Summary
Software Engineer with diverse experience spanning AI infrastructure, distributed systems, full-stack development, and cloud-native platforms. Currently building large-scale model deployment and container testing systems at AWS Bedrock, leading production launches for frontier AI models. Previously worked across startups and enterprise environments, delivering scalable backend systems, containerized architectures, and ML-driven applications. Experienced in owning systems end-to-end — from design and automation to incident response and compliance — across AWS-based production environments.
Also I like tinkering with tech and learning new stuff every day. Trying something new — press A or D to play. On mobile, swipe.
Also I like tinkering with tech and learning new stuff every day. Trying something new — hit A or D to play. On mobile, hold either side of the screen.
Experience
Software Development Engineer I
Amazon Web Services (AWS) — Bedrock Infrastructure, Seattle, Washington
Nov 2024 – Present
- Designed and built the Container Testing Automation (CTA) framework for Anthropic models, orchestrating commit ingestion, container escrow, manifest rendering, container spin-up, functional testing, benchmarking, and results/log delivery to external partners.
- Implemented ECS-based testing workflows encapsulating benchmarking and validation logic, abstracted via AWS Step Functions to manage networking, environment isolation, and failure recovery.
- Developed a DynamoDB syncer Lambda to coordinate escrow state across IAD and CMH regions, eliminating race conditions and duplicate notifications in distributed workflows.
- Built a notification aggregation system to publish model metadata (commit ID, compute type, model version) post-escrow, improving cross-account consistency and operational visibility.
- Led multi-region multinode launches for Claude Sonnet 4, Opus 4, and Haiku 4.5, resolving DKMS infrastructure issues and ensuring production readiness across PDX and NRT clusters.
- Executed zero-downtime container upgrades (200K+ token improvements) with rolling deployments, maintaining 100% availability while improving model throughput.
- Automated ECR escrow replication pipelines and designed dynamic configuration safeguards to prevent cross-model conflicts in shared regional infrastructure.
- Designed the CTA database schema and dashboards for real-time container test tracking, improving historical visibility and deployment auditability.
- Improved logging architecture by replacing fire-and-forget log delivery with continuous streaming (Firehose), reducing duplication and accelerating debugging cycles.
- Resolved 120+ Sev2/Sev3 production incidents across H1/H2 2025, root-causing outages and implementing automation to improve response and system stability.
- Ensured FedRAMP compliance through coordinated CVE patching and container version updates across infrastructure layers.
Full Stack Developer
Arkoz.ai, San Jose, California
Aug 2024 – Present
- Developed backend routes for analytics in Flask, enhancing data retrieval and system performance, while implementing Redis caching to reduce response times.
Teaching Assistant / Research Volunteer
San Jose State University, San Jose, California
Jan 2024 – May 2024
- Developed a scale-free Named Data Networking (NDN) simulation utilizing continuous machine learning with an ensemble of classifiers, dynamically optimizing caching decisions based on model freshness.
- Enhanced simulation efficiency by leveraging CuML for GPU-accelerated machine learning and utilized multi-threading to improve handling of simultaneous network requests, boosting Cache-Hit ratio by 20% compared to LCE and decreasing Hop Counts by 15%.
Intern, Full Stack Developer
Arkoz.ai, San Jose, California
Sep 2023 – Dec 2023
- Streamlined deployment on AWS EC2, utilizing Docker and Kubernetes for orchestration, ensuring efficient scalability and reliability.
- Developed a custom chat interface using Next.js, transitioning from a third-party Gradio interface, enhancing user experience and customization capabilities.
- Optimized data handling pipelines by integrating vector databases and established cron jobs for daily data processing, significantly improving application performance.
- Enhanced system monitoring and automated deployment processes by integrating Nginx and Jenkins, and utilizing AWS CloudWatch for real-time monitoring and alerts.
Intern, Full Stack Developer
ScoutBetter, Hyderabad, India
Mar 2023 – Aug 2023
- Led the architectural design and deployment of containerized workflows using Node.js and React, employing AWS Load Balancer, Launch Configurations, and Auto Scaling Groups to ensure high availability and auto-scaling capabilities.
- Developed a Lambda function to offload machine learning tasks such as speech-to-text processing from EC2 instances, enhancing performance and scalability.
- Authored the speech-to-text module utilizing Whisper; created and deployed a custom video conferencing solution leveraging Jitsi.
- Implemented CI/CD pipelines using Azure DevOps for streamlined version control and application deployment, increasing deployment efficiency by over 50%.
Full Stack Engineer
Cognizant, Bangalore, India
Dec 2020 – Jun 2022
- Created Spring Boot APIs for User Management and Authentication, and Flask APIs for data forecasting, reverse proxied using Nginx and integrated with a React frontend for "Resume Parser".
- Developed the Chatchef project using Spring Boot, integrating Redis for caching, RabbitMQ for message queuing, and MinIO for blob storage, which enhanced overall system efficiency and response time by 35%.
- Contributed to the WMOS project as part of the MERN stack development; authored middleware and backend routes in Express.js and utilized MongoDB, enhancing the application communication layer and data processing capabilities.
- Dockerized multiple projects and utilized AWS ECR as the container registry, optimizing Azure Pipelines to streamline the build and deployment processes, which significantly improved deployment frequency and reliability.
- Architected and deployed containerized workflows using Docker and Kubernetes, ensuring high availability and auto-scaling with AWS Load Balancer and Auto Scaling Groups.
- Developed a custom video conferencing solution using Jitsi with real-time monitoring via Prometheus to support horizontal scaling.
- Improved the "Resume Parser" NLP model by training with padded sentences, enhancing prediction quality.
Intern
Cognizant, Pune, India
Dec 2019 – Jul 2020
- Developed an Inventory Management System using Spring Boot and JavaScript with cron jobs to send reports to the user.
Projects
Sily: Real-Time Music Synchronization App
- Architected a cross-platform mobile application enabling real-time music synchronization between paired users, leveraging the Spotify SDK for playback detection and remote control functionality.
- Engineered a robust pairing system using 6-digit unique codes and Firestore listeners to establish low-latency, persistent connections with automatic state restoration upon app restarts.
- Developed a "Sync Engine" featuring master/follower role logic and a takeover mechanism, utilizing atomic operations to manage concurrent state updates and playback conflict resolution.
- Implemented a rigorous testing suite including property-based tests to validate session uniqueness, data consistency, and the atomicity of shared counters within the user dashboard.
GitInsight
- Developed a web app to summarize git commits by scraping data for analysis and storing it in Astra DB, interfaced with GPT-4 for contextual insights.
- Implemented a Dockerized integration of Flask and React, deployed on Render for robust web service operation.
Image Upscaling Using GANs
- Pioneered an image upscaling web application using GANs, with a custom discriminator, developed using Flask for backend and React.js for frontend integration.
- Applied DevOps practices to ensure robust, scalable deployment by containerizing with Docker and managing containers with Kubernetes on AWS EC2.
Multi-Gesture Recognition with LSTM
- Developed an LSTM-based gesture recognition system, increasing classification accuracy by 30% through hyperparameter tuning that involved converting point data into velocity and acceleration.
- Applied EDA and data visualization using Seaborn and Tableau to provide detailed insights into gesture classification efficiency and accuracy.
Database Optimizer with Access Path Analysis
- Architected a high-performance database optimization tool, focusing on efficient index creation and access path analysis to streamline data retrieval operations.
- Devised and implemented sophisticated algorithms to auto-generate optimal access paths for SQL queries, considerably enhancing query performance.
Resume Parser
- Integrated advanced NLP models with Flask and React.js for dynamic resume parsing and efficient data handling.
- Incorporated MinIO for secure resume storage and MongoDB for data management, coupled with analytics and JWT-based user management.
Hindi Text Sentiment Analysis
- Innovated an NLP model leveraging the Naive Bayes Classifier for sentiment analysis of Hindi text, achieving significant accuracy improvements.
- Compiled and annotated a substantial dataset of movie reviews and sentences to train the model.
Vehicle Detection and Tracking
- Developed a vehicle detection and tracking system using Python and OpenCV, employing MOG2 for background subtraction and filtering techniques to enhance accuracy in low-visibility conditions.
- Implemented image processing algorithms to maintain consistent vehicle tracking, significantly reducing noise.
Education
Master of Science in Computer Science
San Jose State University, San Jose, California
May 2024
GPA: 3.91 / 4.00
Relevant coursework: Design and Analysis of Algorithms, Topics in Artificial Intelligence, Reinforcement Learning, Advanced Parallel Processing, Topics in Database (DB2), Computer Communication Systems
Certifications
AWS Solutions Architect: Associate
Stanford: Machine Learning
Duke University: MLOps Specialization
Technical Skills
Languages
- Python
- Java
- C++
- JavaScript
- TypeScript
- C
- Dart
Cloud & Infrastructure
- AWS ECS
- AWS ECR
- AWS Lambda
- Step Functions
- DynamoDB
- S3
- Firehose
- IAM
- VPC
- Kubernetes
- Docker
- Helm
- Jenkins
- Azure
- CloudWatch
- Prometheus
- Grafana
- Firebase
Backend & Frameworks
- Flask
- Django
- Spring Boot
- Express.js
- Node.js
- React.js
- Next.js
- Redis
- MongoDB
- PostgreSQL
- Nginx
- Flutter
AI & Data
- Model Deployment Pipelines
- Containerized Inference
- Performance Benchmarking
- TensorFlow
- NLP
- Vector Databases
- Time Series Analysis
Systems & Concepts
- Distributed Systems
- Event-Driven Architecture
- High Availability
- Multi-Region Deployments
- CI/CD
- Containerization
- Linux/Unix
- Bash
- Observability
- Incident Response
- Fault Tolerance
- Data Structures & Algorithms
Contact
Seattle, WA