Backend Engineer - Data Acquisition (Anti-Scam 2B Team)

Gogolook is a TrustTech company with the mission of "Build for Trust." We build AI-powered products - including Whoscall and Watchmen - that protect hundreds of millions of people and businesses from fraud across Asia-Pacific. Our work sits at the intersection of real-time threat intelligence, data engineering, and enterprise-grade SaaS, and it has real-world stakes: the systems you build will directly determine how fast we can detect and neutralize emerging scam threats.

Role Overview

As a Backend Engineer (Data Acquisition) on the Anti-Scam 2B team, you will own and evolve Gogolook's web data acquisition infrastructure - the backbone that powers our Watchmen brand-protection platform. You'll tackle one of our most critical cost-and-capability challenges: replacing high-cost crawler dependencies with an in-house, scalable, cost-efficient crawling fleet that supports real-time social media monitoring, fraud signal extraction, and threat intelligence enrichment.

This role requires deep crawler expertise and a high degree of independence. You will be the team's go-to expert for data acquisition, working closely with backend engineers, data engineers, and product to shape how we collect, process, and operationalize web intelligence at scale. As the team's first dedicated crawler specialist, you'll have the ownership to set the technical direction and build the capability for long-term scale.

What You'll Work On

In the next 6-12 months, your primary mission will be to replace the existing Watchmen crawler dependencies with a purpose-built, in-house crawling system, dramatically reducing operational costs while improving coverage, freshness, and reliability. Beyond the initial migration, you'll expand crawler coverage to new social platforms and fraud signals, build extraction pipelines that feed into Gogolook's fraud database, and develop reusable crawling infrastructure that serves the company's broader B2B product roadmap and AI/ML detection initiatives.

Responsibilities

• Design, build, and operate scalable, production-grade web crawling infrastructure across social media platforms and public web sources, with a focus on reliability, coverage, and cost efficiency.
• Build resilient collection mechanisms, including headless browser orchestration, IP rotation, scheduling, rate limiting, retry logic, observability, and automated recovery.
• Own data extraction and normalization pipelines that transform crawled content into structured fraud signals for downstream detection and database enrichment.
• Drive the migration from external crawler dependencies to cost-efficient in-house solutions, continuously optimizing infrastructure cost, performance, and architecture.
• Collaborate with backend, data, and product teams to integrate crawler outputs into Watchmen and broader fraud intelligence systems, while proactively improving technical quality and reducing technical debt.
• Partner with Legal and Security to ensure data acquisition practices meet applicable compliance, privacy, retention, and auditability requirements.

Minimum qualifications

• Demonstrated production experience building crawlers at scale - including resilient collection techniques, headless browser orchestration (Playwright, Puppeteer, or equivalent), large-scale URL scheduling, and structured data extraction pipelines.
• Deep proficiency in HTTP and TLS protocol internals - including the ability to analyze bot-detection signals and build resilient collection systems against mechanisms.
• Proficiency in Python and JavaScript.
• Solid experience with AWS cloud infrastructure (EC2, ECS, Lambda, S3, or equivalent).
• Strong ownership mindset - operates independently, raises issues proactively, and drives work to completion with minimal supervision.
• 3-7 years of software engineering experience with a focus on data acquisition or backend systems.
• Hands-on experience using AI coding agents (e.g., Claude Code, Codex) as part of daily development workflow.
• Effective collaborator across functions and comfortable working in a hybrid environment.
• Working proficiency in written English, with the ability to read and write technical documentation.

Preferred qualifications

• Production experience crawling social media platforms (e.g., Meta ecosystem: Facebook, Instagram, Threads and Google ecosystem: Google Ads, YouTube) or news, forum, and e-commerce sites.
• Background in cybersecurity, threat intelligence, fraud detection, or brand-protection domains.
• Experience using LLMs for structured data extraction - e.g., applying GPT or Claude to parse unstructured crawled content into actionable fraud signals.
• Prior experience driving cost reduction through in-house crawler replacement, proxy architecture redesign, or crawl efficiency optimization.
• Experience with residential proxy networks, datacenter proxy fleet management, or custom IP rotation infrastructure.
• Familiarity with data engineering patterns: ETL pipelines or streaming data.
• Hands-on experience with distributed task scheduling and queueing systems (e.g., Celery, RabbitMQ, SQS, or equivalent).