[email protected]:~
Paul Afolabi

$ whoami

Paul Afolabi

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Software Engineer | MS AI @ Carnegie Mellon University

$ location

Remote (Global) · Kigali, Rwanda

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Software and Machine Learning Engineer with over 3 years of experience building high-throughput, resilient distributed architectures, event-driven payment systems (Kafka, Redis), and secure APIs across leading African banks. Currently complementing that backend depth with applied AI focusing on personalization, recommender systems, and agentic systems for finance, healthcare, logistics, and e-commerce domains.

$ open →

githublinkedinresume.pdfcontact --me
# stats.jsonpaul.dev.ai
EXPERIENCE3+ yrs
CURRENT ROLEMS AI @ CMU
FOCUSDistributed Sys / AI·ML
OPEN TOApplied AI · DS · ML · SWE
EDUCATIONMS AI, CMU · 2028
intro.mp4

$ cat skills.txt

# Programming & DevelopmentLANGUAGES · FRAMEWORKS
C# (.NET Core, ASP.NET, Entity Framework)92%
[
]
Python (AI/ML, FastAPI, data pipelines)88%
[
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Java & SQL85%
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Docker, Kubernetes, Git88%
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AI & ML (Recommender Systems, Applied ML)80%
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]
# Infrastructure & DataCLOUD · MESSAGING · DATABASES
Apache Kafka & Redis (event-driven arch)95%
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AWS (Solutions Architect) & Azure88%
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MSSQL, Oracle SQL, PostgreSQL, MongoDB90%
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Azure Blob, DynamoDB, Redis Cache, S385%
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Linux, SUSE Rancher, IIS, Kubernetes85%
[
]

$ ls projects/

FIFO Single Server Queue

GitHub Repo
Stochastic ProcessesData Science

# stack

PythonNumPyMatplotlibGoogle Colab

# overview

Built a discrete-event simulation of a single-server FIFO queue (M/G/1-style) to study how utilization and arrival variability affect waiting time, system time, and queue length across rho = 0.5 to 0.95.

# key outcomes

›

Demonstrated that utilization alone does not fully determine delay behavior near saturation.

›

Showed reduced arrival variability at matched mean rates materially lowers congestion.

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Provided practical capacity-planning insight: misjudging variability can lead to wrong infrastructure decisions.

FCY Payment Processor

GitHub Repo
FinTechFinanceBanking

# stack

GoPostgreSQLDocker

# overview

Built a multi-currency (USD, EUR, GBP, NGN) payment backend covering onboarding, accounts, deposits, FX conversion, fee and VAT computation, and internal and external transfers using transactional posting through suspense and GL accounts for traceability and settlement.

# key outcomes

›

Implemented concurrent transfer processing using goroutines.

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Diagnosed transfer latency regression from 125ms to 220ms to connection-pool constraints.

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Tuned database pooling to bring transfer latency down to about 110ms and added business-rule and negative-path tests around transfer integrity.

$ cat experience_education.txt

# EXPERIENCE

Backend Engineer

Wema Bank PLC, Lagos, Nigeria

DEC 2025 – OCT 2026
›

Provisioned and managed an on-premises geo-redundant active-active 5-node Kafka cluster + Redis infrastructure processing NGN1B+ ($700K+) in daily payment volume — zero data loss, zero financial exposure.

›

Improved average transaction processing latency by 20% across all payment rails and saved the Bank $100K+ annually by replacing Confluent vendor licensing with an in-house managed solution.

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Redesigned eTranzact payment system into an event-driven Kafka-and-Redis 5-microservice solution: 25x faster (96% latency reduction), end-to-end time dropped from 20s → 800ms.

Backend Engineer

First Bank of Nigeria Ltd, Lagos, Nigeria

APR 2024 – DEC 2025
›

Led decomposition of the LIT mobile monolith backend into 21 microservices, directly managing a team of 7 developers.

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Developed the PAPSS (Pan-African Payment & Settlement System) remittance feature on LIT App — handles $500K+ in annual cross-border transaction volume.

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Built a Kafka-powered push notification service delivering 1M+ notifications daily for user activity events.

Backend Engineer

Access Bank Plc, Lagos, Nigeria

DEC 2022 – MAR 2024
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Led development and deployment of 3 middleware applications across 10 African subsidiaries of the Bank.

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Built an account opening microservice increasing daily customer onboarding by 40% (3,000 → 5,000 customers/day).

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Developed an account statement microservice generating ~₦6M (~$7,500) in annual revenue for the Bank.

# EDUCATION

MS Engineering Artificial Intelligence

2026 – 2028

Carnegie Mellon University, Pittsburgh, PA

› Recommender Systems› Applied Stochastic› AI for Engineers› Applied Machine Learning

B.Eng. Mechanical Engineering

2015 – 2021

Federal University of Technology, Minna — Nigeria

# CERTIFICATIONS

Linux Foundation

MAY 2026

LFS250: Kubernetes & Cloud Native Essentials (KCNA)

Amazon Web Services

JAN 2026

AWS Certified Solutions Architect – Associate

Axelos

MAR 2023

ITIL Foundation Certificate in IT Service Management

Microsoft

MAR 2023

Microsoft Certified: Azure Fundamentals (AZ-900)

$ let's-collaborate

# let's-collaborate.mdopen to opportunities

Whether you're building high-throughput payment infrastructure, designing event-driven distributed systems, or exploring AI integration in enterprise software — I'm always open to challenging problems.

I bring 3+ years of hands-on backend engineering at scale, a track record in FinTech, and a graduate-level grounding in AI & ML from CMU. Let's build something impactful.

# contact.jsonpaul.dev.ai
EMAIL[email protected]
LINKEDIN@paul-afolabi
GITHUBgithub.com/api-sage
STATUSOpen · Applied AI, Data Science, ML, SWE

Response time · usually within 24 hours