Backend Engineering
Languages, APIs, and service patterns I use to build maintainable backend features.
PHPTypeScriptJavaScriptPythonNode.jsNestJSREST APIsOpenAPI/SwaggerAuthentication/AuthorizationJWT/OAuthWebhooks
Senior Software Engineer | AI-enabled backend systems
Lokesh Burma
Senior Software Engineer focused on cloud-native backend systems, reliability, large-scale data movement, and AI-assisted engineering workflows. I build production backend systems that are easier to scale, observe, debug, and operate.
Engineering impact
Designed phased backend migration patterns for moving high-volume relational data into S3-backed analytical storage.
Built reliability workflows that classify retryable and permanent failures, preserve retry history, and improve support diagnostics.
Created AI-assisted debugging workflows that combine issue context, logs, database signals, and structured RCA techniques.
Improved operational visibility with dashboards, standardized status models, and clearer production diagnostics.
Positioning
Backend systems with scale, reliability, and AI-assisted operations.
The portfolio is organized around the work that best represents my engineering direction: distributed backend architecture, production reliability, and practical AI tooling for engineering teams.
Large-Scale Backend Architecture
Worked on billion-row data migration patterns using PostgreSQL, S3 Tables, Apache Iceberg, Athena, DynamoDB, and phased state-machine rollouts.
Reliability And Observability
Improved failure classification, retry-history tracking, error-code coverage, and customer/support visibility across backup workflows.
AI-Enabled Backend Engineering
Built Claude-powered debugging workflows with MCP integrations, log analysis, database context, and fix-plan generation.
Production Ownership
Owned backend features from design through canary rollout, documentation, team enablement, and operational follow-through.
Technologies
Core tools at a glance
A quick visual map of the technologies I use most in backend, cloud, observability, and AI-assisted engineering work.
PHP
TypeScript
Node.js
NestJS
AWS
Docker
PostgreSQL
DynamoDB
Grafana
Claude
Technology map
Tools and systems I have worked with
Grouped by how I use them in backend engineering work, instead of as one long keyword list.
Architecture And Reliability
System design practices for dependable distributed services and failure-aware workflows.
MicroservicesDistributed SystemsEvent-Driven ArchitectureState MachinesRetry WorkflowsIdempotencyRate LimitingBackground Jobs/QueuesFailure ClassificationSystem Design
Cloud And Data
AWS services, storage systems, and data patterns used in SaaS backend platforms.
AWSIAMEC2S3SQSLambdaECS/FargateRDSPostgreSQLDynamoDBRedisAthenaApache IcebergS3 TablesQuery Optimization
Observability
Tools and practices for making production behavior easier to inspect and debug.
GrafanaELKKibanaCloudWatchStructured LoggingError TaxonomyOperational DashboardsRCA Workflows
AI-Enabled Engineering
AI-assisted workflows for debugging, RCA, documentation, and engineering acceleration.
Claude CodeMCPLangflowPrompt EngineeringAI-Assisted DebuggingRCA AutomationLog Analysis With AIEmbedding Search
Delivery And Tools
Version control, delivery pipelines, deployment tooling, and local engineering utilities.
DockerGitGitHubAWS CodeCommitCodePipelineAzure DevOpsCI/CDCanary RolloutsEnvironment VariablesVercelPostmanDBeaverRedisInsight
Case studies
Selected engineering work
These projects show the work I want to be evaluated on: backend architecture, reliability, observability, AI-assisted debugging, and production ownership.
Backup Failure Classification & Observability
A reliability initiative that standardized failure models, retry history, error-code coverage, and customer-facing diagnostics across backup workflows.
Expanded classification coverage from 350 to 2,957 error codes and improved support visibility.
Node.jsPHPELKGrafanaCloudWatch
Read case studyClaude Debugger Agent
An AI-assisted diagnostic agent that connects issue context, logs, database signals, and historical analysis to recommend root causes and fix plans.
Reached 85%+ fix-plan accuracy and reduced manual incident-analysis effort across engineering teams.
Claude CodeMCPAzure DevOpsKibanaDatabasesPrompt Engineering
Read case studyRDS to S3 Table Migration
A large-scale data architecture initiative moving high-volume email metadata from PostgreSQL into S3-backed Apache Iceberg tables with Athena access.
Reduced RDS storage pressure and enabled a safer phased migration model for billion-row metadata tables.
PostgreSQLS3Apache IcebergAthenaDynamoDBAWS
Read case studyPipeline
Future projects and learning direction
A transparent view of where I want to take this portfolio and my engineering practice next.
Now
Portfolio as an engineering knowledge base
Turning the portfolio into a living set of case studies, backend notes, and operational cheat sheets.
Next.jsMDXTypeScriptVercel
Next
Backend architecture diagrams library
Building visual notes that simplify backend concepts and architectures such as state machines, migrations, retry flows, observability, and distributed service patterns.
MermaidSystem DesignDocumentationBackend Architecture
Reference
Cheat sheets for daily engineering
Quick command references for tools I use often. These are useful for me and also show how I document practical workflows.
Containers
Docker Backend Debugging Cheatsheet
Common Docker commands for inspecting containers, logs, images, and local backend services.
Open cheatsheetVersion Control
Git Daily Workflow Cheatsheet
Commands for checking status, branching, committing, syncing, and recovering common Git workflows.
Open cheatsheetDeployment
Vercel And Next.js Deployment Cheatsheet
Quick commands and checks for deploying a Next.js portfolio through GitHub and Vercel.
Open cheatsheetWriting
Engineering notes
Featured posts focus on backend systems and how I reason about architecture, debugging, and this frontend portfolio as a backend engineer.
AI Writes Code Now. So What Is the Role of a Backend Developer?
AI is changing backend development, but it is not removing the need for backend engineers. The role is shifting toward judgment, system design, production ownership, and business problem solving.
AI EngineeringBackend EngineeringSystem DesignCareer
Read postBuilding Production-Grade Backend Applications
A production-grade backend is more than APIs and database queries. This post covers the essential components backend systems need for scalability, reliability, security, observability, and fault tolerance.
Backend EngineeringSystem DesignProduction EngineeringReliability
Read postSecurity Best Practices for Handling Production Workloads
Security for production workloads starts long before deployment. This post walks through secure practices from code and Git workflows to CI/CD, QA, deployment, monitoring, and long-term maintenance.
SecurityProduction EngineeringDevOpsObservability
Read post