Vaishnav Manoj

Software Engineer

Bengaluru, Karnataka, India7 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in building scalable backend systems and cloud infrastructure.
Proficient in generative AI and quantum computing technologies.
Strong collaboration skills with cross-functional teams.

Stackforce AI infers this person is a Backend-focused Software Engineer with expertise in Cloud Computing and AI technologies.

Contact

Skills

Core Skills

Backend Web DevelopmentCloud ComputingGenerative AiUser Experience (ux)Quantum Computing

Other Skills

Server SideRepresentational State Transfer (REST)AWS CDKLambdasEventBridgeSQSRDSSNSEC2Step FunctionsReact NativeLangChainLLMsPineconeQiskit

About

my little corner of the internet: https://vaishnav.one Deeply interested in building scalable systems, backend architectures and all things infrastructure. Check out my GitHub: https://github.com/vaishnav-mk And yes, the banner is a compact version of my excalidraw.com page :P

Experience

7 mos

Total Experience

7 mos

Average Tenure

Current Experience

Cloudflare

Software Engineer Intern

Feb 2026 – Present · 3 mos · Bangalore Urban, Karnataka, India · On-site

worker on workers, working on workflows; everyone's beta tester and complainer

Server SideRepresentational State Transfer (REST)Backend Web DevelopmentCloud Computing

Hyperverge

Software Engineer Intern

Sep 2025 – Jan 2026 · 4 mos · Bangalore Urban, Karnataka, India · Hybrid

pipelines, playwright, gitlab runners, sharding and a bunch of other things

Emendoai

Software Engineer Intern

Dec 2024 – Aug 2025 · 8 mos · San Francisco Bay Area · Remote

RAG Optimization: Reduced average response time from 20s to 3.4s using LangChain, LLMs and Pinecone
AI Assistant: Built a context-aware assistant that adapted to user behavior and preferences without disrupting UX
Cloud Infrastructure: Developed scalable backend systems using AWS CDK with Lambdas, EventBridge, SQS, RDS, SNS, EC2 and Step Functions
Frontend: Improved performance and reliability of a React Native app using targeted Sentry-based profiling
Generative AI: Designed and implemented real-time RAG pipelines for production-grade generative AI features
Performance Tuning: Identified and resolved full-stack bottlenecks to improve overall system latency
Monitoring & Debugging: Set up logging and alerting pipelines for rapid error detection and resolution
Collaboration: Worked with cross-functional teams across research and engineering to deliver production-ready systems
Product Thinking: Helped shape features aligned with user goals, technical constraints and long-term product vision

Server SideRepresentational State Transfer (REST)AWS CDKLambdasEventBridgeSQS+10

Indian institute of science (iisc)

Research Intern

May 2024 – Dec 2024 · 7 mos · Bangalore Urban, Karnataka, India · On-site

Collaborated with IBM researchers to optimize quantum circuit execution and noise model support, contributing to two publications (CCGRID 2025, HiPC 2024)
Built a gRPC service to offload quantum experiments, enabling scalable workflows with GPU simulations, custom noise models and AWS Braket integration
Developed custom noise model support and integrated multiple quantum backends; implemented QXFaaS workflows with AWS, Azure and S3
Automated AWS and Azure resource provisioning (Lambdas, Step Functions, ECR), reducing ops overhead with custom cleanup tooling
Integrated SQS and Azure Queues for real-time monitoring and streamlined XFaaS workflow management; automated dag_benchmark.json generation
Technologies: Qiskit, gRPC, AWS Braket, S3, Azure, Amazon SQS, Azure Queues, Python

QiskitgRPCAWS BraketS3AzureAmazon SQS+4