About the Role

We are looking for a highly skilled Senior DevOps / Cloud Platform Engineer with 5–8 years of experience in designing, deploying, and managing secure, scalable, and highly available cloud infrastructure on AWS.

The ideal candidate will have extensive hands-on experience with AWS, Amazon EKS, Kubernetes, CI/CD automation, infrastructure as code, and cloud security. This role also requires experience supporting AI workloads, including deploying and optimizing Large Language Models (LLMs) on CPU and GPU infrastructure.

You will work closely with software engineers, AI/ML engineers, architects, and security teams to build and maintain cloud platforms that are secure, resilient, cost-efficient, and compliant with SOC 2 and HITRUST requirements. Key Responsibilities

Cloud Infrastructure

Design, deploy, and manage scalable, highly available, and secure AWS infrastructure.

Architect cloud environments capable of supporting enterprise-scale applications and AI workloads.

Optimize infrastructure for performance, reliability, scalability, and cost.

Implement high availability, disaster recovery, backup, and failover strategies.

Design multi-workplace infrastructure (Development, QA, UAT, Production). Kubernetes & Container Platform

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. AWS Services

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 CI/CD & DevOps Automation

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 Infrastructure as Code

Develop and manage infrastructure using:

Terraform

AWS CloudFormation

Kubernetes YAML AI & LLM Infrastructure

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.

Database

Infrastructure & Performance

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. Monitoring & Observability

Implement monitoring and observability using:

CloudWatch

Prometheus

Grafana

ELK / OpenSearch

Loki

Responsibilities include

Infrastructure monitoring

Application monitoring

Log aggregation

Alerting

Capacity planning

Incident response Security & Compliance

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

Participate in security audits and vulnerability remediation.

Maintain audit logs and infrastructure documentation. Cost Optimization

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. Requirements

Required Qualifications

Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.

5–8 years of hands-on experience in DevOps, Cloud Engineering, or Platform Engineering.

Strong experience designing and managing production AWS environments.

Extensive experience with Kubernetes and Amazon EKS.

Experience managing enterprise-scale cloud infrastructure.

Proven experience automating deployments and infrastructure management.

Required Technical Skills

Cloud Platforms

Amazon Web Services (AWS)

AWS Services

Amazon EC2

Amazon EKS

Amazon ECS

Amazon RDS

Amazon S3

Lambda

ECR

CloudFront

IAM

Route 53

VPC

CloudWatch

Systems Manager

WAF

Secrets Manager

SNS

SQS

EventBridge

Containers & Orchestration

Docker

Kubernetes

Amazon EKS

Helm

Kubernetes Networking

Ingress Controllers

Horizontal & Vertical Pod Autoscaling

Infrastructure as Code

Terraform

CloudFormation

Helm

Customize

CI/CD

GitHub Actions

Jenkins

GitLab CI

ArgoCD

Databases

Amazon RDS

PostgreSQL

MySQL

Redis

Experience with

Performance tuning

Replication

Backup & recovery

Connection pooling

Query optimization

AI Infrastructure

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

Monitoring & Logging

Prometheus

Grafana

CloudWatch

ELK/OpenSearch

Loki

Security & Compliance

Strong understanding of

SOC 2

HITRUST

HIPAA

IAM

RBAC

Network Security

Encryption

Secrets Management

Vulnerability Management

Preferred Qualifications

AWS Certified Solutions Architect – Professional or Associate.

AWS Certified DevOps Engineer – Professional.

Certified Kubernetes Administrator (CKA) or Certified Kubernetes Application Developer (CKAD).

Experience with AI platforms, MLOps, or GPU infrastructure.

Experience deploying high-availability, multi-tenant SaaS applications.

Familiarity with service mesh technologies (Istio or Linkerd) is a plus.

📌 Senior DevOps/Cloud Platform Engineer (AWS| Kubernetes|AI Infrastructure) (Madhya Pradesh)
🏢 Annova Solutions
📍 Madhya Pradesh