Konstantinos Melessanakis

Konstantinos Melessanakis

Athens, Greece

Building the systems behind enterprise delivery.

Technical Lead focused on Salesforce architecture, cloud integrations, CI/CD practices, and practical AI adoption.

Career

The Road So Far

From independent Java and ERP project work in Crete to enterprise platform leadership, each step sharpened how I connect business context, architecture, and delivery.

2017/Foundation

Independent Java and ERP Delivery

Started building software independently in Heraklion, Crete, delivering contractor project work across Java, Spring Boot, and ERP-focused business applications. This period built the habit of understanding the business process before shaping the technical solution.

Delivered Java, Spring Boot, and ERP ecosystem project work for client-facing business applications.

2022/Enterprise Delivery

Enterprise Salesforce Foundation

Graduated from the University of Crete with a BSc in Computer Science, then joined Deloitte Greece. Built the Salesforce foundation through hands-on delivery while learning how enterprise teams coordinate requirements, development, testing, and release work.

Built Apex, Visualforce, Lightning, declarative automation, and Salesforce DX delivery workflows.

2023/Architecture

Consulting, Architecture, and Prototyping

Promoted to Consultant at Deloitte and moved deeper into client-facing engineering. Started shaping solution direction, leading technical validation, and using prototypes to reduce delivery risk before implementation scaled.

Led key solution architecture decisions for a major automotive enterprise Salesforce implementation.

2024/Platform Engineering

Platform Engineering and Cloud Integrations

Moved to KERUN.ONE and expanded from feature delivery into platform engineering. Delivered across Salesforce clouds, cloud integrations, and release workflows while pushing the team toward more repeatable, Git-based delivery.

Connected Salesforce with AWS Lambda, S3, Azure Functions, legacy CRM systems, ERPs, and external platforms.

2025/Leadership

Technical Lead Transition

Promoted to Salesforce Technical Lead at KERUN.ONE, expanding from senior hands-on development into team direction, solution architecture, and delivery governance. Began formalizing how the team evaluates architecture choices, delivery practices, and emerging AI-assisted workflows.

Led Salesforce implementation workstreams across multi-cloud platform initiatives and enterprise integrations.

2026/AI Enablement

Enterprise Platform Leadership

Continued technical leadership after KERUN.ONE's merger into CONET, leading a Salesforce development team across architecture, code review, integration design, CI/CD practices, and delivery standards. The current focus is reliable enterprise platforms, cloud-connected business systems, and practical AI-assisted engineering adoption.

Lead a team of five Salesforce developers across architecture, delivery planning, code review, and mentorship.

Technical Stack

Languages

JavaTypeScriptJavaScriptPythonApexCC++SQLSOQL

Frontend & Backend

ReactNext.jsAngularNode.jsSpring BootREST APIs

Salesforce

SalesforceApexLightning Web ComponentsFlowSalesforce DXExperience CloudSales CloudService CloudB2B CommerceRevenue Cloud & CPQData CloudAgentforce

Cloud & DevOps

AWS LambdaAWS S3Azure FunctionsGitCI/CDGitHub ActionsBitbucket Pipelines

Architecture & AI

Solution ArchitectureTechnical LeadershipCode ReviewsEngineering StandardsLLM EvaluationWorkflow AutomationPrompt Engineering
Certifications
Salesforce Certified Experience Cloud Consultant
Salesforce Certified Sharing and Visibility Designer
Process Automation Accredited Professional
Salesforce Certified Javascript Developer I
Salesforce Certified Platform Developer I
Salesforce Certified Administrator (SCA)
Salesforce Certified Platform App Builder Certification
Salesforce Certified AI Associate
Salesforce Certified Associate
Education

Bachelor's degree, Computer Science

University of Crete, Department of Computer Science · 2022

Thesis

SpadePort

An open-source implementation of SParse Audio DEclipper (SPADE) in the C Programming Language

My thesis delivered SpadePort, a full open-source C implementation of the SPADE audio declipping algorithm, making the MATLAB methodology faster, portable, and suitable for constrained systems.

Implemented the full SPADE reconstruction workflow in C, including the core signal-processing operations required for audio declipping.

Matched MATLAB reconstruction quality while reducing average processing time from 4.8s to 1.4s per second of audio and memory usage from roughly 1.8 GB to 11-12 MB.

CSPADEAudio DeclippingFFTSignal ProcessingMATLAB Benchmarking
Languages
Greek - Native or bilingual
English - Native or bilingual
German - Limited working
Dutch - Limited working

Let's connect

Interested in technical collaboration or discussing a new opportunity? Connect with me on LinkedIn.