AI Engineer for Kubernetes & AI Infrastructure – Pakistan
About Our Engineers
This engineer brings 5+ years of DevOps and AI experience, helping SaaS and startup teams containerize GPT-powered tools, automate model deployments, and optimize compute usage using Kubernetes. They’re skilled at Helm, secrets management, and building fault-tolerant AI stacks.
Key Expertise & Skills
Kubernetes Cluster Setup
GPT Model Deployment
Helm Charts
Auto-Scaling AI Services
ML Workflow Orchestration
Containerization
GPU Node Management
CI/CD Pipelines for AI Apps
Technologies & Tools
Kubernetes
Helm
Docker
OpenAI API
TensorFlow Serving
Prometheus
Grafana
GitHub Actions
NGINX Ingress
AWS EKS
GCP GKE
Secrets Manager
ArgoCD
Terraform
Projects Our Engineers Have Worked On
- Scalable GPT Deployment on Kubernetes – Built a full-stack deployment pipeline for GPT APIs with autoscaling, logging, and secure endpoints using Helm, deployed across 3 environments.
AI Model Inference Service in GKE – Designed and deployed a GPU-backed Kubernetes cluster on GCP for image and text inference models with traffic load balancing.
Secure Whisper Integration – Containerized Whisper API, set up K8s secrets, and automated voice file processing with horizontal pod autoscaling for a customer support tool.
AI-Enhanced Form Processing System – Created a microservices-based system where form uploads are parsed via GPT on Kubernetes; logs, cache, and worker jobs run independently.
Zero-Downtime AI App Updates – Built a CI/CD pipeline with GitHub Actions + Helm for updating GPT-based SaaS features without affecting live users.
AI Monitoring Dashboard – Integrated Prometheus and Grafana with K8s pods to monitor latency, token usage, and memory across AI containers in real time.
Who Should Hire This Engineer?
AI startups running models at scale
SaaS teams launching containerized GPT tools
DevOps leads automating ML systems
Founders needing reliable OpenAI deployment pipelines
Tech companies building resilient AI infrastructure