Senior Backend Engineer

About the role

This role focuses on designing, building, and operating backend services and APIs using Python and Django, supported by Postgres and Redis. The work involves modeling data, managing migrations, and optimizing queries and caching to handle high-volume workflows. A key aspect is evolving API contracts with frontend teams, ensuring interfaces are clear, versioned, and resilient to change.

The position requires improving system reliability and performance through strategies like timeouts, retries, and rate limits. It also involves implementing secure, multi-tenant patterns, including authentication, permissions, and auditability. The engineer will contribute to the overall testing strategy, error handling, and graceful failure modes, while also investigating production issues and translating insights into preventative measures.

Success in this role means taking ownership of outcomes rather than just tasks, refining scope, and suggesting trade-offs to deliver value efficiently and safely. The engineer will engage with the open-source community to understand user needs, participate in architectural discussions, and mentor teammates, thereby improving codebase patterns and overall developer experience.

The listed salary range for this full-time senior backend engineer position is between $115,000 and $195,500 USD.

Skills that matter here

• Python: This role requires designing and operating backend services and APIs primarily using Python.
• Django: The core backend framework for developing services will be Django.
• Postgres: Postgres will be used for data modeling, migrations, and query tuning within the services.
• Redis: Redis will be utilized for caching and managing background jobs in high-volume workflows.
• OpenAI API: Familiarity with the OpenAI API is listed as a skill, suggesting potential integration with AI models.
• Kafka: Experience with Kafka is beneficial for handling streaming data and background processing.

Who this role suits

• You are a senior individual contributor who prioritizes delivering value and owning the outcomes of your work.
• You possess a strong product sense, guiding your technical decisions based on real-world usage and feedback.
• You excel at clear, concise written communication for technical documentation and decision-making.
• You are proactive in engaging with user communities and enjoy mentoring colleagues.

From the employer

• Design, build, and operate backend services/APIs in Python/Django with Postgres/Redis.
• Own outcomes, not tasks: refine scope, suggest trade-offs, and land increments that deliver value quickly and safely.
• Model data and author migrations; tune queries and caching; manage background jobs/queues for high-volume workflows.
• Evolve API contracts with FE; keep interfaces clear, versioned, and resilient to change.
• Improve reliability and performance (timeouts, retries, idempotency, rate limits, pagination, backpressure).
• Implement secure, multi-tenant patterns: auth, permissions/RBAC, auditability, and safe data boundaries.
• Contribute to testing strategy (unit/integration), error handling, and graceful failure modes.
• Partner with Support to investigate production issues and turn learnings into fixes and prevention.
• Engage with our open-source community (issues, discussions) to understand real-world needs and improve developer experience.
• Participate in architecture discussions and code reviews; mentor teammates and improve patterns across the codebase.

• Senior-level experience shipping production backends in Python/Django (or a close equivalent) and SQL.
• Strong product sense: you’ve made scope/trade-off decisions and iterated based on real-world usage and feedback.
• Depth in REST API design, relational modeling, migrations, and performance tuning.
• Experience with background processing/queues (e.g., Celery/RQ/Kafka-backed workers) and operational concerns.
• Clear written communication at a Senior IC level—concise RFCs/PRDs, actionable reviews, and crisp decision records.
• Nice to have: GraphQL familiarity; Kafka/streaming; Spark/BigQuery; security/compliance exposure; multi-region architectures.