Gaurav Baser
Software Developer
7+ years exp
4+ years ML exp
SQL
TypeScript
C#
Node JS
Go
JavaScript
Java
Python
Security & Auth: 5/10
API Design: 4/10
Data Layer & Database: 4/10
Active 7 days ago
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Overview
Technical skills
Timeline
Roles
Overview
Middle-level Go API engineer focusing on building REST endpoints, auth flows and MongoDB-backed services with practical test coverage and token lifecycle management. The strongest proven skill is implementing authentication and token lifecycle, demonstrated in utils/token_util.go and controllers/user_controllers.go. There is limited evidence of large-scale distributed systems design, advanced performance tuning, CI/CD or infrastructure-as-code practices in public code.
Technical skills
SQL
TypeScript
C#
Node JS• Middle
Go• Middle
JavaScript• 7y+
Java• 3y+
Python• Junior
C#
.NET
Node JS
Bcrypt
Axios
Dotenv
Go
Gin
Java
Spring MVC
Hibernate• 3y+
Maven• 3y+
Spring Boot• 3y+
Spring Data JPA• 3y+
Python
Django
FastAPI
Databases
MySQL
PostgreSQL
MongoDB
Apache Kafka
RabbitMQ
AI/ML
Gemini
LangChain
Copilot• 4y+
ChatGPT• 3y+
Embeddings• 3y+
LLM• 3y+
Claude
Frontend
GraphQL
React.js
Redux
Vite
Vue.js
PostCSS
Bootstrap• 7y+
JQuery• 7y+
Angular• 4y+
Next.js• 4y+
Tailwind CSS
DevOps
Amazon EC2
AWS Lambda
Bitbucket
CI/CD
Docker Compose
GCP
GitLab CI
Jenkins
Nginx
WebSockets
CI/CD
Rest API• 7y+
AWS
Docker
Git
GitHub Actions
Kubernetes
Design
Adobe XD• 7y+
Figma• 7y+
QA
Cypress
Mocha
Postman
Pytest
Selenium
Jest
Swagger
Mobile
Clean Architecture
JUnit
Web3
Ethereum
Web3.js• 4y+
Cybersecurity
GDPR• 4y+
SonarQube
Timeline
Software Developer
•
Middle
SAS Institute Inc.
•
Full-Time
Developed distributed forecasting services using Go and Python for large-scale time-series processing on AWS. Refactored backend components with Clean Architecture and improved unit test coverage, while modernizing a React + TypeScript frontend with Tailwind CSS and Jest-driven testing. Implemented and standardized REST APIs with FastAPI and Swagger/OpenAPI, and consolidated microservices into a Docker and Kubernetes-based architecture. Built event-driven communication using Kafka and RabbitMQ and improved issue resolution and onboarding through documentation and Jira-based tracking.
Python
FastAPI
Swagger
Docker
Kubernetes
AWS
Tailwind CSS
Jest
GitHub Actions
Git
Apache Kafka
RabbitMQ
Claude
Copilot
Jira
SonarQube
LLM
Java Developer
•
Middle
ConsultAdd Inc.
•
Full-Time
Built and maintained Java Spring Boot microservices, using Maven for modular build and dependency management. Designed data-access layers with Hibernate ORM and Spring Data JPA, tuning queries to reduce database round-trips. Integrated Spring AI to add LLM-powered features including prompt handling, embeddings, and chat completion capabilities. Debugged production incidents related to performance, memory, and API reliability to improve stability and uptime.
Java
Spring Boot
Maven
Hibernate
Spring Data JPA
Embeddings
LLMsince 2023
Graduate Assistant
•
Middle
University of Maryland, Baltimore County (UMBC)
•
Full-Time
Supported coursework by grading assignments and exams for 50+ students and providing structured feedback on computer architecture topics. Created a Go CLI utility to automate score aggregation and generate per-student feedback reports, reducing manual grading time. Used AI-assisted tooling such as ChatGPT and GitHub Copilot to draft reference solutions and generate practice questions to improve feedback turnaround.
ChatGPT
Copilot
Ecommerce Developer Intern
•
Junior
Amtrak
•
Internship
Implemented and maintained Amtrak.com frontend features using Angular and AEM, resolving defects through Jira issue tracking. Assisted with GDPR/CCPA compliance work supporting cookie audit workflows using OneTrust. Prototyped a Go-based microservice to aggregate third-party cookie metadata for streamlined reporting and data collection. Used AI-assisted tooling to accelerate defect triage and help generate unit-test scaffolding for Angular components.
Angular
Jirasince 2022
GDPR
Software Engineer Intern
•
Junior
BlockchainCenter.com
•
Internship
Delivered web3 landing page and dashboard MVP prototypes using Next.js and Web3.js while collaborating with UI/UX designers. Implemented a Go backend service to index and serve on-chain transaction data through lightweight REST endpoints. Used GitHub Copilot to speed up Next.js component development and to generate boilerplate for Web3 integrations. Completed features ahead of schedule through agile iterations and provided weekly progress updates to stakeholders.
Next.js
Web3.js
Copilotsince 2022
Web Design Intern
•
Junior
LionOx Master Company
•
Internship
Built client websites on the Wix platform with custom HTML/CSS/JavaScript integrations and supported UX improvements for e-commerce. Redesigned an e-commerce page to improve user engagement via clearer navigation and stronger calls to action. Developed a small Go utility to automate batch image resizing and asset optimization to reduce load times. Used AI-assisted workflows to generate layout variations and marketing content to speed up delivery.
Assistant Software Trainee
•
Junior
Braintree Products Pvt. Ltd.
•
Full-Time
Built responsive cross-browser web interfaces by implementing HTML5, CSS3, JavaScript, jQuery, and Bootstrap layouts based on Figma and Adobe XD mockups. Explored backend fundamentals by creating small REST utilities in Go, gaining experience with Go modules and API design. Applied early AI/ML tooling to automate repetitive image optimization and content-tagging tasks to reduce manual effort.
JavaScript
JQuery
Bootstrap
Figma
Adobe XD
Rest API
University of Maryland, Baltimore County (UMBC)
Master's Degree •
Computer Science
Middle Backend Developer
Confidence: High API Engineer
Middle-level Go API engineer focusing on building REST endpoints, auth flows and MongoDB-backed services with practical test coverage and token lifecycle management. The strongest proven skill is implementing authentication and token lifecycle, demonstrated in utils/token_util.go and controllers/user_controllers.go. There is limited evidence of large-scale distributed systems design, advanced performance tuning, CI/CD or infrastructure-as-code practices in public code.
API Design
4/10
How well APIs are designed
Solid REST handlers with consistent JSON error responses, input validation and cookie-based auth are present, but no explicit versioning, idempotency keys, or advanced pagination/hypermedia patterns.
Evidence
MagicStreamMoviesServer/controllers/movie_controller.go: GetMovies, GetMovieByID, AddMovie handlers with http status codes and validator usage
MagicStreamMoviesServer/controllers/user_controllers.go: RegisterUser and LoginUser handlers returning consistent JSON error objects
Data Layer & Database
4/10
Working with databases
Direct MongoDB usage with projections, filters, updates and context timeouts shows practical data-layer work, but there is no migration history, multi-document transactions, or advanced query tuning.
Evidence
MagicStreamMoviesServer/controllers/movie_controller.go: GetUsersFavouriteGenres uses projection and bson.A parsing
MagicStreamMoviesServer/controllers/user_controllers.go: CountDocuments and InsertOne for uniqueness and creation
MagicStreamMoviesServer/utils/token_util.go: UpdateAllTokens uses UpdateOne with context and bson.M
Scalability & Performance
2/10
Handling load and speed
Some attention to limits and timeouts exists, but there is no caching strategy, queue-based decoupling, connection pooling tuning, rate limiting or measured performance optimization.
Evidence
MagicStreamMoviesServer/controllers/movie_controller.go: GetRecommendedMovies uses findOptions.SetLimit and SetSort for limiting results
MagicStreamMoviesServer/main.go: client.Ping(context.Background()) and deferred Disconnect for basic connection handling
System Architecture
4/10
Overall system structure
Reasonable module separation (controllers, routes, utils, database) and environment-driven config are used, but the architecture remains a single-service API with no multi-service contracts or explicit degradation strategies.
Evidence
MagicStreamMoviesServer/main.go: router setup, CORS config and routes.SetupUnProtectedRoutes / routes.SetupProtectedRoutes
Project layout: controllers/, utils/, database/ folders visible across server codebase
Security & Auth
5/10
Protecting data and access
Good practical auth work: bcrypt password hashing, JWT access and refresh tokens with expiry, validation and cookie security flags are implemented; some secret handling and cookie domain consistency could be hardened further.
Evidence
MagicStreamMoviesServer/controllers/user_controllers.go: HashPassword, LoginUser sets Secure and HttpOnly cookies for access_token and refresh_token
MagicStreamMoviesServer/utils/token_util.go: GenerateAllTokens, ValidateToken and ValidateRefreshToken implementing JWT lifecycle and expiry checks
Reliability & Observability
4/10
Stability and monitoring
Handlers consistently use context timeouts, tests seed and clean a test DB, and the server uses logger middleware; observability and resilience features like structured correlation ids, retries with backoff, or circuit breakers are not present.
Evidence
Multiple handlers (movie_controller.go, user_controllers.go, utils/token_util.go) use context.WithTimeout around DB operations
MagicStreamMoviesServer/controllers/movie_controller_test.go: TestMain seeds test DB, cleans up and disconnects in teardown
Expertise
Go Development• Middle
Backend AI & LLM• Middle
Industries
Media & Entertainment• Middle
Technologies
Go• Middle
Node JS• Middle
Bcrypt
Gin
Axios
Dotenv
Recommendations
- Develop REST APIs with authenticated user flows and integration tests (auth, token refresh, cookie handling).
- Extend backend features that integrate LLMs safely (wrap prompt construction and validate external inputs) using the existing langchaingo call patterns.
- Build MongoDB-backed recommendation or catalog services, leveraging projections and query limits as shown in the recommendation handler.
- Harden production readiness: add secret management, structured logging with correlation ids, and retry/backoff for external calls.
Repositories
The developer's experience in this domain has been verified based on AI analysis of the following repositories:
Junior Frontend Developer
Confidence: Medium UI Engineer
Frontend UI developer (junior) focused on building static marketing and storefront pages with HTML, CSS and Bootstrap. The strongest proven skill is crafting responsive static layouts and visual pages, demonstrated by the Arise-jewels index.html and arisejewelsstyle.css product and banner sections. There is little evidence of component architecture, client-side state management, automated testing, performance measurement or backend/checkout integrations in public code.
UI Component Architecture
2/10
How interface parts are built
Minimal component architecture; static HTML/CSS pages and a copied slider library instead of custom component design or composition.
Evidence
Arise-jewels-Website/index.html: large monolithic HTML page with repeated product blocks (no componentization)
Arise-jewels-Website/css/arisejewelsstyle.css: custom styles and hover rules implementing visual sections rather than reusable components
Responsive & Cross-browser
3/10
Works on all screens and browsers
Responsive layouts rely on Bootstrap and some media queries; basic responsiveness present but no advanced fluid layout techniques or systematic cross-browser feature detection.
Evidence
Arise-jewels-Website/index.html: viewport meta and Bootstrap 4.5 stylesheet link
educational-website/index.html: Bootstrap 5 alpha usage and responsive grid for cards and lists
Performance Optimization
1/10
Speed of the interface
Almost no evidence of deliberate performance engineering or measurement; a minor font preconnect is present but no bundling/code-splitting or metrics.
Evidence
Arise-jewels-Website/index.html: <link rel="preconnect" href="https://fonts.gstatic.com"> (minor performance hint)
Accessibility & Semantics
2/10
Usable for everyone
Some basic accessibility touches (alt attributes, modal aria attributes and navbar toggler ARIA) but no systematic a11y patterns or custom ARIA for interactive widgets.
Evidence
Arise-jewels-Website/index.html: images include alt attributes across the markup
educational-website/index.html: navbar toggler includes aria-controls, aria-expanded and aria-label attributes
State Management & Data Flow
1/10
Managing data in the app
No sign of structured client-side state management or server-state discipline; pages are static with simple forms and no async state handling.
Evidence
educational-website/index.html: static search and register forms without client-side validation or async request handling
UX & Visual Polish
3/10
Look and feel quality
Visually polished static pages and section-level UX (product cards, sliders, CTAs) but lacking edge states, skeletons, undo, or progressive enhancement for slow networks.
Evidence
Arise-jewels-Website/index.html: featured products and product cards with price, heart and cart icons and CTA buttons
Arise-jewels-Website/css/arisejewelsstyle.css: hover effects, layout rules and section styling for banners and feature blocks
Expertise
HTML & CSS• Junior
Industries
Commerce• Junior
Education• Junior
Technologies
Vue.js
Redux
GraphQL
Tailwind CSS
Next.js• 4y+
Figma• 7y+
Angular• 4y+
Bootstrap• 7y+
React.js
JQuery• 7y+
Vite
Adobe XD• 7y+
PostCSS
Recommendations
- Build responsive marketing and small e-commerce frontends - convert designs into accessible Bootstrap-based pages and product grids.
- Implement componentization and modular CSS (BEM/utility classes or a component framework) to reduce duplication across pages.
- Add basic client-side behaviors and state handling for product interactions (small vanilla JS or light framework) and handle edge states (loading/error/empty).
- Introduce lightweight performance checks (Lighthouse) and simple a11y linting (axe or eslint-plugin-jsx-a11y for future SPA work) before deployment.
Repositories
The developer's experience in this domain has been verified based on AI analysis of the following repositories:
Intern AI/ML Engineer
Confidence: Low Generalist
Full stack software developer (early-career) focused on cloud-native web application development with an emphasis on deployment and CI/CD. The strongest proven skill is cloud-native deployment and operations, evidenced by the About-Me README listing AWS, Docker and Kubernetes as core technologies. There is no human-authored production application code, tests, ML artifacts, or experiment/evaluation pipelines present to demonstrate deeper engineering or ML capability.
Model Architecture & Training
How well models are designed and trained
Not evidenced in public code
Data Pipeline & Feature Engineering
How data is prepared for models
Not evidenced in public code
Experimentation & Evaluation
How results are measured and tested
Not evidenced in public code
MLOps & Deployment
How models are shipped to production
Not evidenced in public code
Computational Efficiency
How efficiently computing resources are used
Not evidenced in public code
Research Depth & Innovation
Depth of research and new ideas
Not evidenced in public code
Technologies
CI/CD
MySQL
MongoDB
PostgreSQL
Copilot• 4y+
LangChain
Claude
GCP
Docker Compose
ChatGPT• 3y+
RabbitMQ
Embeddings• 3y+
Gemini
Apache Kafka
LLM• 3y+
Recommendations
- Develop end-to-end cloud-native web applications with automated CI/CD pipelines to showcase production code and deployment patterns.
- Build and publish a sample microservice with Dockerfile, Kubernetes manifests, and documented deployment steps to prove infra ownership.
- Add feature-complete backend APIs with integration tests and sample data migrations (Postgres/MySQL) to demonstrate backend engineering depth.
- If pursuing ML work, publish a small, reproducible experiment with data preprocessing, training loop, and evaluation script to evidence ML engineering skills.
Repositories
The developer's experience in this domain has been verified based on AI analysis of the following repositories: