Senior Software Engineer

Amazon • Bachelor's Degree • Java • Node JS • Python • TypeScript • JavaScript • 28 days ago
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Salary
≈ $28k – $73k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Senior · 5+ years exp
Overview
Company
Impact
Profile match

Amazon

Amazon is an American technology and retail conglomerate founded by Jeff Bezos in 1994 as an online bookstore and headquartered in Seattle, Washington. It operates the world's largest online marketplace together with a global logistics network, physical grocery stores and a third-party seller platform that accounts for most units sold. Amazon Web Services, launched in 2006, is the leading public cloud provider and generates the majority of the group's operating profit, while advertising, Prime Video, Alexa devices and Kuiper satellite broadband round out the business.
amazon.com • HQ: Seattle, United States • Cybersecurity • Information Technology • Data & Analytics • Artificial Intelligence • Streaming & OTT Platforms • Media & Entertainment • Sales & Marketing • Advertising • Marketplaces • Cloud Computing • E-commerce Platforms • 5000+ employees • Est. 1994

Requirements:

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field, with 5+ years of software engineering experience building production systems.
  • Strong proficiency in TypeScript and React for building performant, developer-facing web applications; comfortable owning the full frontend stack.
  • 3+ years of backend development experience with strong proficiency in Java for building scalable REST APIs; working knowledge of Node.js or Python is a plus.
  • Solid foundation in data structures, algorithms, system design, and distributed systems fundamentals.
  • Hands-on experience with observability and CI/CD tooling such as Prometheus, Grafana, Argo CD, or equivalent GitOps-based pipelines.
  • Demonstrated use of AI-assisted development tools (e. g., Claude Code, Cursor, GitHub Copilot, Windsurf) to improve coding efficiency and output quality.

Nice to Have:

  • Experience with MLOps platforms such as MLflow, Weights & Biases, or equivalent experiment and model lifecycle tooling.
  • Familiarity with Kubernetes and containerised environments (Docker, Helm).
  • Prior experience building developer-facing internal platforms, portals, or SDKs.
  • Exposure to the machine learning lifecycle including model training, experiment tracking, inference serving, or LLM deployment.
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