Computer Scientist 2

The Computer Scientist 2 will work closely with engineering teams and leadership to provide architectural expertise, design mentorship, and improve the visibility of cross-team technical initiatives.

Requirements

• B.Tech/M.Tech from a premier institute with 7+ years of experience including a few years in technical leadership with high-performance engineering teams.
• Deep expertise in advanced JavaScript and TypeScript, with a solid understanding of core web technologies and experience in building responsive, elegant, and scalable web applications using modern frameworks such as React, Vue, Angular, etc.
• Strong understanding of HTML5 and CSS3 design principles and techniques.
• Strong backends development experience, with NodeJS, REST APIs, ElasticSearch, Python, SQS, SNS, Step Functions, Kubernets, Elastic Containers or similar tech stacks.
• Experience with Amazon Web Services, with knowledge of AWS Services like Autoscaling, ELB, ElastiCache, SQS, SNS, RDS, S3, Serverless Architecture, AWS Lambda, Amazon API Gateway, Amazon DynamoDB, etc.
• Extensive Knowledge of Web Standards and modern browsers, both at their API level and their internals (JS engines, browser performance, reflow, repaint, shadow DOM, progressive rendering, Service Workers, CDNs, CSS resetting, normalizing, SCSS, etc.).
• Proficiency in building and architecting web apps that seamlessly function across various browsers, including mobile, where distinct performance, resource constraints, and capabilities necessitate polyfills.
• Knowledge of load optimization and cloud deployment strategies, complemented by CI/CD pipelines.
• Familiarity with monitoring systems like Splunk, New Relic, Grafana etc.
• Good knowledge of algorithms, data structures, and distributed system design/implementation, and ability to debug
• Experience with unit, integration and end to end testing
• Maintain and fix parts of production environment
• Willingness to participate in an on-call rotation
• Leverage modern AI tools to significantly improve development velocity and code quality.
• Build agentic workflows for all SDLC flows - test plan generation, code generation, debugging, test automation and incident response post shipping
• Integrate AI capabilities into product features while ensuring deterministic fallbacks, reliability, and performance constraints.
• Design systems that safely incorporate probabilistic AI outputs into production-grade software

Benefits

• Internal Opportunities
• Creativity, curiosity, and constant learning are celebrated aspects of your career growth journey.
• Equitable opportunities for personal growth and development.
• Positive work culture
• Good company benefits and rewards