Backend Engineer - Extensions

Role Description

In this role, you'll develop, and productize data science capabilities that enhance and expand our product performance on real enterprise use cases - working across a wide range of prediction tasks, data types, and business domains. You'll go deep on hard data science problems, collaborate closely with R&D on product capabilities, and ship production-grade work that has a direct impact on Production use cases.

Key Responsibilities

• Own the reliability, performance, and scalability of Extensions capabilities end to end.
• Design and build distributed workflows that are efficient, reproducible, and observable in production.
• Collaborate closely with Data Scientists on the team to deeply understand requirements and translate them into engineering decisions.
• Identify and resolve performance bottlenecks, ensuring Extensions capabilities meet the latency and throughput demands of enterprise deployments.
• Contribute to architectural decisions around how Extensions integrates with the broader NEXUS backend.
• Write clean, well-tested Python code and hold a high bar for code quality across the team.
• Contribute to internal engineering documentation and help establish best practices for backend development within the team.

Qualifications

• 5+ years of backend engineering experience, with a strong focus on Python.
• Excellent Python skills - you write clean, idiomatic, well-tested code and know the language deeply.
• Solid experience designing and operating distributed systems at production scale.
• Strong understanding of concurrency, task execution, and workflow orchestration patterns.
• Experience building systems that are reproducible, observable, and easy to debug in production.
• Ability to work closely with non-engineering counterparts and translate complex requirements into reliable implementations.
• Strong ownership mindset - you drive work end to end and care about outcomes, not just output.

Nice to Have

• Hands-on experience with workflow orchestration systems such as Temporal, Dramatiq, Celery, or equivalent.
• Familiarity with ML infrastructure or experience working alongside data science teams.
• Experience with high-throughput data processing pipelines.
• Exposure to Kubernetes and container-based deployment environments.
• Background in performance profiling and optimization of Python services.

Benefits

• Competitive compensation with salary and equity.
• Comprehensive health coverage for you and your dependents.
• Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys.
• Relocation support for employees moving to join the team in one of our office locations.
• A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action.