BackEnd Engineer: Experiments

About the Team

The Experiments team at Constructor builds an experimentation platform: traffic allocation, exposure logging, metric computation, statistical analysis, and a UI for launching experiments and interpreting results. It’s used both internally and by customers running experiments on production traffic.

We’re scaling customer experimentation usage and investing in making experiments faster, more reliable, and easier to interpret. Unlike boxed experimentation tools, our platform has to support a wide range of customer integrations, traffic patterns, and industry constraints — which makes the engineering problems unusually real-world and high-leverage.

Team: 3 Software Engineers, 1 Data Analyst, an Engineering Manager, and a Product Manager.

The Role

This is primarily a backend role (Python services + data-heavy systems). You’ll occasionally work in the Dash UI and contribute to Spark jobs, but those are not the main focus. We care about correctness, observability, and product usability more than complex infrastructure.

Tech: Python, FastAPI, PostgreSQL, Plotly Dash, PySpark/Databricks, AWS, CloudWatch, Sentry

(Spark work is ~5–10% — we don’t expect you to be a data engineer or own the data platform.)

What you’ll do

• Build and maintain backend services for experiment assignment, logging, and report generation

• Improve scalability, performance, and reliability of experiment reporting pipelines

• Add product-facing features to the UI to help users launch experiments and interpret results

• Take technical ownership of projects: shape solutions, break down work, and drive execution with the team

• Participate in a weekly on-call rotation (investigating occasional issues and answering internal questions)

You’ll collaborate closely with Search/Recommendations engineers, ML/DS partners, and customer-facing teams when needed. This role does not require frequent direct customer calls.

Requirements

Must-have

• Strong experience building and owning production backend services in Python

• Experience with monitoring, alerting, and debugging user-facing systems

• Strong SQL skills and confidence working with data-heavy systems (metrics, logging, analytics)

• Ability to ship maintainable software (tests, code review, incremental delivery)

Mindset

• You take ownership: you can turn ambiguous problems into an executable technical plan

• You care about building systems people trust and rely on

Nice-to-have

• Experience with experimentation systems, metrics platforms, or A/B testing workflows

• Experience with PySpark and/or Databricks

• We don’t expect you to already be an expert in experimentation methodology — but we do expect strong backend fundamentals and the ability to ramp up effectively in a data-heavy domain

Location / Time Zones

• We’re a distributed team. Preferred time zones are UTC+1 to UTC+7, but we’re flexible