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Devops Engineer

Devops Engineer at VY SYSTEMS PRIVATE LIMITED · Hyderabad, Bengaluru (Bangalore) · 4 - 10 years · ₹5L - ₹26L / yr · Profitable · Posted 30 Sep 2026

VY SYSTEMS PRIVATE LIMITED's logo

Devops Engineer

Pavithra E's profile picture
Posted by Pavithra E
4 - 10 yrs
₹5L - ₹26L / yr
Hyderabad, Bengaluru (Bangalore)
Skills
skill iconPython
skill iconKubernetes
DevOps

Job Description – DevOps + Python

Job Title: DevOps + Python Developer

Experience: 4–10 Years

Location: Bangalore / Hyderabad

Notice Period: Immediate to 15 Days

Mandatory Skills

  • Python
  • Kubernetes
  • Containerization
  • DevOps
  • Cloud Exposure – Any Cloud platform (AWS / Azure / GCP)

Job Description

We are looking for experienced DevOps + Python professionals with strong hands-on experience in Python development and DevOps practices.

The candidate should have practical experience with Kubernetes and containerization, along with exposure to cloud platforms and DevOps processes.

Key Responsibilities

  • Develop and maintain applications/scripts using Python.
  • Work with Kubernetes and containerized environments.
  • Support DevOps processes and automation.
  • Work with cloud platforms and cloud-based environments.
  • Collaborate with development and infrastructure teams.
  • Troubleshoot and resolve deployment and environment-related issues.


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About VY SYSTEMS PRIVATE LIMITED

Founded :
2000
Type :
Services
Size :
100-1000
Stage :
Profitable

About

Vy Systems is a Global Technology consulting, Solutions, and Managed Technology Services company. We service our customers with ‘RESPONSIVENESS’ as a key factor and we believe that timely response to any transaction increases the operational efficiency and accelerates the revenue and profitability to our customers.

The Company is founded and managed by a team of professionals having more than two+ decades of global experience in the business of Technology Consulting and Services.


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Tech stack

IT consulting

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If you are Interested DM me on LinkedIn - Saquib Mundagnur



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Cost & scale - Own cloud cost visibility and optimization; make scaling decisions that balance reliability and spend. 



What You'll Bring - 6+ years in DevOps, SRE, platform, or infrastructure engineering, running production systems at meaningful scale.

- Strong hands-on experience with a major cloud provider (**AWS or Azure or GCP**) and Infrastructure-as-Code (**Terraform** or equivalent).

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AWS, Kubernetes, Docker, Terraform, Ansible, Jenkins, GitLab CI/CD, GitHub Actions, Python, Bash, CI/CD, Infrastructure as Code (IaC), Grafana, Prometheus, ELK, New Relic, CloudWatch, SRE, SLI/SLO/SLA, Linux


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1. Cloud Infrastructure & Infrastructure as Code (IaC) :

  • Provision, configure, and maintain scalable, high-availability infrastructure on multi-cloud platforms, primarily AWS (EC2, VPC, IAM, S3, RDS, Route53, ALB/ASG, Lambda, EBS).
  • Build, deploy, and manage Infrastructure as Code (IaC) using Terraform, Ansible, and CloudFormation to enforce consistency and eliminate configuration drift.
  • Execute disaster recovery (DR) planning, automated failover / failback mechanisms, and chaos engineering exercises to validate system resiliency.

2. CI/CD, Automation & Development :

  • Design, end-to-end maintain, and optimize robust CI/CD pipelines using Jenkins, GitLab CI, and GitHub Actions.
  • Automate release pipelines, versioning, branching strategies, and approval gates using Groovy, Python, and Bash scripting. Integrate automated code quality and security scanning tools (SonarQube, Black Duck, or Fortify) directly into delivery pipelines.
  • Develop custom tools, scripts, or microservices (e.g., Python / Node.js) to automate manual operational tasks and operational toil.

3. Containerization & Orchestration :

  • Onboard and orchestrate containerized microservices utilizing Docker and Kubernetes (including Helm charts).
  • Ensure high availability, auto-scaling, resource management, and fault tolerance for Kubernetes pod deployments.

4. Observability, SRE & Incident Management :

  • Drive Site Reliability Engineering (SRE) maturity by establishing, tracking, and reporting SLIs, SLOs, and SLAs with cross-functional engineering teams.
  • Build, configure, and manage full-stack observability tools : Grafana, Prometheus, New Relic, Elasticsearch / Logstash / Kibana (ELK), Sentry, and AWS CloudWatch.
  • Set up real-time alerting, custom metric dashboards, and automated log rotation / pruning scripts.
  • Handle production incidents, lead Root Cause Analysis (RCA) investigations, and implement preventive measures to reduce Mean Time to Resolution (MTTR).


Required Qualifications & Skills :

  • Education : Bachelor’s Degree in Electronics and Communication Engineering, Computer Science, or a related technical field.
  • Experience : ~4 years of experience in DevOps, SRE, or Cloud System Administration roles.
  • Cloud & Infrastructure : Hands-on experience with AWS (Core services like EC2, S3, VPC, RDS, IAM, Lambda, Auto Scaling) and exposure to Azure / GCP.
  • CI/CD & Version Control : Proficiency with Jenkins, GitLab CI, GitHub Actions, and Git workflows.
  • Containerization : Core proficiency in Docker and Kubernetes cluster management / onboarding.
  • Infrastructure as Code : Expertise in Ansible, Terraform, or AWS CloudFormation.
  • Scripting & Languages : Strong hands-on automation skills with Python, Bash, and foundational knowledge of Node.js, Java or C++.
  • Observability & Logging : Strong experience with Grafana, Prometheus, New Relic, ELK stack, or Splunk.
  • Database & SQL : Familiarity with relational databases (MySQL, RDS) for monitoring setup and operational analytics.
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Amura’s Vision 


We believe that the most under-appreciated route to releasing untapped human potential is to build a healthier body, and through which a better brain. This allows us to do more of everything that is important to each one of us.


Billions of healthier brains, sitting in healthier bodies, can take up more complex problems that defy solutions today, including many existential threats, and solve them in just a few decades.


Billions of healthier brains will make the world richer beyond what we can imagine today. The surplus wealth, combined with better human capabilities, will lead us to a new renaissance, giving us a richer and more beautiful culture.


These healthier brains will be equipped with deeper intellect, be less acrimonious, more magnanimous, and have a kinder outlook on the world, resulting in a world that is better than any previous time.

We find this vision of the future exhilarating. Our hopes and dreams are to create this future as quickly as possible and ensure that it is widely distributed and optimized to maximize all forms of human excellence. 


Role Overview 


We are looking for a highly skilled Senior DevOps Engineer (AI-Native Infrastructure & Platform Engineering) with deep expertise in AWS cloud infrastructure, automation, AI infrastructure operations, and modern DevOps/SRE practices.


This role goes beyond traditional DevOps and requires a seasoned specialist capable of building and operating AI-ready infrastructure platforms that support high-throughput APIs, LLM/AI workloads, GPU-based compute, data-intensive systems, real-time inference pipelines, and scalable ML platforms.


You will be responsible for architecting, automating, securing, and optimizing highly scalable and cost-efficient cloud environments that enable high-velocity engineering and AI teams. This is an ideal position for someone who combines technical ownership, an automation-first mindset, and a passion for developer productivity and platform reliability. 


Key Responsibilities 


Cloud Infrastructure & Platform Engineering (AWS) 

  • Architect, deploy, and manage highly scalable and secure infrastructure on AWS. Design cloud platforms supporting AI/ML workloads, data pipelines, real-time APIs, and high-concurrency backend systems.
  • Hands-on expertise with key AWS services including EC2, ECS/EKS, Lambda, RDS, DynamoDB, S3, VPC, CloudFront, IAM, CloudWatch, and GPU-enabled instances.
  • Build and maintain Infrastructure-as-Code (IaC) using Terraform, CloudFormation, or AWS CDK.
  • Design multi-AZ and multi-region architectures for high availability and disaster recovery (HA/DR).
  • Build reusable platform templates and shared infrastructure modules. 


AI/ML Infrastructure & MLOps 

  • Build and maintain infrastructure for LLM applications, AI inference workloads, model serving platforms, vector databases, and feature stores.
  • Support GPU-based workloads and optimize compute/storage usage.
  • Enable scalable deployment patterns for AI applications using Kubernetes/EKS. Collaborate with Data Science and ML Engineering teams on model deployment, training/tuning of models, CI/CD for ML systems, experiment environments, and reproducibility.
  • Support orchestration and deployment of AI workflows and inference services while implementing observability and reliability for AI pipelines. 


CI/CD, Automation & Developer Productivity 

  • Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or AWS CodePipeline.
  • Automate deployments, environment provisioning, and release workflows.
  • Build self-service developer platforms, preview environments, and reusable deployment workflows to improve developer productivity.
  • Implement automated patching, scaling, backups, cleanup workflows, and drift detection. 


Containers, Kubernetes & Platform Reliability

  • Manage Docker-based environments, containerized applications, and optimize workloads using Kubernetes (EKS) or ECS/Fargate.
  • Manage autoscaling, cluster health, node pools, ingress, service mesh, and workload isolation.
  • Optimize infrastructure for performance, resilience, and cost-efficiency.
  • Implement progressive deployment strategies including blue/green, canary, and rolling deployments. 


Observability, Incident Response & SRE Practices

  • Implement observability stacks using CloudWatch, Prometheus, Grafana, ELK, Datadog, OpenTelemetry, or New Relic.
  • Build actionable dashboards and intelligent alerting systems while defining and tracking SLIs, SLOs, and SLAs.
  • Lead incident response, root cause analysis, and blameless postmortems to reduce operational toil and improve MTTR.

FinOps, Cost Governance & Security

  • Continuously monitor and optimize cloud costs (compute utilization, storage lifecycle, GPU usage, and data transfer) using AWS Cost Explorer, Budgets, Trusted Advisor, CloudHealth, or Kubecost.
  • Implement AWS security best practices for IAM, VPCs, security groups, NACLs, encryption, and manage secrets using KMS, SSM Parameter Store, or Vault.
  • Build secure CI/CD pipelines with automated security checks, least-privilege access, audit logging, and ensure compliance readiness for ISO 27001, SOC2, and GDPR.

Collaboration, Leadership & Platform Culture

  • Work closely with engineering, AI/ML, QA, product, and operations teams to drive a DevOps, SRE, GitOps, and automation-first culture.
  • Mentor junior DevOps and Platform Engineers while creating and maintaining detailed runbooks, architecture diagrams, and platform documentation.

Skills & Qualifications


Must-Have:

  • 7+ years of experience in DevOps, SRE, Platform Engineering, or Cloud Infrastructure Engineering.
  • Strong expertise in AWS cloud architecture, services, and deep understanding of Kubernetes (EKS), containers, and cloud-native systems.
  • Strong Infrastructure-as-Code expertise using Terraform, CloudFormation, or CDK. Strong Linux administration, networking, DNS, routing, and load balancing knowledge. Strong scripting/programming experience in Python, Bash, or Go (preferred). Experience with CI/CD automation, GitOps workflows, and observability platforms supporting scalable production systems.


Preferred / Nice-to-Have:

  • Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
  • Familiarity with Kafka, Redis, SQS, and event-driven systems.
  • Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
  • AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 


Preferred / Nice-to-Have:

  • Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
  • Familiarity with Kafka, Redis, SQS, and event-driven systems.
  • Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
  • AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 


Here are answers to some questions you may have

Where is your office?

Chennai (Velachery)

Work Model

Work from Office – because great stories are built in person!

Do you have an online presence?

https://amura.ai (we are @AmuraHealth on all social media)


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I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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