Engineering Manager, Billing & Monetization

DataSnipper•New York, NY

1d•$199,000 - $248,000•Hybrid

About The Position

We are looking for a skilled and passionate Engineering Manager to join our Billing & Monetization Team in the New York City office. Working in a bootstrapped and profitable scaleup, you'll have the unique opportunity to lead the team that powers how our agentic AI products are metered, priced, and billed, building the systems that turn AI usage into reliable, transparent revenue for a fast-growing category-defining company. Why DataSnipper? Audit and finance are still massively manual, and we're changing that. DataSnipper is a $1B, bootstrapped unicorn with 600,000+ users across 180+ countries, already embedded in the daily workflows of top audit and accounting firms. Now, we're bringing AI directly into where the work actually happens through our agentic products, and monetizing AI usage at scale is central to how we grow. As our agentic products expand, so does the complexity of measuring and monetizing them. Credit consumption, usage-based billing, and transparent pricing are core to the business, and the systems behind them need to be accurate, real-time, and trustworthy. If you want to own the infrastructure where AI usage meets revenue at scale, this is the place.

Requirements

At least 3 years of leading and managing engineering teams, driving performance, growth, and professional development through hands-on mentorship, feedback, and goal setting.
Minimum 5 years as a software engineer with a passion for building scalable, reliable, and high-quality software systems.
Seasoned user of AI development tools yourself, with hands-on fluency in AI-assisted coding and agentic coding harnesses, and a track record of leading engineering teams that build with these tools day to day and are measurably more effective as a result.
Experience building billing, metering, payments, or monetization systems, ideally involving usage-based or credit-based pricing at scale.
An empowerment style of management; you lead through outcomes and trust, not by assigning tasks.
Strong product aptitude; can challenge product framing, translate business and pricing needs into technical solutions, and make effective roadmap tradeoffs.
Strong understanding of software architecture, distributed systems, APIs, and cloud native development.
Experience operating systems in production with a focus on accuracy, reliability, observability, and maintainability, especially where financial correctness matters.
A track record of growing engineers and creating high-performing teams.
Strategic thinker; able to shape product direction, technical direction, and team scope, not just execute on what's handed down.
Entrepreneurial mindset with the ability to thrive in a fast-moving scale-up environment.

Nice To Haves

Experience building usage-based, metered, or credit-based billing systems in production.
Experience integrating with payment providers, billing platforms (e.g. Stripe), or ERP and financial systems.
Familiarity with monetizing AI or agentic products, including token or usage metering and cost attribution.
Experience with Python and modern backend development practices.
Understanding of financial correctness concerns such as idempotency, reconciliation, auditability, and revenue recognition.
Familiarity with Azure and cloud infrastructure.
Experience with observability and monitoring tools.
Experience working in startups or scaleups.
Experience in fintech, audit technology, or document-intensive workflows.
Strong understanding of testing strategies and engineering quality practices.

Responsibilities

Lead an engineering team through outcomes, not tasks; set clear goals with the team and trust them to figure out how.
Make the team measurably better; raise the engineering bar, grow engineers into bigger problems, and address performance issues directly when they arise.
Drive a step change in what the team can do with AI; not just shipping faster, but tackling harder problems, raising quality, and expanding what the team can credibly own.
Lead the team responsible for building the credit, metering, and billing systems that power monetization across our agentic AI products, from usage tracking and credit consumption to invoicing and revenue reporting.
Own the technical direction and architecture of the billing and monetization platform, ensuring metering is accurate, billing is reliable, and the systems are observable, secure, and auditable.
Guide the team in designing and scaling systems that meter AI and agent usage in real time, enforce credit limits and entitlements, and integrate with pricing, payments, and financial systems.
Partner closely with Product, Finance, and other Engineering teams to shape pricing and packaging, and translate monetization strategy into robust technical implementation.
Make the architectural and technical calls that shape the team's systems, and stay close enough to the code to do so credibly.
Lead the adoption of AI-assisted engineering practices, including AI coding tools and agentic coding harnesses, and set the bar for how the team uses them to drive outcomes; contribute to how DataSnipper leverages AI across the broader engineering organization.
Help shape the team's scope as it evolves, including expanding ownership areas and standing up new teams when needed.
Foster a culture of experimentation, learning, documentation, and operational excellence.