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Cube is a financial intelligence platform built for the AI era, automating data management for the Office of the CFO. The company has raised over $65M from top-tier investors including Battery Ventures and Mayfield, and was recognized by Forbes as one of the Best Places to Work in 2026.
You will serve as a technical North Star for the engineering organization, acting as a highly strategic individual contributor who shapes architectural patterns, infrastructure standards, and engineering practices across the company. Reporting to an Engineering Manager, you will partner closely with Engineering, Product, and Customer Success to transform ambiguous business needs into robust distributed systems powering real financial workflows.
Key responsibilities include:
**Technical Leadership:** Define architectural direction and establish engineering patterns that become the golden path across teams. Design and evolve complex backend systems including multi-tenant database routing, distributed task orchestration, async pipelines, and enterprise integrations. Lead adoption of AI-assisted development practices and LLM agent systems within production environments.
**Execution & Excellence:** Take ambiguous product goals and deliver them end-to-end, from infrastructure (CDK) and deployment to monitoring and documentation. Foster a culture of observability by default, owning strategies around structured logging, APM tooling, metrics, and production debugging workflows. Act as a steady technical leader during production incidents, guiding root-cause analysis and long-term remediation strategies.
**Mentorship & Culture:** Remove technical blockers, mentor engineers, and promote psychological safety alongside a culture of continuous improvement. Continuously improve CI/CD pipelines, testing infrastructure, release processes, and deployment strategies so teams can ship safely at speed.
**Tech Stack:** Python (Django + DRF), MySQL, ClickHouse, Redis, RabbitMQ, Celery, AWS (deployed via CDK), CI/CD automation, JavaScript/TypeScript (React/Redux) frontend, AI-driven workflows, LLM agents, enterprise integrations, and advanced observability.
**Requirements:**
- Typically 10+ years of professional software engineering experience (flexibility for exceptional candidates demonstrating strong Staff-level impact, ownership, and technical leadership)
- Deep knowledge of Django internals including middleware, database routing, management commands, signals, and performance optimization in high-scale, multi-tenant environments
- Strong experience building and evolving distributed systems across cloud infrastructure; comfortable debugging complex concurrency challenges (race conditions, distributed deadlocks, async failures, large-scale database performance issues)
- Experience with dataframe-based computation tools such as Pandas, Polars, or NumPy to power data-intensive workflows and financial modeling pipelines
- Proven ability to define engineering standards, design reusable abstractions, and improve developer velocity through internal tooling and frameworks
- Early adopter of AI-assisted engineering workflows (Cursor, Claude Code, automated refactoring, or similar tooling) to increase velocity without sacrificing reliability or code quality
- Ability to clearly explain architectural trade-offs to executives, product partners, and engineers at all levels
- Nice to have: Familiarity with FP&A domain concepts such as trial balances, charts of accounts, fiscal calendars, scenario modeling, and multi-currency workflows
Note: This position requires working onsite at the New York office Tuesday through Thursday. Immigration sponsorship is not available at this time.
