the roadmap, on cloud and infrastructure spend, and on the ROI case for major engineering investments. You will work directly with Product and Engineering leaders as a trusted advisor, not just a reporting function, by translating technical initiatives and financial constraints into financial context that leadership can act on and that Product and Engineering can plan around.

Requirements

10+ years of FP&A or finance business partnership experience, with 5+ years specifically supporting Product and Engineering organizations at a technology or SaaS company.
Direct experience partnering with engineering leaders on cloud infrastructure cost management and optimization. You understand the cost drivers behind cloud spend and can hold a credible conversation with an engineering VP about them.
Hands-on experience forecasting variable, consumption-based costs and building usage-based pricing models. You can build a financial plan around a cost structure that scales with usage rather than a fixed budget.
Familiarity with AI/LLM-related cost structures (inference costs, token-based pricing from model providers, API/vendor costs) and how they factor into product margin and pricing decisions.
Experience building team productivity/efficiency metrics for Product and Engineering organizations and using them to inform headcount and investment decisions.
Proven track record of being a business partner for Product and Engineering, as the translation bridge between Finance and Technology teams.
A track record of building ROI/business-case models for technology investments and using them to influence real prioritization decisions.
Strong financial modeling and Excel skills; SQL a plus.
Experience with financial planning tools (e.g., Abacum, Adaptive Planning, Anaplan, or similar) and ERP systems (e.g., Sage, NetSuite).
Proficiency with and interest in AI assistants (e.g., Claude, ChatGPT) and workflow automation tools (e.g., n8n) for research, analysis, communication, and to streamline recurring finance processes.
Working knowledge of software capitalization rules (ASC 350-40) and how they apply to engineering headcount and project costs.
Excellent communication skills, including comfortability with translating technical and engineering concepts into financial terms for finance and executive audiences, and vice versa for technical audiences.
A bias toward being a proactive advisor, bringing insight to and challenging the Product/Engineering planning, not just a scorekeeper providing after-the-fact reporting.
Bachelor's degree in Finance, Accounting, Economics, or Engineering, or related field; MBA a plus but not required.

Nice To Haves

Prior experience at a B2B SaaS company, ideally with a significant enterprise customer base.
Experience supporting the investor-grade reporting rigor of a growth-equity or private-equity ownership structure.
Exposure to M&A or technology due diligence.

Responsibilities

Act as the primary finance business partner to Product and Engineering leadership, building the relationships and credibility to influence decisions, not just report on them after the fact.
Own budgeting, forecasting, and variance analysis for the Product and Engineering org, including headcount planning, cloud/infrastructure costs, and third-party software and tooling spend, during the strategic, annual, and quarterly planning cycles.
Partner with Engineering leaders to understand and optimize cloud hosting and infrastructure costs (e.g., AWS/GCP/Azure spend), identifying efficiency opportunities and tracking unit economics as the business scales into new product lines.
Build and own the forecasting model for variable, consumption-based costs across new product lines (cloud compute/storage, API and data usage, AI/LLM inference and token costs), tying usage drivers revenue.
Develop consumption-based pricing recommendations for products or features with usage-driven cost structures, including the underlying financial plan (margin targets, breakeven usage levels, and sensitivity to customer usage patterns) to support Product and executive decision-making.
Own cost analysis specific to AI-related spend (model inference, token consumption, third-party AI vendor/API costs), tracking cost per query/output, evaluating margin impact of AI-powered features, and partnering with Engineering to identify optimization opportunities as AI usage scales.
Analyze team productivity and efficiency across Product and Engineering, tracking metrics such as cost per engineer, output per engineer, and R&D spend as a percentage of revenue, to help leadership assess whether team structure and investment levels are producing the expected output.
Build and maintain ROI and business-case frameworks for major product and engineering investments (i.e. new features, platform re-architecture, build-vs-buy decisions, AI investments, M&A/tech integration) so leadership can prioritize with financial rigor.
Partner with Product and Engineering on roadmap prioritization, bringing a cost/benefit and capacity-allocation lens to planning cycles (strategic, annual and quarterly).
Support Accounting in the application of capitalization of internally developed software in accordance with GAAP (ASC 350-40).
Design recurring reporting and dashboards (e.g., cost per engineer, R&D spend as % of revenue, infrastructure cost per customer/unit), and work with BI teams to build, in order to increase leadership visibility and accountability.
Support headcount planning and tradeoffs across Product and Engineering, including contractor and offshore support analysis.
Actively engage with CIQ’s existing AI and automation initiatives, adopting tools like Claude, ChatGPT, and n8n in your own workflows, and contributing ideas to help extend their use across FP&A processes, reporting, and analysis.
Present findings and recommendations directly to both the Product/Engineering and executive leadership teams.