Who is Karan Popat?
Karan Popat is a Lead Software Engineer and Technology Architect based in Berlin, Germany. For 12+ years he has helped companies build and scale enterprise e-commerce platforms — from greenfield Spryker and Magento backends to distributed Go microservices running across 26 countries. Today he works at Accenture Song leading teams of 9–15 engineers, and spends a growing share of his time shipping production AI workflows that make engineering teams faster without making them larger.
Four problems I solve well
$ Spryker · Magento 2 · Adobe Commerce · Go · Kafka
> I architect and deliver high-availability e-commerce backends that hold up under real load — B2B, B2C, and D2C models, multi-country deployments, distributed order management, and composable commerce migrations. If your platform is becoming a bottleneck, I can help you figure out why and what to do about it.
$ Microservices · Event-Driven Architecture · Strangler Fig Pattern
> I have led monolith-to-microservices migrations using the Strangler Fig pattern — breaking legacy platforms apart incrementally while keeping them live. I manage inter-service API contracts, design Kafka-based event streams, and make sure the transition does not become a rewrite-in-disguise.
$ n8n · CrewAI · Claude API · MCP Integration · Prompt Engineering
> I build production-grade agentic automation pipelines — not demos. Documentation generation, LLM-assisted code review, multi-agent research systems, automated order processing. I pioneered AI-enhanced engineering workflows at Accenture Song and took a proof-of-concept directly into a live client engagement.
$ Technical Leadership · Mentoring · TDD · Code Review Standards
> I lead and grow cross-functional backend teams through hands-on technical leadership — not just management. I establish TDD and code review practices, break down complex problems into deliverable work, and mentor engineers at every seniority level. Three engineers I have mentored have made measurable career progression under structured guidance.
Not a skills list — the areas where I have real accumulated judgment
$ Spryker · Magento 2 · Adobe Commerce · SAP Commerce Cloud · IBM Sterling OMS
> I have worked across every major enterprise e-commerce platform — certified in Spryker and Adobe Commerce, with hands-on experience in SAP Commerce Cloud and IBM Sterling OMS. I know where each platform breaks down at scale and how to design around those limits.
$ Go · Kafka · Kubernetes · Redis · PostgreSQL
> My primary backend language is Go. I design event-driven microservice systems with Kafka, manage stateful workloads on Kubernetes, and build caching layers with Redis. I own these decisions end-to-end — from domain modelling to production observability.
$ GraphQL · REST APIs · gRPC · API-First Design
> I design APIs that other teams can build on without constantly asking questions — clear contracts, versioning strategies, and integration patterns that hold up as systems grow. I have delivered GraphQL API layers, RESTful service contracts, and gRPC service meshes across distributed platforms.
$ n8n · CrewAI · Claude API · LLM Integration · Agentic Systems
> I build AI workflows that run in production, not just in notebooks. Multi-agent pipelines with CrewAI, automation workflows in n8n, LLM integration via the Claude API and MCP. I apply prompt engineering rigorously and have structured AI-enhanced development standards adopted across an engineering practice.
$ AWS · Docker · Kubernetes · Terraform · CI/CD · Azure DevOps
> I deliver on AWS — containerised workloads, infrastructure-as-code with Terraform, automated CI/CD pipelines. I led a deployment process overhaul that cut deployment time by 65% across a multi-country OMS rollout.
How I approach the work — what you can expect
$ ADRs · Incident ownership · No finish lines at launch
> When I am on a project, I treat the system as my responsibility — writing architecture decision records, tracking problems to root cause, and thinking about what happens six months after go-live. I do not drop the work at the edge of my job description.
$ TDD · BDD · Integration Testing · Acceptance Testing
> I write tests before implementation — not as a ritual but because it catches the right problems at the right time. I establish these practices in teams I join and treat untested code as unfinished work.
$ Agentic tooling · Prompt engineering · Workflow automation
> AI should handle the repetitive parts — boilerplate, documentation, research synthesis — so engineers can focus on design, architecture, and the problems that actually require thinking. I build AI workflows with that constraint in mind.
$ Code review · Engineering culture · Compounding standards
> I care about what the team leaves behind — the patterns, the practices, the habits. A codebase should be in better shape after I have worked on it, not just functionally complete.
$ Technical blog · Go · Spryker · AI engineering
> I maintain a technical blog covering microservice architecture, Spryker and Magento patterns, composable commerce, and production AI engineering. Writing forces clarity — and it means the ideas I find useful do not stay locked in my head.
Formal recognition that reflects where I have invested time
$ Claude Code in Action
> Issued March 2026 · Credential ID: i8k65e9m6btx
$ Reinvention with Agentic AI
> Issued March 2026 · AI Agents · Agentic Systems
$ Adobe Certified Professional — Magento Commerce Developer
> Issued March 2019
$ Certified Foundations Developer
> Issued September 2022
$ AWS Cloud Quest: Cloud Practitioner
> Issued April 2023
Worth a Conversation?
If you are scaling an e-commerce platform, breaking apart a monolith, or trying to make AI actually useful inside an engineering team — I am happy to talk through what you are working on.