Frame the problem
Turn a vague request into users, constraints, risks and a useful outcome.
ABOUT REZWAN / REZTECHLABS
The engineer
behind the experiments.
I’m Rezwan Hassan, an Ottawa-based software developer working across backend systems, analytics and applied AI.
I start with the real problem: understand the workflow, clarify the requirements, design the system, then test and explain the result. My professional work includes enterprise simulation systems, backend analytics, predictive models, explainable AI prototypes and evaluation of an RAG-based natural-language to SQL database agent.
RezTechLabs is my independent research portfolio. Each project shows the question, feasibility, architecture, implementation and evidence behind a working prototype.
HOW I WORK
From a messy question
to a testable system.
I work across the full development path: problem framing, feasibility, system design, implementation, testing, evaluation and documentation.
Design the shape
Choose the data flow, interfaces, model boundaries and evidence needed to trust the result.
Build and test
Develop the smallest useful version, test the important paths and measure what changes.
Explain the decisions
Document the architecture, trade-offs and next steps so the work can be reviewed and extended.
SKILLS IN PRACTICE
What I bring to
each part of the build.
These are the areas where my work connects software engineering with applied AI and data.
BACKEND & SYSTEMS
Services that hold up under real workflows.
I design and troubleshoot backend services for complex applications, moving from requirements and data flow to APIs, integration points and operational reporting.
APPLIED AI
Models with a reason behind the answer.
I build and evaluate predictive models, retrieval systems and agent workflows with attention to grounded results, measurable behaviour and explanations people can inspect.
DATA & ANALYTICS
Turning system data into useful evidence.
I work with relational data, schema analysis, aggregation and anomaly signals so teams can understand what changed and decide what to investigate next.
DELIVERY & RELIABILITY
A working prototype is only the start.
I use tests, CI/CD, containers and documentation to make experiments repeatable and easier for another engineer to run, review and extend.
TECHNOLOGY STACK
Tools I use to
make the ideas real.
Selected technologies from recent engineering, analytics and AI work.
PyPython
☕Java
SQLSQL
RRAG
APIFastAPI
AWSAWS
◇Docker
AAngular
THE THROUGH-LINE
Java and Python services, relational data, retrieval and model evaluation, connected through APIs and delivered with tests, containers and clear notes.
PROFESSIONAL CONTRIBUTIONS
Engineering where
the details matter.
Selected contributions from my work at SimFront / Calian, alongside earlier automation, data science and machine learning experience.
RAG & AGENT EVALUATION
Making AI-generated SQL more dependable.
Contribute to the evaluation and improvement of an existing RAG-based NL-to-SQL database agent: schema-ingestion validation, knowledge enrichment, SQL guidance and failure analysis.
Designed an evaluation framework that runs natural-language test suites and checks SQL generation, execution, expected tables and columns, and unsupported requests. Produces structured evidence for regression testing.
APPLIED AI & AGENT ARCHITECTURE
Predictions that can be explained.
Designed predictive analytics prototypes using Random Forest and Decision Tree models, deterministic decision-path explanations and optional LLM-generated explanations.
Integrated Python services with Java through FastAPI. Developed an alternative A2A prototype separating prediction and LLM explainability into independently callable services.
BACKEND & ANALYTICS
Reliable services behind complex systems.
Develop and maintain backend services for simulation and analytics applications, including aggregation, filtering, computation and operational reporting.
Work across Java, Python, SQL, REST APIs and relational databases. Troubleshoot processor, integration and data-flow issues to improve workflow reliability.
EXPERIENCE
A foundation in building.
Full Stack Developer
SimFront / CalianBackend services, applied AI prototypes and evaluation of an existing enterprise RAG-based NL-to-SQL agent. Selected contributions include RAG evaluation, explainable AI prototypes and operational reporting.
Automation Engineer
Micro FocusAutomated testing for machine learning models and APIs, CI/CD pipelines, Python model workflows and AWS environments.
Data Scientist Intern
Micro FocusStatistical anomaly models, SQL analysis, data transformation and MLflow deployment.
Machine Learning Engineer Intern
Ericsson · Mitacs AccelerateTime-series forecasting, anomaly detection, ETL pipelines and monitoring for microservice environments.
EDUCATION
Research meets practice.
Master of Computer Science
Carleton University · Ottawa · 2020–2023
Research: automated real-time anomaly detection in microservice architectures.
BSc in Computer Science and Engineering
BRAC University · 2015–2018
SELECTED WRITING
Thinking behind the work.
Want to understand the work?
Ask about a project, a technical decision or the engineering behind a prototype.