Software Engineer E-Commerce

Sumeet Suryawanshi

É 867-***-**** *.*.************@*****.*** LinkedIn GitHub

HackerRank Publication

PROFESSIONAL SUMMARY

Software Engineer with experience designing cloud-native, full-stack systems across e-commerce, edtech, and AI domains. Proficient in Java, Python, TypeScript, and AWS, with a strong foundation in microservices, observability, and CI/CD automation. Led and delivered high-impact features like predictive inventory engines, LLM-based email generation, and real-time alerting systems—driving measurable gains in availability, fulfillment, and engagement. Skilled at balancing fast-paced development with infrastructure reliability, and passionate about leveraging ML and AI, privacy tech, and distributed systems to solve complex real-world problems. I enjoy building things that matter—and learning something new every step of the way. EXPERIENCE

Software Engineer Dawgzonline Mumbai, India Jan-2022 to Feb-2023

(Next.js, React, SCSS, Node.js, TypeScript, Express, GraphQL, MongoDB, DynamoDB Sanity CMS, AWS Lambda, S3, Docker, GitHub Actions, Redis)

• Built StockGuard, a prediction engine that flagged stale reservations using historical cancellation trends. Leveraged Redis keyspace notifications to monitor lock expirations and auto-release idle inventory—boosting stock availability by 18% and improved order fulfillment.

• Built a self-serve onboarding service to provision vendor-specific Lambda APIs, DynamoDB tables, and CloudWatch alarms using declarative CDK. Reduced partner integration time from ~3 days to under 1 hour and improved consistency across environments.

• Engineered PromoPilot, a GitHub Actions–driven deployment system for flash sales that batch-deploys time-bound Lambda functions with isolated configs. Supported parallel rollout for 50+ dynamic promo services and cut production misconfigurations by 35%.

• Implemented NotifyNow, a restock alert system using SNS + SQS to message subscribed users when high-demand SKUs were replenished. Reclaimed $18K+/month in previously lost orders and increased returning user engagement.

• Resolved frequent stale-stock bugs by building a cache invalidation pipeline with Redis pub-sub + TTL sync, replacing interval-based logic with event-driven invalidation. Held cache accuracy at > 95% and eliminated over-selling during promotions.

• Developed SwiftStock, a just-in-stock fulfillment microservice using DynamoDB Streams and Lambda to track real-time SKU movement across 3 warehouses—reduced delayed shipments by 14% and improved ETA accuracy on product pages.

• Orchestrated end-to-end inference deployment using AWS CDK to version ML model artifacts in S3, expose Flask APIs via API Gateway, and attach Redis for caching—enabled sub-140ms personalized product recommendations at 30K+ daily scale.

• Integrated a pre-trained LLM into the internal email tooling pipeline using Hugging Face Transformers—to auto-generate 30+ promotional emails—accelerated content creation by 3x while preserving brand tone via prompt templates and validation rules.

• Configured a dynamic log-level API for production, enabling real-time debugging without redeployments and cutting incident resolution time by over an hour—especially valuable in complex, distributed services. Software Developer Intern YHills Pune, India Dec-2021 to Jan-2022

(React, Node.js, AWS CDK, Markdown, Git, GitHub, AWS CloudWatch, AWS Step Functions, AWS EventBridge, DynamoDB, S3)

• Developed a Git-powered CMS interface with version-controlled Markdown previews and schema validation hooks—enabled instructors and marketing teams to publish content safely without engineering involvement.

• Built a self-service deployment interface for curriculum managers to validate course changes via dry-run previews and preflight schema checks—cut QA cycle time by 70% and eliminated over 50% of failed content pushes.

• Automated post-publish workflows using EventBridge and Step Functions to trigger content indexing, student notifications, and cache refreshes—reduced post-deploy latency from ~8 minutes to under 90 seconds.

• Used AWS CDK to provision tier-specific CloudWatch dashboards for tracking engagement anomalies, content access failures, and API bottlenecks—standardized observability across NA (North America), EU (Europe) and FE (Far East) consistent ops visibility. Web Developer Intern Sparue Private Limited Hyderabad, India Sept-2021 to Dec-2021

(Node.js, Express, React, GraphQL, MongoDB, Redis, Docker, GitHub Actions, Socket.io, IMAP, CloudWatch)

• Redesigned a manual support inbox workflow by building InfraFlow, a Node.js microservice that parsed high-volume IMAP email traffic, applied GraphQL-based rules to auto-categorize support requests (“tickets”), and stored structured metadata in MongoDB—cut triaging time by 80% and ensured 100% SLA adherence.

• Built an internal alerting layer using Redis pub-sub for backend service coordination and Socket.io to stream real-time server health events to a live dashboard—cut detection-to-response time from 5 minutes to under 30 seconds.

• Dockerized full-stack React–Node.js platform—including internal tools, support services like InfraFlow – using ECR layer caching. Reduced image size by 60% —using multi-stage builds, cut CI build time by ~40%, and improved deployment consistency across environments.

• Established and led a logging/metrics optimization initiative and process during AWS migration—standardized logs, removed redundant code, cutting noise, improving debuggability, and reducing CloudWatch costs by $1,200/month. SKILLS

• Languages / API’s: Java, Python, C++, C, C#, XML, JSON, JSP, C, Unix, Bash, Data structures and Algorithms, OOPS, Mathematics.

• Databases / Scripting: MySQL, Google Firebase, MongoDB, Postgres SQL, OracleDB, Linux (Shell), Redis (TTL, pub-sub), distributed storage.

• Web Technologies: JavaScript, TypeScript, REST API, ReactJS, NodeJS, Express, Flask, Spring Boot, PHP, NextJs, MERN, Angular, JMS, SOAP, Unit Testing, full-stack, Gradle, npm, Socket.io, Servlets, EJB, gRPC, JDBC, Redux, Collections, Hibernate, Junit, Socket.io, Agile.

• Cloud & DevOps: AWS (Lambda, S3, API Gateway, DynamoDB, CDK, SNS, SQS, Step Functions, CloudWatch, ECR), Git, GitHub Actions, Jenkins, Azure, Terraform, Ansible, HashiCorp Vault, CI/CD pipelines, integration testing, observability, monitoring, Kubernetes, Docker, Kafka.

• Machine Learning & Data Science & AI: Hugging Face Transformers, TensorFlow Lite, PyTorch Mobile, Scikit-learn, OpenCV, ResNet, LSTM, Bayesian models, Pandas, NumPy, Matplotlib, SciPy, EDA, k-fold C, Pandas, Matplotlib, NumPy, SciPy. EDUCATION

• Arizona State University, Tempe, Arizona Master’s in Computer Science Software Engineering. Aug - 2023 to May-2025 GPA - 3.70

• Savitribai Phule Pune University, India Bachelor’s in Computer Science and Engineering. Jun - 2019 to Jun-2023 GPA - 3.80 PROJECTS - https://github.com/IMSUMEET

• Privacy Beacon Tracker App SENSAI - Built a cross-platform UWB/BLE scanner (Flutter + CoreBluetooth + ARKit) with PyTorch-Mobile– powered LSTM + Bayesian fusion pipeline and gRPC threat-intel backed by TFLite CNNs and Transformer-based mitigation

• Distributed Video Processing and Facial Recognition Pipeline - Designed a serverless, multi-stage face-recognition pipeline (AWS Lambda, FFmpeg, OpenCV, ResNet-34) with Dockerized inference on ECR, reducing latency to < 2s for 100+ videos.

• Animegram - Developed an Instagram-like app using TanStack Query, Docker, and Argon2 hashing—boosted API efficiency by 40%.

• Semantic Web Crime Ontology - Built an RDF-backed crime analytics platform using NYPD/LAPD datasets for semantic geospatial analysis

• Employee Turnover Prediction System - Built a Flask–React ML platform achieving 92% predictive accuracy via k-fold CV; reduced UI interaction time by 20% with a streamlined frontend and published findings after surveying 100+ papers ACHIEVEMENT

• Won a prize for the most innovative project at ‘SunHacks’ at Arizona State University.

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