Backend Software EngineerJava, Spring, and SAP Commerce Cloud

Backend Software Engineer focused on Java and Spring across production platforms, with SAP Commerce Cloud as a strong specialization.

My work combines REST APIs, SQL, integrations, incidents, and close collaboration with QA, business teams, and clients.

4+ years experience

Java Backend

Production support

SAP Commerce expert

Featured work

Work presented through problem, solution, and impact

Three concrete cases covering production, checkout, pricing, stock, integrations, and support work.

Stratesys · CaixaBank Tech · 2025

BuildingCenter: production backend on SAP Commerce Cloud

Keeping a business-critical platform stable while shipping backend changes and investigating production issues with clear functional context.

ProductionIntegrationsSQLJavaSpringSAP Commerce Cloud
View case

Minsait · Claro Perú · 2024

Claro Perú: backend work across checkout, pricing, and stock

Implementing changes in checkout, pricing, stock, and integrations without degrading baseline platform behavior.

CheckoutPricingIntegrationsJavaSpringSAP Commerce Cloud
View case

AI applied to technical work

AI as an analysis accelerator, not a substitute for technical judgment

Since my current stage at Stratesys, I use generative AI to accelerate technical analysis, debugging, and change preparation while keeping technical decisions, local testing, and pre-QA validation under my own responsibility.

View real cases

AI as accelerator

1

Context and data

I review logs, traces, code, and business context.

2

AI analyzes

AI detects patterns and proposes hypotheses.

3

Initial output

I get a summary, likely causes, and options.

I validate and decide

4

Local testing

I validate hypotheses with tests and code review.

5

Technical validation

I review standard behavior, impact, and functional criteria.

6

Decision and delivery

I make the final decision and deploy the solution.

AI = Accelerator

It speeds up analysis, information lookup, and option generation to save time on cognitive and repetitive tasks.

I = Responsible

I decide, validate, test, and own the technical outcome and the production impact.

AI does not replace experience or technical judgment. Its greatest value is getting to useful context sooner, reducing repetitive work, and leaving more time to solve complex problems and make better engineering decisions.

Day-to-day impact

Complex changes

~70%

less time

On analysis and initial preparation of complex changes when the context is comparable.

1-2 day tasks

< 1

day

When the context is bounded and validation still remains mine.

Incidents

minutes

first hypothesis

To locate likely causes before debugging and validating.

Estimates based on my own metrics from comparable tasks completed before and after introducing generative AI into my workflow. They are not universal benchmarks, but observed impact in my professional context.

About

How I built my profile as a Backend Engineer

My profile has grown around real systems: production platforms, integrations, incidents, business logic, and collaboration with technical and functional teams.

01

Before touching code

I understand flows, affected data, and risks before implementing.

02

When there is an incident

I analyze symptoms, logs, and hypotheses before defining a solution.

03

When business needs an answer

I translate technical impact into clear next steps for QA, clients, and business teams.

04

How I use AI

I use it as an accelerator, never as a substitute for technical judgment.

Ready to talk about backend, integrations, and product?

Open to new opportunities and conversations around backend engineering, integrations and product platforms.