Venkatnarayan G

Software Engineer

Seattle, Washington, United States4 yrs 11 mos experience
AI EnabledAI ML Practitioner

Key Highlights

  • Reduced processing latency by over 40%
  • Achieved $2M in annual OPEX savings
  • Built scalable backend systems for cloud infrastructure
Stackforce AI infers this person is a Backend-focused Software Engineer with expertise in Cloud Infrastructure and Automation.

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Skills

Core Skills

Back-end OperationsBack-end Web DevelopmentLinuxMachine LearningGit

Other Skills

TypeScriptReactJavaAWS internal toolsPythonCC++RivALHIL systemsdiagnostics toolingNVHMicroservicesMongoDBFastAPIDocker

About

Software engineer focused on building scalable backend systems, distributed architectures, and automation for cloud infrastructure. At Amazon Web Services, I work on services that support global infrastructure operations, where reliability and efficiency have direct impact at scale. Recent work has reduced processing latency by over 40%, simplified operational workflows, and delivered measurable compute cost savings through system-level improvements. I've built microservices that handle high-throughput workloads with low-latency guarantees, and led initiatives to improve visibility and resilience across production systems. I approach problems with curiosity, deep technical reasoning, and a strong bias for simple, maintainable solutions. I care about systems that behave predictably in failure conditions and remain easy to operate as they grow. Earlier experience includes embedded platforms in the automotive space and applied machine learning for security detection. These domains taught me to work across abstraction layers, debug complex system behavior, and prioritize correctness under pressure. I focus on engineering that balances performance, durability, and long-term simplicity. My interests include distributed platforms, infrastructure tooling, developer experience, and automation that reduces friction at scale. Technical Skills • Languages: Python, Java, C++, Rust, TypeScript • Cloud & Infrastructure: Amazon Web Services (EC2, Lambda, ECS, S3, CloudWatch), Docker, Kubernetes • Architecture: Microservices, distributed systems, observability, fault-tolerant design • DevOps & Tooling: CI/CD pipelines, distributed tracing, system diagnostics, performance profiling • Machine Learning: Detection systems, ML pipelines, automation workflows Looking forward to connect, learn and grow

Experience

4 yrs 11 mos
Total Experience
1 yr 5 mos
Average Tenure
8 mos
Current Experience

Amazon web services (aws)

Software Engineer

Sep 2025Present · 8 mos · Greater Seattle Area · On-site

  • Supporting AWS Data Center Automation by improving internal tools that enhance operational reliability and streamline engineering workflows.
  • Fixed frontend and data-handling defects in operational dashboards, ensuring accurate operator readiness and permission visibility for data center teams
  • Partnered with ML/AI teams to integrate data and implement deterministic sorting, reducing ambiguity for operators during task assignment and reviews
  • Reviewed designs and refactored legacy frontend components, simplifying operator workflows and reducing future defect risk
  • Identified and resolved integration test failures caused by data contract mismatches, preventing incorrect data propagation to production dashboards
  • Restored expected system behavior during a Sev2 production incident by tracing logs, validating backend data paths, and deploying a targeted fix
  • Detected edge-case automation failures during Gameday fault injection, surfacing reliability gaps before customer-facing impact
  • Documented recurring failure patterns and debugging steps, decreasing issue reproduction and diagnosis time for partner teams
  • Tech: TypeScript, React, Java, AWS internal tools
TypeScriptReactJavaAWS internal toolsBack-end OperationsBack-End Web Development

Rivian

Software Engineer

May 2025Aug 2025 · 3 mos · Palo Alto, California, United States · On-site

  • Supported Rivian’s Reliability and Diagnostics team by automating HIL tests and improving diagnostic workflows for embedded systems.
  • Automated HIL test execution using Python and RivAL to validate embedded diagnostics
  • Built reusable diagnostic scripts and signal-processing utilities to increase regression coverage
  • Identified subsystem issues under dynamic NVH conditions to support earlier failure detection
  • Enabled secure remote access to Vehicle Health Monitoring HIL rigs for global test automation
  • Validated real-time sensor–actuator behavior in collaboration with reliability and simulation teams
  • Tech: Python, C, C++, RivAL, OS, HIL systems, diagnostics tooling, NVH
PythonCC++RivALHIL systemsdiagnostics tooling+3

Binghamton university

Computer Science Graduate Student

Jan 2023Jan 2025 · 2 yrs · New York, United States · On-site

  • Projects
  • BingB Chatbot
  • Multithreaded Web Server with Proxy Server
  • Multilevel Feedback Queue (MLFQ) Scheduling in Xv6 OS
  • Copy-on-Write Implementation in Xv6 OS
  • Get2Bing Web Application
  • WebUP? (Android UDP Pinger)
  • Android Malware Analysis
  • 5G NR Network Security and Vulnerability Analysis
CMicroservices

Vodafone

Software Engineer

Jan 2021Jan 2023 · 2 yrs · Bengaluru, Karnataka, India · On-site

  • HCLTech
  • Developed an application using Python and MongoDB, reducing base station power wastage by 68%
  • Achieved $2M in annual OPEX savings via a Python-based energy optimization tool using Cisco SON
  • Built a CI/CD-integrated test framework, cutting testing time from 14 days to 1 hour
  • Led R&D for a flexible O-RAN platform using FastAPI, Docker, Kubernetes, and Rancher
PythonMongoDBFastAPIDockerKubernetesMachine Learning+1

Education

Binghamton University

Master of Science - MS — Computer Science

National Institute of Technology Warangal

Bachelor of Technology - BTech

Jan 2017Jan 2021

GEMS Education

Grade 3-12

Jan 2007Jan 2017

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