Backend Systems
Designing service boundaries, API contracts, and operational patterns for production workloads.
Backend x Distributed Systems x Applied AI
Vishwajeet Kumar
Backend Engineer | Distributed Systems | Applied AI Systems
Focus
Scalable APIs, event-driven services, and AI-assisted product workflows
Approach
Design for reliability first, then optimize latency and operability
Recent Work
Explore production-oriented projects
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ModuleAPI
ModuleDB
ModuleCloud
ModuleAI
Distributed APIs
AI Workflows
Cloud Ready
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Projects Built
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Internships
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LeetCode Problems
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Open Source
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Production Systems
About
Engineering-first product builder
I focus on backend systems that are reliable in production and straightforward to operate. My work combines scalable APIs, distributed service communication, real-time application behavior, and AI-backed features where they provide clear product value. I prefer measurable improvements over hype and prioritize maintainable systems.
Distributed Architecture
Building for concurrency, consistency, and graceful degradation in networked systems.
AI-Assisted Workflows
Integrating retrieval, orchestration, and inference into practical backend products.
Performance
Profiling bottlenecks, tuning hot paths, and improving API and query latency.
Real-Time Engineering
Delivering websocket and event-driven flows with clear state handling and reliability.
Cloud Infrastructure
Deploying and operating backend systems with AWS, containers, and CI/CD pipelines.
Skills
Technology stack I use to ship systems
Backend
Node.jsExpressNestJSFastAPIREST APIsWebSockets
Frontend
Next.jsReactTailwind CSSResponsive UIHTMLCSS
AI / GenAI
LangChainLangGraphRAGVector EmbeddingsPrompt EngineeringQdrant
Databases
PostgreSQLMongoDBRedis
Cloud & DevOps
AWSDockerCI/CDGitHub Actions
Languages
JavaScriptTypeScriptPythonJava
Current preference: pragmatic architecture, explicit interfaces, and operational simplicity.
LeetCode
DSA practice and problem-solving discipline
400+ problems solved with a focus on backend reasoning and interview readiness.
Featured Projects
Production-oriented systems and AI workflows
Monetized Link Shortener SaaS
SourceA read-heavy SaaS backend designed for high-throughput redirects, monetization hooks, cache-aware routing, and API-driven campaign management. The architecture emphasizes low-latency redirects, safe write paths, and clean separation between business logic, persistence, and delivery.
Redis-first redirect path with TTL strategy and fallback database reads
Rate limiting and abuse protection at API and redirect edges
PostgreSQL indexing strategy for high-cardinality link lookups
Node.jsFastAPIPostgreSQLRedisAWS
Autonomous Codebase Engineer (AI Agent)
SourceAn agentic backend workflow that analyzes repositories, plans modifications, and executes scoped engineering tasks with guardrails for reliability and traceability. The system is designed around bounded actions, explicit state transitions, and observability so automated changes remain reviewable and safe.
Multi-step orchestration for analysis, planning, and execution stages
Task state tracking, retry behavior, and deterministic action boundaries
Designed for production-safe automation instead of one-shot prompting
PythonLangGraphLangChainFastAPIPostgreSQL
AI-Powered Code Review System
SourceA backend platform for repository-aware pull request analysis using retrieval and LLM reasoning to deliver contextual quality feedback. It combines embeddings, indexed context retrieval, and analysis workflows that help turn code review into a more scalable engineering process.
RAG pipeline with embeddings and vector search for code-aware context
Async job execution for scalable repository and PR analysis
API architecture designed to integrate with developer workflows
FastAPILangChainRAGVector EmbeddingsQdrant
Real-Time Multiplayer Backend System
SourceA distributed realtime backend supporting concurrent sessions, synchronized state updates, and fault-tolerant session lifecycle management. It focuses on room-scoped communication, race-condition avoidance, and stateless deployment patterns that can scale horizontally.
Redis-based ephemeral state for low-latency room updates
WebSocket event routing with room-scoped communication
Stateless service deployment model for horizontal scaling
Node.jsSocket.ioRedisPostgreSQLAWS
EduIntel AI Career Platform
SourceAn AI-backed career intelligence platform with backend pipelines for resume parsing, ranking, and recommendation services. The platform is built around modular APIs, scored workflows, and retrieval-backed insights that can support future product expansion.
Structured ingestion and scoring pipeline for resume data
Retrieval-powered recommendation workflows with embedding search
Modular APIs for integration with frontend and partner tooling
Node.jsFastAPIMongoDBLLMsVector Embeddings
Experience
Product engineering in real environments
Backend Engineering Intern
PurpleMerit
March 2026 – Present
India
Built and maintained backend modules powering analytics and workflow automation features.
Designed API endpoints and service logic with attention to performance and maintainability.
Integrated AWS-backed infrastructure and deployment processes for stable service delivery.
Improved request handling and data access patterns to reduce latency in key endpoints.
Collaborated in iterative releases with product and engineering stakeholders.
Node.jsExpressPostgreSQLAWSDocker
Software Developer Intern
StuFit Approach Pvt. Ltd.
July 2025 – September 2025
Lucknow, India
Designed and shipped backend services using NestJS and PostgreSQL for user-facing product modules.
Owned modules end-to-end from API design to deployment and production support.
Optimized query paths and endpoint execution, reducing latency in frequently used APIs.
Implemented JWT-based authentication and RBAC patterns for secure service access.
Worked on production debugging, release quality, and reliability improvements.
NestJSPostgreSQLJWTRBACAWSAgile
Education
Formal training that supports the engineering work
Bachelor of Technology — Computer Science & Engineering (AI)
University of Lucknow
Focused on computer science fundamentals, AI specialization, backend architecture, distributed systems, and production software engineering.
Nov 2022 – Jun 2026
CGPA: 8.10 / 10
Computer ScienceAI SpecializationBackend Systems
Senior Secondary (XII)
Manas Convent School, CBSE
Physics, Chemistry, Mathematics, and English.
2021 – 2022
74.2%
Secondary (X)
Manas Convent School, CBSE
Mathematics, Science, Social Studies, English, and Hindi.
2019 – 2020
84%
Open Source
Contributions to production tooling
Core Framework Contribution
LangChain
Open Source Contributor · langchain-ai/langchain
Contributed to LangChain internals by improving reliability around model initialization and developer-facing behavior in production-centric code paths.
Improved validation logic for safer model setup and clearer failure handling
Enhanced inference-related workflow behavior in initialization paths
Added targeted test coverage to prevent regressions in edge scenarios
Worked through maintainer review cycles with iterative PR refinements
PythonLangChain CorePytestCI/CDGitHub Actions
Documentation Contribution
Next.js
Open Source Contributor · vercel/next.js
Improved the App Router internationalization documentation with clearer guidance for setup, SEO, and locale handling.
Added setup and installation guidance for internationalization workflows
Documented SEO best practices including locale-aware metadata and hreflang usage
Improved examples for middleware and locale persistence patterns
Refined content through review cycles to align with maintainers’ documentation standards
Next.jsTypeScriptMDXDocumentationi18n
Engineering Mindset
How I think about system design
I optimize for systems that keep working under real load, are easier to reason about, and can be improved without constant rewrites. The focus is reliable backend architecture with practical AI integration.
Caching Strategy
Use cache-aside patterns and TTL design intentionally, with clear invalidation boundaries for correctness.
Concurrency Handling
Prefer explicit state transitions, idempotent endpoints, and queue-aware execution for race-prone paths.
API Reliability
Build around retries, timeouts, and graceful fallbacks so services degrade predictably under load or dependency failures.
Database Optimization
Focus on query plans, indexes, and read/write path design before scaling infrastructure blindly.
Distributed Systems
Design with service boundaries, observability, and failure modes in mind from the first iteration.
AI Workflow Integration
Treat AI flows like production systems: retrieval quality, guardrails, latency budgets, and measurable outcomes.
Contact
Let us build something reliable
Open to backend engineering, distributed systems, and applied AI engineering opportunities.
Direct Contact
Profiles & Resume
Built with Next.js, TypeScript, Tailwind CSS, and a backend-first product mindset.