# 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 with 9 years of continuous IC progression. Building LLM ensemble labelling pipelines, knowledge distillation systems, and sub-50ms intent classification at Canada's largest bank.

## About

Nine years at Canada's largest bank. From intern to Staff. Always building.

Nearly a decade ago, I joined RBC as an intern with a Statistics degree and a curiosity about what production software really looks like at scale. That curiosity led me through six distinct engineering disciplines — ChatOps, SRE, security platforms, developer experience — before arriving at what I find most compelling: building AI systems that work at the intersection of research and production.

Today, I lead AI engineering for an end-to-end call center platform at Canada's largest bank. My current work spans LLM ensemble labelling pipelines, knowledge distillation of large embedding models, and intent classification systems routing 14,000+ banking intents with under 50 ms latency on CPU-only infrastructure. The challenge is bridging the gap between what's possible in an AI research lab and what can actually be deployed reliably at enterprise scale.

My foundation is a Statistics degree from the University of Toronto — which means I think in distributions, not just decisions. I care about why models behave the way they do, not just whether they hit a benchmark. That mathematical rigour shapes how I approach everything from embedding fine-tuning to production observability.

Outside work, I maintain a homelab, experiment with network engineering, and prototype ideas. I'm interested in the long game of technology: systems that age gracefully, teams that grow sustainably, and engineering that compounds.

## Key Statistics

- **9+** Years at RBC
- **6** Roles Progressed
- **14K+** Intents Classified
- **50ms** CPU Inference Latency

## Professional Experience (Full Detail)

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

  - Architect end-to-end AI call center platform integrating SIP telephony, real-time speech-to-text transcription, and LLM summarization pipelines processing thousands of daily banking interactions.
  - Engineered LLM ensemble labelling pipeline using GPT-4o mini, GPT-4.1 mini, and GPT-5 mini with consensus voting and tie-breaking escalation to larger thinking models; generated high-quality training labels at scale for fine-tuning.
  - Implemented knowledge distillation workflow: used LLM ensemble as teacher to fine-tune Arctic Embed 2.0 Large as domain-specific student model for banking intent semantics.
  - Built continuous training MLOps pipeline on S3 + Apache Airflow; automated dataset ingestion, model retraining, evaluation, and deployment to OpenShift.
  - Benchmarked SVM (RBF kernel), logistic regression, SetFit (head and full fine-tune), centroid, and fine-tuned Arctic Embed classifiers for production intent routing.
  - Led BART intent classification system using Jina v3 / multilingual-e5 with ONNX Runtime; reduced inference latency from 8 s → 50 ms on CPU-only OpenShift 4.
  - Built Spring Boot microservices with k-NN routing of 14,000+ banking intents across 110 workflow categories; achieved 95% semantic naming accuracy via LLM-assisted clustering.

Tech stack: Python · Java · Spring Boot · ONNX Runtime · Arctic Embed 2.0 · Jina v3 · multilingual-e5 · SetFit · SVM · GPT-4/4o/5 · Claude · S3 · Apache Airflow · OpenShift 4 · AWS Transcribe/Bedrock

### Staff Software Engineer
**Security Platforms** — Royal Bank of Canada | Toronto, ON | Jul 2024 – Sep 2025
Tags: security, backend

  - Built centralized vulnerability triage platform spanning Canada, US, and UK subsidiaries; reduced security assessment time by 60% across multi-subsidiary operations.
  - Designed data ingestion pipelines integrating Snyk, NexusIQ, Kenna, Tenable, and Aqua security feeds into unified Snowflake data warehouse.
  - Delivered full-stack platform using React, FastAPI, Snowflake, Redis, and SQL Server deployed on OpenShift.

Tech stack: React · 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 – Jul 2024
Tags: sre, devops

  - Automated large-scale chaos experiments on VMs and Kubernetes namespaces across AKS, OpenShift, and VMware using Tanium and Gremlin APIs; reduced experiment setup time by 90%.
  - Architected SRE data enrichment pipelines integrating PagerDuty, ServiceNow, and ELK Stack; reduced mean time to detect (MTTD) by 30%.
  - Built observability data pipelines using Python, Pandas, Oracle DB, SQL Server, and PostgreSQL to feed critical 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 – Aug 2022
Tags: backend, devops

  - Architected mTLS API gateway connecting Slack applications to internal banking services using Golang, HashiCorp Vault, GitHub API, and Nginx on OpenShift; enabled enterprise ChatOps saving hundreds of engineer-hours weekly.
  - Built bulk employee onboarding service reducing provisioning time from hours to minutes using Golang, Gin, PingFederate SSO, and ServiceNow on OpenShift.
  - Developed metrics pipeline tracking open-source/innersource artifact reuse across the organization; delivered executive dashboards using Logstash, Kibana, Redis, NexusIQ, and Artifactory.
  - Created innersource SDKs in Python/Golang reducing Slackbot onboarding from 2 weeks to 2 days for 15+ teams.

Tech stack: Go · Gin · HashiCorp Vault · Nginx · Elasticsearch · Logstash · Kibana · Redis · NexusIQ · Artifactory · MariaDB · Java · Python · OpenShift

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

  - Built internal Stack Overflow-style Q&A platform with gamification; increased answered-question rate by 25% and connected developers across 10+ lines of business.
  - Architected production-ready WebSocket Slackbot pub-sub framework scaling horizontally without message duplication using Golang and RabbitMQ.

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

### Software Developer Intern → SRE Intern
**3 terms** — Royal Bank of Canada | Toronto, ON | May 2017 – Aug 2019
Tags: ai, devops

  - Implemented ChatOps into DevOps pipeline via scalable Slackbot saving 20+ engineer-hours per microservice per week using Python, MongoDB, Redis, RASA NLU, Docker, OpenShift, and Kubernetes.
  - Built ML-based SRE pipeline improving application resilience and reducing toil/recovery times using Elasticsearch, Logstash, Kafka, and IBM CDP.
  - Developed automation test portal reducing test execution time by 80%, saving $100k+ annually.
  - Built intelligent war room using Raspberry Pi, Python, Snips, PagerDuty, Moogsoft, and ServiceNow to surface solution vectors 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 – Feb 2018
Tags: backend

  - Developed web application for the History Department to track course enrollment trends; built with Django, Bootstrap, Redis, jQuery, Nginx, Chart.js, and PostgreSQL.

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

## Projects (Full Detail)

### BART Intent Router — Knowledge Distillation Pipeline
LLM ensemble labelling pipeline (GPT-4o mini + GPT-4.1 mini + GPT-5 mini with consensus voting) used as teacher to fine-tune Arctic Embed 2.0 Large as a domain-specific student model. Routes 14,000+ banking intents across 110 categories with sub-50ms latency on CPU-only OpenShift 4.
Tags: Python, ONNX Runtime, Arctic Embed 2.0, LLM Ensemble, Apache Airflow, OpenShift
Metrics: <50ms CPU inference | 14K+ intents | 95% naming accuracy
Access: Internal/proprietary

### AI Call Center Platform — Real-time SIP + STT + LLM
End-to-end AI-powered platform integrating SIP telephony, real-time speech-to-text transcription, and LLM summarization pipelines. Processes thousands of daily banking interactions with automated intent classification and agent-assist workflows.
Tags: Java, Spring Boot, AWS Transcribe, AWS Bedrock, GPT-4, Claude, OpenShift
Metrics: 1000s of daily interactions | Real-time SIP | Multi-model LLM
Access: Internal/proprietary

### Vulnerability Triage Platform — Multi-Subsidiary Security Data Pipeline
Centralized vulnerability management platform spanning Canada, US, and UK subsidiaries. Unified data ingestion from Snyk, NexusIQ, Kenna, Tenable, and Aqua into a Snowflake warehouse with real-time triage dashboards.
Tags: React, FastAPI, Snowflake, Redis, Python, OpenShift
Metrics: 60% faster assessments | 3 global subsidiaries | 5 security feeds
Access: Internal/proprietary

### Chaos Engineering Platform — Automated Resilience Testing at Scale
Automated large-scale chaos experiments across AKS, OpenShift, and VMware clusters using Tanium and Gremlin APIs. Enables self-service chaos scheduling for VM and Kubernetes workloads across multi-cloud infrastructure.
Tags: Python, Go, Tanium API, Gremlin, Kubernetes, AKS
Metrics: 90% setup reduction | AKS + OpenShift + VMware | 100s of VMs/pods
Access: Internal/proprietary

### MirrML — ML Clothing Style Classifier — UofTHacksIV
Flask + Clarifai Image Recognition API; clothing style classifier (business/casual/evening) via neural network trained on scraped image data. Matches users with friends with similar style profiles.
Tags: Python, Flask, Clarifai, ML, Bootstrap
Link: https://github.com/samhaque/UofTHacksIV_MirrML

### LendR — NFC Micro-Lending App — TD Finhacks
Android app using NFC technology for social micro-financing. Built a Karma system to incentivize repayment; negative karma reduces borrowing limits. Custom 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 – Present**: Staff Software Engineer — AI Advice Centre — LLM ensemble labelling, knowledge distillation, Arctic Embed fine-tuning (current)
- **2024 – 2025**: Staff Software Engineer — Security Platforms — Centralized vulnerability triage across global subsidiaries
- **2022 – 2024**: Lead Software Engineer — SRE & Chaos — Chaos engineering & SRE enrichment pipelines
- **2020 – 2022**: Senior Software Developer — Dev Experience — Enterprise ChatOps, mTLS gateway & innersource SDKs
- **2019 – 2020**: Software Developer — Dev Experience — Internal Q&A platform & WebSocket pub-sub Slackbot framework
- **2017 – 2019**: Software Developer Intern → SRE Intern — ChatOps automation with RASA NLU + ML-based SRE pipeline

## Education

**Honours B.Sc., Statistics** — University of Toronto (2015 – 2021, Toronto, ON)
  Double Minor: Geographic Information Systems (GIS) & Psychology
  Activities: VP of Development, AMACSS (Association of Mathematical & Computer Science Students)
**Engineering Studies** — Ontario Tech University (2024 – Present, Oshawa, ON)

## Volunteering

- **VP of Development** — AMACSS — Association of Mathematical & Computer Science Students (Jun 2018 – Apr 2020): Led development projects and technical initiatives for the mathematics and computer science student association at University of Toronto Scarborough.
- **Developer / SRE** — Computer Science Enrichment Club (CSEC, UofT) (Aug 2016 – Apr 2020): Contributed to club infrastructure and development projects, mentored students in software engineering and site reliability engineering fundamentals.
- **Web Developer** — Women in Computer Science, Statistics & Mathematics (WiCSM) (Aug 2020 – Present): Built and maintained the organization's web presence, supporting an initiative that 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,
Sub-50ms Inference, CPU-only ML, Banking AI, Call Center AI, Speech-to-Text, LLM Summarization,
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,
specializing in AI/ML systems and platform engineering. He builds LLM ensemble labelling
pipelines, knowledge distillation systems, and sub-50ms intent classification at scale.
Website: https://www.samiulhaque.com