Md. Masum Khan
AvailableEngage
Md. Masum Khan
About

The person behind
the systems

20+ years. Healthcare. Government. Enterprise. Global AI. This is how a network engineer becomes a reasoning systems architect.

13Global active clients
500K+Records managed
$2.5M+Budget led
01

The Story

Not a resume. An evolution.

I started where most infrastructure stories begin, deep in network architecture, pulling cable, configuring Cisco switches & routers, keeping hospitals alive. For over a decade at BIRDEM, I built the IT backbone that 1,000+ healthcare professionals depended on daily. Near-zero downtime wasn't a KPI. It was a clinical necessity.

That discipline of building systems that cannot fail never left me. It shaped how I think about every layer of a stack — from a database schema to an LLM pipeline.

At the World Bank's ROSC-II project, the scale shifted to national. I architected a monitoring system for 400,000+ student records across Bangladesh — designing not just the technology, but the data governance policy that would make it trustworthy for decades.

Then came Lithe Group, where I stepped into enterprise leadership as Head of IT — managing a $1M+ annual budget, building an ISO 27001 security program that cut incidents by 40%, and deploying ML models that reduced supply chain delays by 15%.

Today, as Chief Data Scientist & CTO at Encore IT, I lead AI strategy for 13 global clients — architecting RAG systems, GraphRAG knowledge graphs, and Agentic AI workflows that don't just retrieve information. They reason about it.

Current RoleCTO & Chief Data ScientistEncore IT · Global
LocationDhaka, BangladeshAvailable globally (remote)
Experience20+ YearsHealthcare · Gov · Enterprise · AI
SpecializationAI Reasoning SystemsRAG · GraphRAG · Agentic AI · MLOps
LanguagesBengali · EnglishNative · Professional
Open toConsulting & CollaborationAI strategy · System architecture
02

How I Think

The principles that shape every system I build

"Most systems fail not because the code is wrong, but because the model of the problem was wrong. I spend more time understanding the system I'm building for than the system I'm building."

— Md. Masum Khan

01

Systems before solutions

Before writing a line of code, I map the system. What are the inputs? What decisions does this need to support? Where does it break? Most failures are architectural, not technical.

02

AI must reason, not just retrieve

The gap between a search engine and an intelligent system is reasoning. RAG retrieves. GraphRAG connects. Agentic AI acts. I build toward the third — systems that can hold context, weigh trade-offs, and justify outputs.

03

Complexity is not an excuse

I've worked on national-scale government systems, hospital infrastructure, and textile supply chains. Every one of them was 'too complex to simplify.' That's exactly when clarity becomes the most important deliverable.

04

Data governance is trust infrastructure

An AI system is only as reliable as the data it reasons about. ISO 27001, data lineage, access controls — these aren't compliance checkboxes. They're the foundation that determines whether a system can be trusted at scale.

03

Technical Arsenal

Grouped by thinking domain — not dumped in a list

🧠
AI & ML Systems
Large Language ModelsRAG ArchitectureGraphRAGAgentic AILangChainOpenAI APITensorFlowKerasPyTorchScikit-LearnMLOpsCI/CD Pipelines
📊
Data Science
PythonPandasNumPySeabornMatplotlibPredictive ModelingDemand ForecastingStatistical AnalysisData PipelinesFeature Engineering
⚙️
Backend & APIs
DjangoFastAPIPostgreSQLMySQLREST APIsGraphQLCeleryRedisWebSockets
🖥️
Frontend
Next.jsReactTypeScriptTailwind CSSFramer Motionshadcn/uiHTML5CSS3
☁️
Cloud & Infrastructure
AWS (S3, EBS, IAM, EC2)Linux (RHCE)Cisco (CCNA)DockerCloud ERPISO 27001IT GovernanceNetwork Architecture
🎯
Leadership & Strategy
C-Suite AdvisoryDigital TransformationEnterprise ArchitectureBudget Management ($1M+)Team Leadership (17+)IT ProcurementPolicy Formulation
04

Career Timeline

Network Engineer → IT Head → World Bank Consultant → Global AI CTO

Chief Data Scientist & CTO

Current
Encore IT
2025 – Present
Leading AI strategy for 13 global clients
Architecting LLM, RAG & GraphRAG systems
Building Agentic AI workflows
AWS cloud-native MLOps pipelines
C-suite advisory across verticals

Head of Information Technology

Enterprise
Lithe Group · RMG & Textile
2019 – 2025
30% operational efficiency via cloud ERP
15% reduction in order delays using ML
$1M+ annual IT budget managed
25% cost savings achieved
ISO 27001 → 40% fewer security incidents
99.9% uptime across all systems
Team of 17 professionals led

IT Consultant

Government
World Bank · ROSC-II Project
2017 – 2019
National student monitoring system for 400K+ records
Digital automation policy formulation
ISO 27001 compliance framework
National-scale IT procurement

Senior Network Engineer

Healthcare
BIHS Hospital · BIRDEM
2005 – 2016
IT infrastructure for 1,000+ healthcare professionals
Near-zero downtime for clinical systems
20% licensing cost reduction
Hospital's first official website
05

Certifications

From Wharton to RHCE — breadth that validates depth

University of Michigan
AI
Generative AI in Business
University of Michigan
University of Pennsylvania
AI
AI in Business Strategy
Wharton · University of Pennsylvania
IBM
AI/ML
IBM AI Engineering
IBM · Professional Certificate
IBM
Data
IBM Data Science Professional
IBM · Professional Certificate
Google
Data
Google Advanced Data Analytics
Google · Professional Certificate
AWS
Cloud
AWS Certified
Amazon Web Services · Compute · Security · IAM
Red Hat
Infrastructure
Red Hat Certified Engineer
Red Hat · RHCE
Cisco
Network
Cisco CCNA
Cisco · Network Associate
Download CV (PDF)

Updated 2026 · Full project history, certifications, and client references