Ahmed Elbadawy

Large-scale enterprise platform serving application teams across hybrid cloud infrastructure — covering secure development, deployment, and operations from a single internal platform.

I owned product strategy across four capability areas: Identity and Access Management, secure authentication, API enablement, and CI/CD. Not just backlog grooming — full alignment between Architecture, DevOps, Security, and Product Management on what got built and why.

What I delivered:

Defined and drove the platform roadmap, translating enterprise architecture standards and compliance requirements into prioritised epics with clear acceptance criteria

Strengthened CI/CD pipelines and automated release processes for Kubernetes-based containerised workloads across private and public cloud environments

Improved deployment workflows, RBAC models, secure service-to-service communication, and infrastructure provisioning standards in direct partnership with engineering teams

Contributed to observability enhancements across monitoring, logging, and traceability — improving operational transparency and Tier 3 support readiness

Owned and prioritised backlogs in Jira and Confluence; facilitated sprint planning, backlog refinement, and PI coordination in a SAFe environment across cross-functional teams

Supported scalable platform permission management and governance aligned to enterprise security policies

Core Areas:

Cloud-Native Platforms · Kubernetes · CI/CD · IAM & RBAC · DevSecOps · Hybrid Cloud · Observability · Grafana · ArgoCD · GitLab · GitHub · RDS · SAFe · Scrum

Skills: Product Ownership · Platform Engineering · IAM · Agile Delivery · Backlog Management · DevOps · Enterprise Architecture Alignment

Here's the rewritten Deutsche Bank experience, under 2000 characters:

AI Product Owner & Product Manager — Loan Intelligence Platform

Deutsche Bank · Freelance

Spain (Remote) · May 2023 – Oct 2025

Corporate lending at Deutsche Bank ran on manual spreadsheets, 30-day approval cycles, and growing ECB regulatory pressure. I led the AI-Driven Loan Intelligence Platform end-to-end — from product vision and roadmap through delivery, adoption, and regulatory sign-off — across a cross-functional team of data scientists, engineers, DevOps, QA, and compliance specialists.

What I delivered:

Loan approval time cut from 30+ days to under 48 hours

70% of manual credit risk reviews automated

Fraud detection accuracy improved to 85% using ML credit scoring, NLP document parsing, and Explainable AI (SHAP and LIME)

Underwriter adoption of AI recommendations up 30%; analyst productivity up 25%

Cloud infrastructure costs reduced by 20% through disciplined capacity roadmapping tied to product releases

Managed product budgeting and resource allocation across engineering, cloud infrastructure, and vendor costs aligned to the bank's digital transformation strategy

Integrated Salesforce CRM with the AI risk platform — relationship managers and credit analysts accessing AI-generated risk insights directly in dashboards, improving decision speed and customer engagement

Translated MiFID II, Basel III, GDPR, and ECB requirements into traceable, audit-ready user stories; delivered full ECB compliance documentation package in 9 working days under an emergency audit request

Stack: Python · TensorFlow · PyTorch · MLflow · SHAP · LIME · Salesforce · Kubernetes · Docker · Terraform · AWS · GCP · Azure · Jira · Confluence · SAFe

Skills: AI Product Ownership · Roadmap Strategy · Backlog Management · Regulatory Compliance · Stakeholder Management · Agile Delivery · Budget Ownership · DevOps · REST APIs · UX · Design Thinking

Almac Group’s four divisions — Clinical Services, Sciences, Diagnostics, and Drug Discovery — operated with fragmented master data, no unified client record, and end-to-end data integration gaps across Salesforce, SAP ERP, LabWare LIMS, and Veeva Vault. Led the full programme to design and deliver a scalable data integration architecture consolidating four legacy systems, establishing Salesforce as the single system of record, and enabling real-time data flow across all divisions through structured Master Data Management and Agile/Scrum delivery.

-Defined and owned the end-to-end data integration strategy across Salesforce and SAP ERP, establishing Master Data Management governance covering data ownership, entity resolution, golden record definitions, and data quality standards across 47,000+ records and four divisions.

-Guided and aligned Data Engineering teams across integration layers, translating complex data requirements into structured Jira backlogs with clear Definition of Ready, acceptance criteria, and sprint goals; ran Sprint Reviews as live integration demos with stakeholders replacing document-only reviews.

-Managed a complex multi-stakeholder environment across nine groups spanning BD, Client Services, Finance, IT, Quality, and Regulatory Affairs; established a two-tier governance model.

-Designed and implemented Snowflake data warehouse architecture to centralise integrated data from Salesforce and SAP ERP — building staging, transformation, and analytics layers; defined data models, pipelines, and access controls enabling real-time reporting, cross-divisional analytics, and audit-ready data traceability across all integration workstreams.

Technologies and Tools: Salesforce Sales Cloud, Service Cloud, Experience Cloud, Tableau CRM, MuleSoft Anypoint Platform, SAP ERP, Snowflake, LabWare LIMS, Veeva Vault, DocuSign, Conga Composer, Heroku, Node.js, React, Jira, Confluence, SAFe, Agile/Scrum, Master Data Management