D
Datasnipper
Engineering Manager (Billing & Monetization)
Skills
PythonAIAzure
1 month ago
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Important information
Contract type:
Permanent
Salary:
$199,000 – $248,000 / year
Location:
New York, NY, USA
Work mode:
Onsite
Published on:
24 September 2026
What they need
- 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
- 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- Strong product aptitude; can challenge product framing, translate business and pricing needs into technical solutions, and make effective roadmap tradeoffs
- Minimum 5 years as a software engineer with a passion for building scalable, reliable, and high-quality software systems
- Strong understanding of software architecture, distributed systems, APIs, and cloud native development
- At least 3 years of leading and managing engineering teams, driving performance, growth, and professional development through hands-on mentorship, feedback, and goal setting
- 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
- Strategic thinker; able to shape product direction, technical direction, and team scope, not just execute on what’s handed down
- A track record of growing engineers and creating high-performing teams
- Entrepreneurial mindset with the ability to thrive in a fast-moving scale-up environment
- An empowerment style of management; you lead through outcomes and trust, not by assigning tasks
- Experience building billing, metering, payments, or monetization systems, ideally involving usage-based or credit-based pricing at scale
- Experience operating systems in production with a focus on accuracy, reliability, observability, and maintainability, especially where financial correctness matters
- Experience integrating with payment providers, billing platforms (e.g. Stripe), or ERP and financial systems
- Understanding of financial correctness concerns such as idempotency, reconciliation, auditability, and revenue recognition
- Experience with observability and monitoring tools
- Experience in fintech, audit technology, or document-intensive workflows
- Experience building usage-based, metered, or credit-based billing systems in production
- Familiarity with monetizing AI or agentic products, including token or usage metering and cost attribution
- Experience with Python and modern backend development practices
- Familiarity with Azure and cloud infrastructure
- Experience working in startups or scaleups
- Strong understanding of testing strategies and engineering quality practices
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