About Me

For Recruiters

I am a Go-focused Backend, Platform, and AI Infrastructure Engineer who specializes in building production-grade distributed systems. My work combines cloud-native engineering, Kubernetes automation, event-driven architectures, AI infrastructure, and observability to create scalable and reliable platforms. I am particularly interested in AI Infrastructure Engineering, Platform Engineering, Distributed Systems Engineering, Senior Backend Engineering, and Cloud Native Engineering roles.

Senior Go Backend Engineer Platform Engineer AI Infrastructure Engineer AI Platform Engineer Cloud Native Engineer Distributed Systems Engineer Staff Software Engineer
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Professional Summary

I specialize in building systems that are reliable, observable, secure, and capable of operating at scale. My focus is not only on writing software but on designing complete platforms that solve real-world business problems through automation, intelligent workflows, and resilient distributed architectures. Currently, I am building LogiFlow AI, a production-grade AI infrastructure platform that combines Kubernetes automation, multi-agent workflows, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), LLM routing, event-driven architecture, and enterprise-grade observability.

My goal is to bridge the gap between traditional backend engineering and next-generation AI systems by building the infrastructure that powers intelligent applications. I enjoy solving complex technical problems, designing scalable architectures, and building systems that operate reliably at production scale.

Core Skills & Expertise

Backend Engineering

  • āœ” Go (Golang)
  • āœ” REST APIs
  • āœ” gRPC
  • āœ” GraphQL
  • āœ” WebSocket
  • āœ” Microservices Architecture
  • āœ” Domain Driven Design (DDD)
  • āœ” Clean Architecture
  • āœ” Event Driven Architecture

Distributed Systems

  • āœ” Kafka
  • āœ” RabbitMQ
  • āœ” Temporal Workflows
  • āœ” CQRS
  • āœ” Event Sourcing
  • āœ” Outbox Pattern
  • āœ” Saga Pattern
  • āœ” Distributed Transactions
  • āœ” High Availability Systems

Cloud Native & Platform Engineering

  • āœ” Kubernetes
  • āœ” Custom Operators
  • āœ” CRDs & Controllers
  • āœ” Helm
  • āœ” Terraform
  • āœ” GitOps
  • āœ” ArgoCD
  • āœ” Docker
  • āœ” Infrastructure as Code
  • āœ” Multi-Tenant Platforms

AI Infrastructure Engineering

  • āœ” LLM Gateways
  • āœ” Multi-Agent Workflows
  • āœ” Retrieval Augmented Generation (RAG)
  • āœ” Model Context Protocol (MCP)
  • āœ” Vector Search
  • āœ” pgvector
  • āœ” Semantic Caching
  • āœ” Prompt Versioning
  • āœ” Structured Outputs
  • āœ” LLM Routing & Fallback Systems
  • āœ” AI Observability
  • āœ” LLM Cost Governance

Databases & Storage

  • āœ” PostgreSQL
  • āœ” MySQL
  • āœ” MongoDB
  • āœ” Redis
  • āœ” ClickHouse
  • āœ” InfluxDB
  • āœ” pgvector

Security & Identity

  • āœ” OAuth2
  • āœ” OpenID Connect (OIDC)
  • āœ” JWT Authentication
  • āœ” RBAC
  • āœ” Multi-Tenant Authorization
  • āœ” API Key Management
  • āœ” MFA Systems
  • āœ” SSO Integrations

Observability & Reliability

  • āœ” OpenTelemetry
  • āœ” Prometheus
  • āœ” Grafana
  • āœ” Jaeger
  • āœ” Distributed Tracing
  • āœ” SLO Design
  • āœ” Error Budget Management
  • āœ” Production Monitoring
  • āœ” Incident Response

Key Achievements

1

AI Infrastructure Platform Development

Designing and implementing a complete AI infrastructure platform including multi-provider LLM Gateway, MCP Server integration, RAG pipelines, agentic workflows, tenant isolation, usage billing, and Kubernetes automation.

2

Distributed Systems Engineering

Built scalable event-driven architectures using Kafka, RabbitMQ, Temporal, PostgreSQL, and gRPC with a strong focus on reliability, fault tolerance, and operational excellence.

3

Multi-Tenant SaaS Architecture

Designed systems supporting tenant isolation, secure authentication, authorization, billing, rate limiting, and resource governance across shared infrastructure.

4

Platform Engineering

Built cloud-native deployment platforms using Kubernetes, Helm, Terraform, GitHub Actions, and ArgoCD to enable automated deployments and infrastructure management.

5

Client Delivery

Delivered SaaS and backend solutions for international clients, including large-scale business applications, microservices migration projects, RBAC systems, multi-tenant architectures, and production deployments.

Work Experience

Freelance Senior Backend & Platform Engineer

Fiverr | Upwork | Direct Clients
2022 ā€“ Present

Working with international clients to design, architect, and build scalable backend systems, cloud-native platforms, and SaaS products. Responsibilities extend beyond coding to include system architecture, infrastructure planning, security, performance optimization, deployment automation, and technical leadership.

  • Architected distributed microservices systems in Go and designed PostgreSQL schemas with optimized indexes.
  • Designed and implemented multi-tenant SaaS platforms with secure authentication, role-based access control (RBAC), and session management.
  • Deployed applications on Kubernetes using Docker, Helm, Terraform, and GitOps with ArgoCD.
  • Integrated AI services, LLM APIs, vector search (pgvector), and automated multi-agent workflow engines.
  • Collaborated directly with founders and business stakeholders to scope, estimate, and deploy production projects.