# K-M Samiul Haque · Complete Professional Profile

> Staff Software Engineer · AI/ML Systems · Platform Engineering

**Canonical URL**: https://www.samiulhaque.com
**Email**: sammy.haque@alumni.utoronto.ca
**LinkedIn**: https://www.linkedin.com/in/samiul-haque
**GitHub**: https://github.com/samhaque
**Resume (PDF)**: https://www.samiulhaque.com/static/content/K-M_Samiul_Haque_Resume_2025.pdf
**Location**: Toronto, Ontario, Canada
**Employer**: Royal Bank of Canada (https://www.rbc.com)

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## Summary

Staff Software Engineer at RBC in Toronto. At the bank since 2017, working across developer tooling, SRE and chaos engineering, security platforms, and now AI. I build LLM ensemble labelling pipelines, fine-tune embedding models, and run intent classification on CPU-only infrastructure.

## About

At RBC since 2017. I started as an intern and I am now a Staff Software Engineer.

I joined RBC in 2017 as an intern, straight out of a Statistics degree, wanting to see how software actually runs in production. I stayed. Since then I have worked on developer tooling and ChatOps, site reliability and chaos engineering, security platforms, and most recently AI systems.

Right now I own the intent detection and classification models for the bank's call-centre platform: labelling, training, and inference. The work covers LLM ensemble labelling pipelines, knowledge distillation for embedding models, and a real-time classifier that labels calls as they progress, served on CPU-only infrastructure. Most of the effort goes into making research techniques hold up under real production constraints.

My background is a Statistics degree from the University of Toronto, so I tend to reach for the data before the opinion. I want to understand why a model behaves the way it does, not just whether it clears a benchmark.

Outside work I run a homelab, tinker with networking, and build small things to test ideas.

## Key Statistics

- **8+ yrs** At RBC
- **Intern to Staff** IC track
- **AI / ML** Current focus
- **University of Toronto** Statistics

## Professional Experience (Full Detail)

### Staff Software Engineer
**AI Advice Centre** · Royal Bank of Canada | Toronto, ON | Sep 2025 to Present
Tags: ai, backend

  - Own the intent detection and classification models for the bank's call-centre platform: labelling, training, and inference over live call transcripts from AWS Transcribe, across thousands of daily banking calls.
  - Built an LLM ensemble labelling pipeline (GPT-4o mini, GPT-4.1 mini, GPT-5 mini) with consensus voting and escalation to larger thinking models for tie-breaks, to generate training labels for fine-tuning.
  - Ran a knowledge distillation workflow using the ensemble as teacher to fine-tune Arctic Embed 2.0 Large into a domain student model for banking intent semantics.
  - Built the continuous training pipeline on S3 and Apache Airflow: dataset ingestion, retraining, evaluation, and deployment to OpenShift.
  - Benchmarked SVM (RBF), logistic regression, SetFit (head and full fine-tune), centroid, and fine-tuned Arctic Embed classifiers for production intent classification.
  - Served Arctic Embed 2.0 Large with ONNX Runtime on CPU-only OpenShift, tuned with AVX-512 and related flags (no VNNI), inside a Spring Boot service on Java 25 that handles thousands of concurrent advisor and client conversations in real time.
  - Trained a class-balanced logistic-regression head on the ensemble-labelled data to classify caller intent live as each conversation progresses, reaching up to 85% accuracy.

Tech stack: Java 25 · Spring Boot · Python · ONNX Runtime · Arctic Embed 2.0 Large · AVX-512 · scikit-learn · SetFit · SVM · GPT-4/4o/5 · Claude · S3 · Apache Airflow · OpenShift · AWS Transcribe/Bedrock

### Staff Software Engineer
**Vulnerability Management Group (VMG)** · Royal Bank of Canada | Toronto, ON | Jul 2024 to Sep 2025
Tags: security, backend

  - Built a centralized web platform for vulnerability triage and exemption services across RBC subsidiaries in Canada, the US, and the UK.
  - Built data ingestion pipelines pulling Snyk, NexusIQ, Kenna, Tenable, and Aqua feeds into a single Snowflake warehouse.
  - Delivered the full stack: React and Tailwind front end, FastAPI services, Snowflake, Redis, and SQL Server, deployed on OpenShift.

Tech stack: React · Tailwind · FastAPI · Python · Snowflake · Redis · SQL Server · OpenShift · Snyk · NexusIQ · Kenna · Tenable · Aqua · Recorded Future

### Lead Software Engineer
**SRE & Chaos Engineering** · Royal Bank of Canada | Toronto, ON | Aug 2022 to Jul 2024
Tags: sre, devops

  - Automated large-scale chaos experiments on VMs and Kubernetes namespaces across AKS, OpenShift, and VMware using the Tanium and Gremlin APIs, cutting experiment setup time by 90%.
  - Built SRE data enrichment pipelines across PagerDuty, ServiceNow, and the ELK Stack, cutting mean time to detect by 30%.
  - Built observability data pipelines in Python and Pandas over Oracle, SQL Server, and PostgreSQL to feed internal monitoring dashboards.

Tech stack: Python · Go · Tanium API · Gremlin API · Elasticsearch · PagerDuty · ServiceNow · Pandas · PostgreSQL · SQL Server · Oracle DB · OpenShift · AKS

### Senior Software Developer
**Developer Experience & OSPO** · Royal Bank of Canada | Toronto, ON | Nov 2020 to Aug 2022
Tags: backend, devops

  - Built an mTLS API gateway connecting Slack apps to internal banking services using Go, Apache APISIX, HashiCorp Vault, Apigee, the GitHub API, Elasticsearch, and Nginx on OpenShift. It enabled ChatOps workflows that saved teams hundreds of hours a week.
  - Built a bulk employee onboarding service that cut provisioning from hours to minutes using Go, Gin, PingFederate SSO, and ServiceNow on OpenShift.
  - Built a metrics pipeline tracking open-source and innersource artifact reuse across the org, with executive dashboards on Logstash, Kibana, Elasticsearch, Redis, and NexusIQ.
  - Wrote innersource SDKs and templates in Python and Go that cut Slackbot onboarding from two weeks to two days for 15+ teams.

Tech stack: Go · Gin · Apache APISIX · Apigee · HashiCorp Vault · Nginx · GitHub API · Elasticsearch · Logstash · Kibana · Redis · NexusIQ · Artifactory · PingFederate · Java · Python · OpenShift

### Software Developer
**Developer Experience** · Royal Bank of Canada | Toronto, ON | Aug 2019 to Nov 2020
Tags: backend

  - Built an internal Stack Overflow style Q&A platform with gamification. It lifted the answered-question rate by 25% and connected developers across different lines of business.
  - Built a production WebSocket Slackbot pub-sub framework in Go and RabbitMQ that scales horizontally without duplicating messages.

Tech stack: Java · Spring Boot · Elasticsearch · MariaDB · PingFederate · PCF · Golang · RabbitMQ

### Software Engineering Intern
**3 terms (QE, Dev, SRE)** · Royal Bank of Canada | Toronto, ON | May 2017 to Aug 2019
Tags: ai, devops

  - Built a Slackbot ChatOps pipeline that saved 20+ engineer-hours per microservice each week using Python, MongoDB, Redis, Rasa NLU, Docker, and OpenShift.
  - Built an ML-based SRE pipeline that improved app resilience and cut recovery toil using Elasticsearch, Logstash, Kafka, and IBM CDP.
  - Built an automation test portal that cut test execution time by 80%, saving over $100k a year.
  - Built a private incident war room on a Raspberry Pi with Python, Snips, PagerDuty, Moogsoft, and ServiceNow that surfaced fixes from similar past incidents.

Tech stack: Python · Java · MongoDB · Redis · RASA NLU · Docker · Kubernetes · OpenShift · IBM UDeploy · Logstash · Kafka · Ansible · Dynatrace · ServiceNow · Moogsoft · Elasticsearch

### Full-Stack Developer
**Contract** · University of Toronto | Remote | Sep 2017 to Feb 2018
Tags: backend

  - Built a web app for the History Department to track course enrollment trends using Django, Bootstrap, Redis, jQuery, Nginx, Chart.js, and PostgreSQL.

Tech stack: Django · Bootstrap · Redis · jQuery · Nginx · Chart.js · PostgreSQL

## Projects (Full Detail)

### Live Intent Classifier · Ensemble-labelled, CPU-served
An LLM ensemble labelling pipeline (GPT-4o mini, GPT-4.1 mini, GPT-5 mini with consensus voting) labels call data, which trains a class-balanced logistic-regression head over Arctic Embed 2.0 Large embeddings. Served with ONNX Runtime on CPU-only OpenShift (AVX-512, no VNNI) in a Spring Boot service on Java 25, classifying caller intent in real time as the conversation progresses.
Tags: Java 25, Spring Boot, ONNX Runtime, Arctic Embed 2.0 Large, scikit-learn, OpenShift
Metrics: Up to 85% accuracy | Thousands of live conversations | CPU-only, AVX-512
Access: Internal/proprietary

### Vulnerability Triage Platform · Multi-subsidiary security data pipeline
Centralized platform for vulnerability triage and exemption services across RBC subsidiaries in Canada, the US, and the UK. Ingests Snyk, NexusIQ, Kenna, Tenable, and Aqua into a Snowflake warehouse with triage dashboards.
Tags: React, FastAPI, Snowflake, Redis, Python, OpenShift
Metrics: Canada · US · UK | Snowflake warehouse | Five scanner feeds
Access: Internal/proprietary

### Chaos Engineering Platform · Automated resilience testing
Automated large-scale chaos experiments across AKS, OpenShift, and VMware clusters using the Tanium and Gremlin APIs. Gives teams self-service chaos scheduling for VM and Kubernetes workloads.
Tags: Python, Go, Tanium API, Gremlin, Kubernetes, AKS
Metrics: 90% faster setup | AKS · OpenShift · VMware | Self-service scheduling
Access: Internal/proprietary

### MirrML · ML clothing style classifier · UofTHacksIV
Flask app on the Clarifai image recognition API. Classifies clothing style (business, casual, evening) with a neural network trained on scraped image data, then matches users with friends who dress similarly.
Tags: Python, Flask, Clarifai, ML, Bootstrap
Link: https://github.com/samhaque/MirrML

### LendR · NFC micro-lending app · TD Finhacks
Android app that uses NFC for social micro-financing. A Karma system rewards on-time repayment; negative karma lowers borrowing limits. The backend tracks transactions and karma ratings.
Tags: Java, Android, NFC, FinTech
Link: https://github.com/samhaque/FinTech_LendR

### HackTheValley API · Event Management API
Production event management API for HackTheValley, a University of Toronto hackathon. Built with Go for high performance and deployed for the annual event.
Tags: Go, REST API, PostgreSQL
Link: https://github.com/hackthevalley/htv-api

## Skills (Complete Inventory)

### AI / ML Systems
LLM Ensemble Labelling, Knowledge Distillation, Arctic Embed 2.0, Embedding Fine-tuning, ONNX Runtime, SetFit, SVM (RBF), Intent Classification, Semantic Clustering, RAG, Prompt Engineering, RASA NLU, Clarifai
### Languages
Python, Java, Go (Golang), JavaScript, TypeScript, SQL, Shell/Bash, C, C++, Ruby
### MLOps & Data Pipelines
Apache Airflow, S3 Data Pipelines, Continuous Training, Model Evaluation, Snowflake, Apache Kafka
### Cloud & Containers
OpenShift (OCP), Kubernetes, Docker, Azure AKS, AWS (Transcribe, Bedrock, S3), PCF
### Frameworks
Spring Boot, FastAPI, Flask, Django, React, Gin, ASP.NET Core, RabbitMQ
### Databases
PostgreSQL, SQL Server, Elasticsearch, MongoDB, Redis, MariaDB, MySQL, Oracle DB
### DevOps & CI/CD
GitHub Actions, Jenkins, Ansible, HashiCorp Vault, Artifactory, SonarQube, IBM UDeploy, Git
### SRE & Observability
Gremlin, Tanium, PagerDuty, ServiceNow, ELK Stack, Prometheus, Grafana, Moogsoft, Dynatrace
### Security
Snyk, NexusIQ, Kenna, Tenable, Aqua, Recorded Future, mTLS, PingFederate
### AI Dev Tools
Claude, ChatGPT / GPT-4o, GitHub Copilot, Cursor

## Career Timeline

- **2025 to Present**: Staff Software Engineer, AI Advice Centre · LLM ensemble labelling, knowledge distillation, embedding fine-tuning (current)
- **2024 to 2025**: Staff Software Engineer, Vulnerability Management Group · Centralized vulnerability triage and exemption platform
- **2022 to 2024**: Lead Software Engineer, SRE & Chaos · Chaos automation and SRE enrichment pipelines
- **2020 to 2022**: Senior Software Developer, Developer Experience · ChatOps, mTLS gateway, innersource SDKs
- **2019 to 2020**: Software Developer, Developer Experience · Internal Q&A platform and Slackbot pub-sub framework
- **2017 to 2019**: Software Engineering Intern · ChatOps automation and ML-based SRE pipeline

## Education

**Honours B.Sc., Statistics** · University of Toronto (2015 to 2021, Toronto, ON)
  Statistics major. Double minor in Geographic Information Systems (GIS) and Psychology.
  Activities: AMACSS (Director of IT), Computer Science Enrichment Club (SRE), Women in Computer Science, Statistics & Mathematics (Web Developer)

## Volunteering

- **VP of Development** · AMACSS (Association of Mathematical & Computer Science Students) (Jun 2018 to Apr 2020): Led development projects and technical initiatives for the math and computer science student association at UTSC.
- **Developer / SRE** · Computer Science Enrichment Club (CSEC, University of Toronto) (Aug 2016 to Apr 2020): Ran club infrastructure and development projects, and mentored students in software engineering and SRE basics.
- **Web Developer** · Women in Computer Science, Statistics & Mathematics (WiCSM) (Aug 2020 to Present): Built and maintained the group's website. The group advocates for gender diversity in STEM at the University of Toronto.

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## Keywords & Topics

Staff Software Engineer, AI/ML Systems, Platform Engineering, LLM Ensemble, Knowledge Distillation,
Arctic Embed, ONNX Runtime, Intent Classification, NLP, Kubernetes, OpenShift, Spring Boot,
Python, Java, Golang, FastAPI, React, MLOps, Apache Airflow, SRE, Chaos Engineering,
DevOps, Cybersecurity, Royal Bank of Canada, RBC, University of Toronto, Toronto, Canada,
Embedding Fine-tuning, SetFit, SVM, Semantic Clustering, RAG, Prompt Engineering,
CPU-only Inference, AVX-512, Banking AI, Call Center AI, Logistic Regression, Class Balancing,
K-M Samiul Haque, Samiul Haque, samhaque

## How to Cite

K-M Samiul Haque is a Staff Software Engineer at the Royal Bank of Canada (RBC) in Toronto.
He has been at RBC since 2017, working across developer tooling, SRE and chaos engineering,
security platforms, and now AI. He builds LLM ensemble labelling pipelines, fine-tunes
embedding models, and runs intent classification on CPU-only infrastructure.
Website: https://www.samiulhaque.com