Senior DevOps Engineer (AWS-Focused)

Position Overview

We are seeking a highly experienced Senior DevOps Engineer to design, build, and operate scalable cloud infrastructure with a primary focus on AWS. The ideal candidate has extensive experience managing complex distributed systems, deploying machine learning workloads, implementing secure and automated infrastructure, and supporting multi-service architectures in production environments.

This role requires a strong infrastructure engineering mindset, deep cloud expertise, and the ability to collaborate with software, data, and machine learning teams to deliver highly available and scalable platforms.

Key ResponsibilitiesCloud Infrastructure & Platform Engineering

Design, implement, and manage cloud-native infrastructure primarily on AWS.

Build and maintain highly available, fault-tolerant, and scalable production environments.

Develop Infrastructure as Code (IaC) using tools such as Terraform or CloudFormation.

Establish cloud governance, security, networking, and operational best practices.

Optimize infrastructure costs while maintaining performance and reliability.

Kubernetes & Container Orchestration

Design and operate production Kubernetes environments.

Manage containerized applications and platform services across multiple environments.

Implement autoscaling, service discovery, ingress routing, and workload isolation strategies.

Optimize cluster performance, reliability, and resource utilization.

Machine Learning Infrastructure

Deploy, manage, and scale machine learning workloads in production environments.

Support GPU-based and CPU-based workloads for training and inference.

Build deployment pipelines for ML models and AI services.

Collaborate with ML engineers and data scientists to operationalize machine learning systems.

Manage model-serving infrastructure and inference scaling requirements.

Networking & Multi-Service Architecture

Design and maintain complex networking architectures across cloud environments.

Configure and manage:

Load balancers

API gateways

Service meshes

Reverse proxies

Traffic routing policies

Support multi-service and microservice-based platforms.

Implement secure communication between distributed services.

CI/CD & Automation

Build and maintain robust CI/CD pipelines.

Automate infrastructure provisioning, deployments, testing, and operational workflows.

Implement deployment strategies including:

Blue/green deployments

Canary releases

Rolling updates

Improve engineering productivity through platform automation.

Reliability & Observability

Implement monitoring, logging, tracing, and alerting solutions.

Establish SLOs, SLIs, and operational metrics.

Lead incident response and root-cause analysis activities.

Continuously improve platform reliability and operational excellence.

Required QualificationsExperience

5+ years of DevOps, Platform Engineering, Site Reliability Engineering (SRE), or Infrastructure Engineering experience.

Proven experience operating production environments at scale.

Experience supporting mission-critical systems with high availability requirements.

AWS Expertise

Strong hands-on experience with AWS services including:

EC2

VPC

IAM

Route 53

Application Load Balancer (ALB)

Network Load Balancer (NLB)

ECS and/or EKS

S3

RDS

ElastiCache

CloudWatch

Secrets Manager

Lambda (preferred)

Kubernetes & Containers

Extensive Kubernetes production experience.

Strong understanding of:

Networking

Ingress controllers

Storage management

Cluster operations

Security policies

Advanced Docker experience.

Infrastructure as Code

Experience with:

Terraform (strongly preferred)

CloudFormation

Pulumi (nice to have)

CI/CD

Hands-on experience with one or more:

GitHub Actions

GitLab CI/CD

Jenkins

ArgoCD

CircleCI

Networking

Strong understanding of:

DNS

TLS/SSL

VPNs

Routing

Reverse proxies

Service-to-service communication

Network security architecture

Preferred QualificationsGoogle Cloud Platform Exposure

Experience with:

GKE

Cloud Run

Compute Engine

Cloud Storage

IAM

VPC Networking

Machine Learning Infrastructure

Experience deploying and operating:

ML inference services

GPU workloads

Model-serving platforms

MLOps workflows

Vector databases

LLM applications and AI infrastructure

Observability & Operations

Experience with:

Prometheus

Grafana

OpenTelemetry

ELK/OpenSearch

Datadog

New Relic

Security

Cloud security best practices.

IAM design and access controls.

Secrets management.

Vulnerability management and compliance frameworks.

Required Application Submission

Applicants should include:

Resume/CV

LinkedIn profile (optional)

GitHub profile (if applicable)

Description of the largest production infrastructure they have managed

Summary of Kubernetes and AWS environments they have operated

Details of machine learning or AI workloads they have deployed

Examples of CI/CD pipelines and Infrastructure-as-Code projects they have implemented

Success Criteria

The successful candidate will:

Architect and maintain highly reliable cloud infrastructure.

Independently manage AWS-based production environments.

Successfully deploy and operate complex ML and AI workloads.

Design secure and scalable multi-service routing architectures.

Drive automation, observability, and operational excellence.

Serve as a technical leader for cloud infrastructure and platform engineering initiatives.

Improve deployment velocity, system reliability, and infrastructure scalability across the organization.

Pay: ₹647,045.59 - ₹804,652.19 per year

Benefits:

Health insurance

Paid sick time

Paid time off

Provident Fund

Work Location: In person