Vijay Venugopal

Software Engineer

Fredericton, New Brunswick, Canada1 yr 7 mos experience

Key Highlights

Expert in Kubernetes and cloud-native platforms.
Strong background in CI/CD and infrastructure-as-code.
Proven ability to navigate ambiguity in enterprise environments.

Stackforce AI infers this person is a Cloud-Native Infrastructure Engineer with expertise in Kubernetes and CI/CD.

Contact

Skills

Core Skills

KubernetesCi/cdMachine LearningDeep LearningBackend DevelopmentApi Development

Other Skills

DockerTerraformGitLab CI/CDHelmGrafanaGoogle Cloud PlatformPythonBashPyTorchNLPComputer VisionDjangoFlaskPostgreSQLData Science

About

I enjoy solving real-world problems and delivering value through a mix of technology, people, and well-defined processes. I’ve worked in enterprise environments where systems are regulated, changes are frequent, and requirements aren’t always clear. I’m comfortable navigating ambiguity, adapting quickly, and helping teams move forward without breaking reliability. My experience includes working on Kubernetes-based platforms, CI/CD pipelines, and infrastructure-as-code, with a strong focus on building repeatable, scalable patterns rather than one-off solutions. I’ve also been exposed to governance and operational practices that come with running platforms at scale in regulated institutions.

Experience

1 yr 7 mos

Total Experience

9 mos

Average Tenure

Current Experience

Bell

2 roles

Software Engineer - Platform DPI

Promoted

Jan 2023 – Feb 2026 · 3 yrs 1 mo · Fredericton, NB

Summary of Expertise
Supporting and operating production cloud-native platforms in an enterprise environment
Running and maintaining Kubernetes-based workloads on Google Kubernetes Engine (GKE)
Building and supporting CI/CD pipelines for containerized applications
Provisioning infrastructure and maintaining environment consistency using infrastructure-as-code
Deploying, upgrading, and migrating applications to Kubernetes-based platforms
Working within regulated enterprise environments and collaborating across multiple stakeholders
Troubleshooting production issues and improving platform reliability and observability
Summary of Tools & Technologies
Kubernetes (GKE), Docker, Google Artifact Registry
Terraform for infrastructure provisioning and environment standardization
GitLab CI/CD for build, test, and deployment automation
Helm and Kubernetes manifests for application deployments
Grafana for monitoring and observability
Google Cloud Platform (GKE, IAM, Cloud Functions)
Python and Bash for automation and operational tasks

KubernetesDockerTerraformGitLab CI/CDHelmGrafana+4

Sotware Developer

Jan 2022 – Dec 2022 · 11 mos · Fredericton, NB

University of new brunswick

Media Coordinator (Ocean Mapping Group)

Oct 2021 – Apr 2022 · 6 mos · Fredericton, New Brunswick, Canada

Developed a minimal website for the COMREN Network. Responsible for handling different social media accounts of the COMREN Network.
https://comren.vercel.app/

Quantrium

Software Engineer - AI/ML

Aug 2020 – Jan 2021 · 5 mos · Chennai, Tamil Nadu, India

Summary of Expertise
Developing and productionizing deep-learning models from theoretical data science concepts
Translating research-oriented models into deployable and scalable solutions
Working on applied machine learning problems such as CAPTCHA resolution systems
Managing experimentation workflows and model execution in remote compute environments
Collaborating across engineering and data teams to integrate ML solutions into applications
Summary of Tools & Technologies
for model development and experimentation
PyTorch for building and training deep-learning models
Google Colab Pro for training and experimentation
SSH-based workflows for remote execution and monitoring
NLP and computer vision techniques for applied ML use cases

Deep LearningPyTorchNLPComputer VisionMachine Learning

Kcube consultancy services (p) ltd

Software Developer

Jun 2019 – Aug 2020 · 1 yr 2 mos · Chennai, Tamil Nadu, India

Summary of Expertise
Developing backend microservices for a GIS-based Geo Web Maps (GWM) platform
Designing and implementing RESTful APIs for spatial and data-driven applications
Working closely with application requirements, data flow, and API integration
Implementing security mechanisms to protect APIs and sensitive data
Supporting application quality through structured testing and validation
Summary of Tools & Technologies
Python for backend development
Django and Flask REST Framework for building APIs
RSA and AES encryption techniques for API security
PostgreSQL and spatial data concepts (GIS context)
Unit, integration, regression, and manual testing practices