Backend Engineer - Extensions
Fundamental4 months ago
Remote, EMEASenior
Responsibilities
- Own the reliability, performance, and scalability of Extensions capabilities.
- Design and build efficient, reproducible, and observable distributed workflows.
- Collaborate with data scientists to translate requirements into engineering decisions.
- Identify and resolve performance bottlenecks affecting latency and throughput.
- Contribute to architectural decisions for integrating Extensions with the NEXUS backend.
- Write clean, well-tested Python code and uphold backend engineering quality standards.
- Contribute to engineering documentation and backend development best practices.
Requirements
- 5+ years of backend engineering experience with a strong focus on Python.
- Deep knowledge of Python and the ability to write clean, idiomatic, well-tested code.
- Experience designing and operating distributed systems at production scale.
- Strong understanding of concurrency, task execution, and workflow orchestration patterns.
- Experience building reproducible, observable, and debuggable production systems.
- Ability to collaborate with non-engineering counterparts and translate complex requirements into reliable implementations.
- Experience with workflow orchestration systems such as Temporal, Dramatiq, or Celery is preferred.
- Familiarity with ML infrastructure, data science collaboration, high-throughput data processing pipelines, Kubernetes, container-based deployment, or Python performance optimization is preferred.
Benefits
- Competitive compensation with salary and equity.
- Comprehensive health coverage for employees and dependents.
- Paid parental leave for all new parents, including adoptive and surrogate journeys.
- Relocation support for employees moving to an office location.
- Mission-driven, low-ego culture emphasizing diversity of thought, ownership, and bias toward action.
Tech Stack
Categories
About Fundamental
Fundamental builds NEXUS, a large tabular AI model and platform for enterprise decision-making on structured data, delivered with deployment support. It sells to large companies, including Fortune 100 firms, through software licensing and forward-deployed data science services. Founded in 2024 by former DeepMind engineers and headquartered in San Francisco, the company is expanding industry use cases such as oil and gas, where it supports predictive analytics and operational planning.