Python Developer

Job Summary GrabOn is looking for a highly skilled Python Developer with deep expertise in large-scale web scraping, browser automation, and distributed systems . The ideal candidate will design and maintain high-resilience, fault-tolerant scraping infrastructure capable of operating reliably against modern anti-bot defenses. You will work on distributed, cloud-native scraping pipelines , collaborate on agentic and autonomous systems , and continuously optimize for scale, cost, and reliability . Key Responsibilities Scraping & Automation Design, build, and maintain high-resilience web scraping systems at scale Implement advanced Selenium / Playwright automation (headless, stealth, browser fingerprint control) Handle anti-bot mechanisms , including: IP rotation & proxy orchestration CAPTCHA detection & mitigation Browser fingerprinting and evasion strategies Distributed Systems & Cloud Architect and maintain distributed scraping pipelines using: AWS Lambda SQS EC2 (auto-scaling worker fleets) Build retry-safe, idempotent, and fault-tolerant pipelines Ensure graceful handling of failures, throttling, and partial outages Performance, Monitoring & Optimization Monitor scraping throughput, failure rates, and infrastructure health Debug production issues across distributed workers Optimize AWS cost, latency, and system throughput Agentic & Autonomous Systems Collaborate on agent-based architectures for: Autonomous task execution Decision-making workflows Self-healing data pipelines Engineering Practices Write production-grade Python code (clean, testable, maintainable) Work comfortably in Linux server environments Follow best practices for concurrency, rate-limiting, and queue-based systems Mandatory Requirements (Non-Negotiable) Strong Python expertise (production systems, not notebooks or scripts) Deep hands-on experience in web scraping at scale Expert-level Selenium and/or Playwright knowledge Proven experience with AWS Lambda, SQS, and EC2 Strong understanding of: Concurrency & parallelism Queues and distributed workflows Retries, backoff strategies, and rate limits Comfortable managing and debugging Linux servers & cloud infrastructure