Senior DevOps/Cloud Platform Engineer (AWS| Kubernetes|AI Infrastructure)

Design, deploy, and manage production-grade Kubernetes clusters using Amazon EKS .

Optimize Kubernetes workloads for high availability and resource utilization.

Configure namespaces, RBAC, network policies, autoscaling, ingress controllers, and service meshes where applicable.

Troubleshoot Kubernetes networking, scheduling, storage, and performance issues.

Manage rolling deployments, blue-green deployments, and canary releases.

Strong hands-on experience with:

Amazon EKS

Amazon EC2

Auto Scaling Groups

Elastic Load Balancer (ALB/NLB)

Amazon S3

Amazon RDS

AWS Lambda

Amazon ECR

Amazon CloudWatch

IAM

Route 53

VPC

NAT Gateway

Security Groups

AWS WAF

AWS Secrets Manager

Systems Manager (SSM)

CloudFront

EventBridge

SNS

SQS

Design and implement end-to-end CI/CD pipelines.

Automate application deployments across multiple environments.

Implement infrastructure automation and GitOps practices.

Build deployment strategies with minimal downtime.

Integrate automated testing, security scanning, and quality gates into CI/CD pipelines.

Experience with:

GitHub Actions

Jenkins

GitLab CI

ArgoCD

Develop and manage infrastructure using:

Terraform

AWS CloudFormation

Kubernetes YAML

Deploy and manage Small Language Models (SLMs) and Large Language Models (LLMs) in production environments.

Build scalable inference infrastructure for AI workloads.

Configure GPU-enabled Kubernetes nodes for model serving.

Optimize CPU and GPU utilization for AI inference.

Manage model deployments, scaling, versioning, and monitoring.

Support vector databases and AI inference services.

Work closely with AI/ML engineers to optimize model performance and infrastructure costs.

Deploy and manage Amazon RDS databases.

Monitor and optimize database performance.

Implement backup, recovery, and replication strategies.

Tune database configurations for high-throughput applications.

Monitor slow queries, indexing strategies, and connection pooling.

Collaborate with engineering teams on database performance optimization.

Implement monitoring and observability using:

CloudWatch

Prometheus

Grafana

ELK / OpenSearch

Loki

Responsibilities include:

Infrastructure monitoring

Application monitoring

Log aggregation

Alerting

Capacity planning

Incident response

Implement AWS security best practices.

Design secure IAM policies and access controls.

Manage secrets and encryption.

Perform infrastructure hardening.

Ensure compliance with: SOC 2 HITRUST HIPAA

SOC 2

HITRUST

HIPAA

Participate in security audits and vulnerability remediation.

Maintain audit logs and infrastructure documentation.

Continuously optimize AWS infrastructure costs.

Right-size EC2 instances and EKS node groups.

Optimize storage and networking costs.

Implement Savings Plans and Reserved Instances where appropriate.

Optimize GPU utilization for AI workloads.

Monitor cloud spending and recommend cost-saving initiatives.

Amazon Web Services (AWS)

Amazon ECS

Lambda

ECR

Systems Manager

WAF

Secrets Manager

Docker

Kubernetes

Helm

Kubernetes Networking

Ingress Controllers

Horizontal & Vertical Pod Autoscaling

CloudFormation

Customize

PostgreSQL

MySQL

Redis

Performance tuning

Replication

Backup & recovery

Connection pooling

Query optimization

Experience deploying and managing:

LLMs and SLMs

GPU-based inference workloads

NVIDIA GPU infrastructure

CUDA-enabled environments (preferred)

Hugging Face models

vLLM, Ollama, or similar inference frameworks

Model serving and autoscaling

ELK/OpenSearch

Strong understanding of:

RBAC

Network Security

Encryption

Secrets Management

Vulnerability Management