Venkataraman V

Software Engineer @ Google

About

I’m a backend software engineer passionate about building high-scale, distributed systems that power millions of users.With 2+ years at Google Cloud designing data pipelines for 20M+ enterprise users and an Amazon Security internship developing serverless AI-driven security pipeline handling 100K+ events/day, I bring a deep understanding of reliability, scalability, and performance engineering.I graduated with an M.S. in Computer Science at USC (3.9 GPA), I specialize in algorithms, AI-driven infrastructure, and distributed systems. I thrive in teams solving complex technical problems and pushing infrastructure to new limits.My core strengths:- Designing and scaling backend and distributed systems (Java, C++, Python)- Building on GCP and AWS, with expertise in serverless and cloud-native architectures- Developing reliable data pipelines and high-performance storage solutions for complex customer needs- Deep experience in debugging, performance optimization, and production reliability

Country

United States

City

San Francisco Bay Area

Industry

Computer Software

Skill

Networking, Python (Programming Language), Natural Language Processing (NLP), Deep Learning, Data Structures, C (Programming Language), Front-End Development, Backend, Full-Stack Development, Application Programming Interfaces (API), Databases, JavaScript, Systems Design, Storage, Java, Spring Framework, SQL, Guice, C++, Algorithms

Experience

Software Engineer

Google

2026-6 - Present · 4 mos

Sunnyvale, CA

Software Engineer Intern

Amazon

2025-5 - 2025-8 · 4 mos

Seattle, Washington, United States

• Engineered a scalable, fault-tolerant serverless pipeline (AWS Lambda, Bedrock Claude 3.5 Sonnet) classifying 100K+ domains/day with high reliability • Built serverless infrastructure (Lambda, S3, SQS, DynamoDB) with 99.9% uptime, supporting peak load of 1000 domains/sec and scalable parallel execution • Developed a secure human-review dashboard with bulk approval/rejection and domain grouping features, allowing the team to efficiently validate 100+ AI-suggested domains in a 10 minute timeslot • Enhanced backend scoring logic with token-based domain similarity + HTTP metadata, boosting classification accuracy by 30% over baseline

Software Engineer

Google

2022-7 - 2024-7 · 2 yrs 1 mo

Bangalore Urban

• Designed and implemented distributed data processing pipelines for the Business Insights Platform, handling audit usage for 20M+ enterprise users across 50+ applications with scalable, reliable performance • Built an end-to-end export pipeline allowing users to move 180-day data to external storage; deployed to 10K+ subscribing customers • Deprecated legacy ingestion server API, saving 8000 GCUs and 3TiB memory while reducing operational overhead • Refactored 10+ storage systems to enforce EU data sovereignty compliance with accurate location-aware storage rules • Developed backend infrastructure and onboarding workflow APIs for audit event configuration, cutting onboarding time from 2+ weeks to 2 days • Created validation playground for rollout testing, automating 50+ checks across 60+ applications • Designed an accessible fullstack dashboard enabling 100K+ companies to migrate data from Microsoft Teams to Google Chat • Analyzed and designed a dynamic threshold and alerting logic for an intermediate broker system to optimize throughput and reliability under peak loads. • Resolved 300+ production bugs and 30+ customer escalations during on-calls; improved system reliability and latency

Software Engineer Intern

Arcesium

2021-6 - 2021-8 · 3 mos

Hyderabad, Telangana, India

• Led refactoring of monolithic Price Change APIs into microservices, modularizing domain logic to improve maintainability and scalability • Designed and implemented cursor-based pagination reducing API latency by 50% on 10M+ scale financial datasets • Delivered production-ready APIs with 100% test coverage and robust error handling, ensuring high availability