Staff Backend Engineer | Remote, US & Canada

Cube•Reston, VA

4d•Hybrid

About The Position

Cube is hiring a Staff Back-End Engineer to provide technical leadership across its engineering organization. This strategic individual-contributor role will shape architectural patterns, infrastructure standards, and engineering practices as the platform grows. Reporting to an Engineering Manager, the engineer will work across multiple problem areas and partner with Engineering, Product, and Customer Success to turn ambiguous business needs into robust distributed systems for financial workflows. The role owns complex initiatives end to end, influencing infrastructure, deployment strategies, observability, and long-term system health. It includes building scalable foundations, reusable abstractions, and internal frameworks that help the engineering organization deliver reliably and efficiently. The position requires working onsite at Cube’s New York office Tuesday through Thursday. The technology stack includes Python (Django and DRF), MySQL, ClickHouse, Redis, RabbitMQ, Celery, AWS deployed via CDK, CI/CD automation, and JavaScript/TypeScript with React/Redux. The role also touches AI-driven workflows, LLM agents, enterprise integrations, and advanced observability.

Requirements

Typically 10 or more years of professional software engineering experience; exceptional candidates with strong Staff-level impact, ownership, and technical leadership may be considered.
Experience-backed technical judgment in distributed systems and long-term architecture, including designing for years of growth.
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.
Ability to debug complex concurrency challenges, including race conditions, distributed deadlocks, asynchronous failures, and large-scale database performance issues.
Experience with dataframe-based computation tools such as Pandas, Polars, or NumPy for 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.
Experience using AI-assisted engineering workflows, such as Cursor, Claude Code, or similar tools, 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.
Authorization to work in the posted location; immigration sponsorship is not available.

Nice To Haves

Familiarity with FP&A concepts such as trial balances, charts of accounts, fiscal calendars, scenario modeling, and multi-currency workflows.

Responsibilities

Set architectural direction and establish engineering patterns that become the standard across teams.
Design and evolve complex backend systems, including multi-tenant database routing, distributed task orchestration, asynchronous pipelines, and enterprise integrations.
Lead adoption of AI-assisted development practices and production LLM agent systems.
Deliver strategic initiatives end to end, from infrastructure and deployment through monitoring and documentation.
Develop observability strategies involving structured logging, APM tooling, metrics, and production debugging workflows.
Lead technical response during production incidents, including root-cause analysis and long-term remediation.
Mentor engineers, remove technical blockers, and promote psychological safety and continuous improvement.
Improve CI/CD pipelines, testing infrastructure, release processes, and deployment strategies so teams can ship safely and quickly.