Associate Software Engineer – Web Scraping

Description

SEON is the command center for fraud prevention and AML compliance, helping thousands of companies worldwide stop fraud, reduce risk and protect revenue. Powered by 900+ real-time, first-party data signals, SEON enriches customer profiles, flags suspicious behavior and streamlines compliance workflows - all from one place. SEON provides richer data, more flexible and transparent analysis, and faster time to value than any other provider on the market. We’ve helped companies reduce fraud by 95% and achieve 32x ROI, and we’re growing fast, thanks to our partnerships with some of the world’s most ambitious digital brands like Revolut, Wise, and Bilt.

As an Associate Software Engineer on our web scraping team, you will work on the real-time scraping platform behind SEON's data enrichment products. Our enrichment APIs answer questions about an email address, phone number or IP in real time, which means our data collection runs on the live request path, under a tight latency budget, against a large and constantly changing set of public sources.

This is a role for someone early in their career who wants to go deep on a hard technical problem. You will own real scrapers in production, with a senior engineer as a mentor and structured code review as a default.

You will join the data collection side of the Data Enrichment team, working closely with backend engineers, Product Management and infrastructure specialists. This role reports into the Engineering Manager of the Data Enrichment Crawler Team.

Responsibilities

• Write production-quality, well-tested scraper code in Python that needs little rework after review, including comprehensive unit and integration tests written with minimal guidance.
• Learn the architecture of our collection platform — how scrapers, proxy layer, queues and the enrichment API fit together — and read our design docs and ADRs to build that intuition before you're asked to produce designs yourself.
• Debug issues across a few components with guidance, including problems that originate outside your own code, using our logging, monitoring and alerting tools to investigate.
• Work with our proxy infrastructure: understand selection and rotation, and help recover from blocks.
• Take part in incident response by following established processes and documenting what you find, and learn from every incident you're part of.
• Build depth in reliability engineering: SRE practices, resilience patterns and observability platforms, applied to a system where upstream sources fail constantly and unpredictably.
• Deliver at a steady, predictable pace with minimal back-and-forth on requirements, breaking work into small increments that get reviewed and merged quickly rather than sitting in long-lived branches.
• Understand our build, test and deployment pipeline end-to-end, automate the repetitive manual steps in your own workflow, and raise process friction with concrete suggestions rather than working around it.
• Use an AI coding assistant as a regular part of your workflow, applying verification proportionate to the task and risk, and run small experiments on prompts and tooling — documenting what works and what doesn't so teammates can reuse it.
• Take part in code review in both directions, and help onboard newer teammates by pairing and reviewing their work as you find your footing.
• What You Bring:
• Around 1–2 years of professional software engineering experience, or a strong portfolio of internships, personal projects or open-source work. Solid Python matters most.
• Some hands-on exposure to web scraping or automated data collection, even if it was coursework or a side project.
• Working understanding of HTTP and networking fundamentals: requests and responses, headers, status codes, TLS at a conceptual level, what a proxy does.
• Comfort writing tests and working in a code-review culture with Git.
• Basic comfort with Docker; willingness to learn Kubernetes on the job.
• Regular use of at least one AI coding assistant, and curiosity about getting more out of it.
• The habit of reading release notes, docs and engineering blogs for the languages and frameworks you use, and asking about unfamiliar patterns rather than copying them blindly.
• Realistic self-assessment on timelines: you check with teammates before committing to a deadline, and you raise blockers with context rather than just flagging that you're stuck.
• Ownership of the outcome rather than the ticket, and a habit of surfacing problems and mistakes early.
• Willingness to argue for the customer's perspective when the technically convenient option would degrade the product.
• Openness to picking up Java/Spring, which is where the platform is heading.
• Strong collaboration and communication skills, adapted to the audience; fluent in English.
• Amazing if You Also Have:
• Any exposure to scraping or browser automation tooling: Playwright, Selenium, Puppeteer, Scrapy, or low-level HTTP clients.
• Any exposure to cloud infrastructure (ideally AWS) or infrastructure as code.
• Familiarity with monitoring tools such as Grafana, Prometheus, Kibana or InfluxDB.
• Exposure to CI/CD pipelines, especially GitHub Actions.
• Any experience with Elasticsearch, Redis or DynamoDB.
• Interest in fraud prevention, trust and safety, or another domain where data freshness is a product requirement.