Finance Engineer
About the role
Finance Engineer role at AssemblyAI focused on building data pipelines, dashboards, and automation to run finance and revenue operations with a systems-first approach.
Responsibilities
- Own unit economics — build and maintain cost-to-serve, gross margin, and contribution models by product, customer, and workload, rebuilt from source data rather than spreadsheets.
- Own budgeting for the technology organization: cloud and GPU/TPU spend attribution, vendor and capacity forecasting, and the models engineering leadership uses to plan.
- Build and run finance dashboarding — a single source of truth for burn, runway, margin, and company KPIs that the leadership team and board can trust.
- Automate budget-vs-actuals: live department-level views and overspend alerts that make budget and margin targets enforceable without manual chasing.
- Build the deal desk framework: pricing and discount guardrails derived from the margin model, automated quote and order-form generation, and routing so only non-standard deals need escalation.
- Automate sales compensation: implement a comp tool and the pipelines behind it so statements, accelerators, and disputes run from CRM and billing data instead of spreadsheets.
- Design and ship finance agents and internal tools — workflows that pull, reconcile, and summarize financial data so non-engineers get answers without filing a ticket.
- Build and maintain the finance data layer: pipelines from billing, payroll, cloud, and accounting systems into a well-modeled warehouse.
- Partner with the VP Finance, Controller, and engineering leadership to trace discrepancies to their real source and ship fixes that hold.
Qualifications
- Strong data engineering fundamentals, including SQL, Python, warehouse modeling, and orchestration (dbt, Airflow, or equivalent).
- Measurement discipline: define and validate numbers before building them, reconcile results, treat unexplained variance as a problem.
- Appetite for the whole stack: pipelines to deeper areas like billing events or cloud tags when needed.
- Experience with financial or operational data (revenue, cost, billing, payroll, or cloud spend) and fluency in revenue, cost, and margin structures to model them.
- Track record of building internal tools, dashboards, or automations relied on by non-engineers.
- Familiarity with LLM-based agent workflows and applying them to operational processes.
- Enthusiasm for automating existing processes to improve speed and reliability.
- Strong Python skills; experience with accounting, billing, or ERP APIs (NetSuite, Stripe, or similar) is a plus.
- Excellent communication and collaborative mindset.
Skills
Benefits
- Competitive salary range: $160,000 - $240,000 (US)
- Remote - North America work location
- Opportunity to own cross-functional impact in a lean, meritocratic environment
- Equity likely typical for growth-stage roles (not explicitly stated)

About AssemblyAI
APIs for AI models
AssemblyAI is an applied AI company. We research, train, and deploy State-of-the-Art AI models for developers and product teams to integrate into their products/apps. Today, we offer AI models for audio transcription, content moderation, summarization, topic detection, and many other tasks. We are working towards building the "Stripe for AI models" - where developers and product teams will be able to easily access State-of-the-Art AI through a simple API. We're a fully remote team of AI researchers and ML engineers, and have raised over $65M in funding from top investors including Accel, Insight Partners, Y Combinator, John/Patrick Collison, Daniel Gross, and Nat Friedman.
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