I am building at the intersection of AI, Platform Engineering, DevOps, SRE, and Cloud Infrastructure.

My focus is not AI theatre. I am interested in practical systems that improve engineering execution: intelligent incident analysis, infrastructure automation, AI-assisted SDLC workflows, reliable model operations, and developer productivity.

• KubeSage AI — AI-powered Kubernetes operations and incident intelligence
• AI agents for DevOps and SRE — investigation, diagnosis, remediation, and workflow automation
• Agentic ML workflows — orchestration and automation across the ML lifecycle
• AI-assisted SDLC platform — hackathon project for planning, coding, testing, reviewing, documenting, and deployment workflows
• PaisaPulse — modern expense tracking and financial intelligence platform
• AWS platform automation — reusable infrastructure patterns using Terraform, Kubernetes, ECS, EKS, and CI/CD

• Agentic AI systems and multi-agent architectures
• OpenAI Agents SDK, LangGraph, CrewAI, and MCP
• RAG architecture, evaluation, and observability
• MLOps and LLMOps workflows
• Model serving and inference infrastructure
• AI security, governance, and production reliability

• AI infrastructure and agentic systems
• AI-powered DevOps, SRE, and platform engineering tools
• Kubernetes automation and incident intelligence
• MLOps, LLMOps, and model workflow orchestration
• Open-source AI developer tools
• Cloud-native platform engineering

AWS · Kubernetes · Terraform · ECS · EKS · Platform Engineering · DevOps · SRE · CI/CD · Observability · AI Agents · GenAI on AWS

• Designing and operating production AWS platforms
• Multi-region ECS Fargate and Kubernetes workloads
• Terraform Enterprise and Environment-as-Code
• Jenkins, Spinnaker, GitHub Actions, and GitOps
• Dynatrace, Splunk, Prometheus, Grafana, and CloudWatch
• Event-driven and serverless systems using Lambda, SQS, EventBridge, Step Functions, and S3
• Amazon Bedrock integrations and AI-powered document workflows
• AI agents for cloud operations, incident response, and engineering automation

AI-powered Kubernetes Operations and Incident Intelligence Platform

Designed to help engineers investigate cluster issues, correlate operational signals, summarize incidents, and support safe remediation workflows.

Core stack: Python · FastAPI · Kubernetes · LLMs · Docker · Prometheus · Grafana

An AI-assisted software delivery workflow designed around specialized engineering agents.

Planned agent workflow:

• Requirements analysis
• Architecture generation
• Implementation planning
• Code generation
• Test generation
• Code review
• Documentation
• Deployment assistance

The objective is not blind autonomous coding. It is a controlled SDLC workflow with human review, traceability, and quality gates.

Enterprise document classification workflow using Amazon Bedrock and serverless AWS services.

Core stack: Amazon Bedrock · Claude · TypeScript · AWS Lambda · CloudWatch · DLQ · Serverless

A modern expense tracking and financial intelligence application.

Focus areas:

• Secure authentication
• Expense and account tracking
• Budget management
• Financial analytics
• AI-assisted insights and categorization
• Clean full-stack user experience

Reusable cloud infrastructure patterns for production workloads.

Core stack: Terraform · AWS · ECS · EKS · ALB · Route 53 · CI/CD · Observability

Amazon Bedrock · Claude · OpenAI · AI Agents · Prompt Engineering · LangGraph · CrewAI · MCP · MLflow · scikit-learn · Pandas · NumPy

AWS · Azure · GCP · EKS · ECS Fargate · Lambda · S3 · DynamoDB · SQS · EventBridge · Step Functions · Route 53

Terraform · Terraform Enterprise · CloudFormation · Kubernetes · Docker · Helm · GitOps · Packer · Vagrant

Jenkins · Spinnaker · GitHub Actions · GitLab CI/CD · Bitbucket Pipelines

Dynatrace · Splunk · Prometheus · Grafana · CloudWatch · Container Insights · SLOs · Incident Response

Python · TypeScript · Go · Bash · PowerShell

• 7+ years across cloud, DevOps, SRE, and platform engineering
• Designed and operated multi-region AWS infrastructure
• Reduced recovery time through automated health checks and failover
• Provisioned repeatable infrastructure across multiple AWS accounts
• Built CI/CD workflows with approvals, validations, and rollback controls
• Implemented centralized observability and SLO-driven operations
• Developed event-driven TypeScript Lambda services
• Built AI-powered document classification workflows using Amazon Bedrock
• AWS Certified Solutions Architect – Associate
• Recipient of delivery and performance awards across previous organizations

• Production cloud and platform engineering
• Kubernetes, Terraform, CI/CD, and observability
• Amazon Bedrock integrations
• AI-assisted development and prompt engineering
• Initial AI-agent projects
• Multi-agent workflow orchestration
• AI evaluation and guardrail framework
• Production LLMOps reference platform
• Kubernetes incident intelligence agent
• Open-source contribution to an agentic AI or platform engineering project

I am documenting what I learn and build around:

• AI infrastructure and agentic systems
• DevOps, SRE, and platform engineering
• Kubernetes and Terraform
• AWS architecture and automation
• MLOps and LLMOps
• AI-assisted software delivery
• Engineering career growth
• Building practical software products

I am interested in serious conversations around AI Infrastructure, Platform Engineering, Kubernetes, DevOps, SRE, Agentic AI, and open-source engineering.