Sr. DevOps Software Engineer

Information Technology Services is hiring Sr. DevOps Software Engineer job in Pune | Cutshort

Sr. DevOps Software Engineer
Information Technology Services
Sr. DevOps Software Engineer

at Information Technology Services
Agency job
5
\- 8 yrs
₹10L - ₹30L / yr
Pune
Skills
Java
Python
Javascript
Scala
Docker
Kubernetes
DevOps
Amazon Web Services (AWS)
Windows Azure
Google Cloud Platform (GCP)
Sr. DevOps Software Engineer:
Preferred Education & Experience: •
Bachelor’s or master’s degree in Computer Engineering,
Computer Science, Computer Applications, Mathematics, Statistics or related technical field or
equivalent practical experience. Relevant experience of at least 3 years in lieu of above if from a different stream of education.
• Well-versed in DevOps principals & practices and hands-on DevOps
tool-chain integration experience: Release Orchestration & Automation, Source Code & Build
Management, Code Quality & Security Management, Behavior Driven Development, Test Driven
Development, Continuous Integration, Continuous Delivery, Continuous Deployment, and
Operational Monitoring & Management; extra points if you can demonstrate your knowledge with
working examples.
• Hands-on experience with demonstrable working experience with DevOps tools
and platforms viz., Slack, Jira, GIT, Jenkins, Code Quality & Security Plugins, Maven, Artifactory,
Terraform, Ansible/Chef/Puppet, Spinnaker, Tekton, StackStorm, Prometheus, Grafana, ELK,
PagerDuty, VictorOps, etc.
• Well-versed in Virtualization & Containerization; must demonstrate
experience in technologies such as Kubernetes, Istio, Docker, OpenShift, Anthos, Oracle VirtualBox,
Vagrant, etc.
• Well-versed in AWS and/or Azure or and/or Google Cloud; must demonstrate
experience in at least FIVE (5) services offered under AWS and/or Azure or and/or Google Cloud in
any categories: Compute or Storage, Database, Networking & Content Delivery, Management &
Governance, Analytics, Security, Identity, & Compliance (or) equivalent demonstratable Cloud
Platform experience.
• Well-versed with demonstrable working experience with API Management,
API Gateway, Service Mesh, Identity & Access Management, Data Protection & Encryption, tools &
platforms.
• Hands-on programming experience in either core Java and/or Python and/or JavaScript
and/or Scala; freshers passing out of college or lateral movers into IT must be able to code in
languages they have studied.
• Well-versed with Storage, Networks and Storage Networking basics
which will enable you to work in a Cloud environment.
• Well-versed with Network, Data, and
Application Security basics which will enable you to work in a Cloud as well as Business
Applications / API services environment.
• Extra points if you are certified in AWS and/or Azure
and/or Google Cloud.
Required Experience: 5+ Years
Job Location: Remote/Pune
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Senior Cloud Engineer Job Description
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Location: Remote \[REQUIRES WORKING IN CST TIME ZONE\]
Position Overview
The Senior Cloud Engineer will play a critical role in designing, deploying, and managing scalable, secure, and highly available cloud infrastructure across multiple platforms (AWS, Azure, Google Cloud). This role requires deep technical expertise, leadership in cloud
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Design, implement, and maintain cloud infrastructure and services, ensuring high availability, performance, and security across multi-cloud environments (AWS, Azure, GCP)
Develop and manage Infrastructure as Code (IaC) using tools such as Terraform, CloudFormation, and Ansible for automated provisioning and configuration
Lead the adoption and optimization of DevOps methodologies, including CI/CD pipelines, automated testing, and deployment processes
Collaborate with software engineers, architects, and stakeholders to architect cloud-native solutions that meet business and technical requirements
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Document cloud architectures, processes, and procedures to ensure knowledge transfer and operational excellence
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– _Bachelors or Masters degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent work experience_
– _6–10 years of experience in cloud engineering or related roles, with a proven track record in large-scale cloud environments_
– _Deep expertise in at least one major cloud platform (AWS, Azure, Google Cloud) and experience in multi-cloud environments_
– _Strong programming and scripting skills (Python, Bash, PowerShell, etc.) for automation and cloud service integration_
– _Proficiency with DevOps tools and practices, including CI/CD (Jenkins, GitLab CI), containerization (Docker, Kubernetes), and configuration management (Ansible, Chef)_
– _Solid understanding of networking concepts (VPC, VPN, DNS, firewalls, load balancers), system administration (Linux/Windows), and cloud storage solutions_
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– _Excellent analytical, troubleshooting, and root cause analysis skills_
– _Strong communication and collaboration abilities, with experience working in agile, interdisciplinary teams_
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Read more

Posted by
Anubhav Kumar Rai
Bengaluru (Bangalore)
2
\- 5 yrs
₹5.4L - ₹7.2L / yr
DevOps
Amazon Web Services (AWS)
Google Cloud Platform (GCP)
Windows Azure
Location: Bangalore
Experience: 2–5 years
Type: Full-time | On-site
Start: Immediate
Why this role exists
Most systems don’t fail because of one big outage.
They fail because reliability is treated as an afterthought.
Right now, uptime depends too much on individual heroics.
That doesn’t scale.
This role exists to build a reliability system where:
– Uptime is predictable
– Failures are contained
– Escalations don’t depend on leadership
What you’ll do
You will not just monitor systems.
You will own reliability as a product.
1\. Drive uptime to production-grade reliability
– Improve system uptime to 99.9% customer-facing SLA within 4 months
– Define and track:
– SLAs / SLOs / error budgets
– Ensure reliability is measured from the customer’s perspective, not internal metrics
2\. Build incident response as a system
– Set up a 24/7 incident response rotation across 3 engineers
– Eliminate dependency on leadership (no single escalation point)
– Define:
– Incident severity levels
– Response playbooks
– Escalation protocols
– Ensure fast detection → containment → resolution
3\. Contain and fix erratic system behavior
– Identify and resolve:
– Latency spikes
– Downtime incidents
– Integration failures
– Build guardrails to prevent recurrence
– Focus on root cause elimination, not temporary fixes
4\. Create continuous reliability feedback loops
– Work closely with engineering teams to:
– Surface recurring failure patterns
– Improve build quality
– Reduce production bugs
– Ensure learnings from incidents directly improve future releases
5\. Improve observability and monitoring
– Build dashboards and alerts for:
– System health
– Performance metrics
– Failure signals
– Ensure issues are detected before customers report them
6\. Reduce operational fragility
– Remove single points of failure (people, systems, workflows)
– Improve system resilience across:
– Deployments
– Integrations
– Runtime environments
What success looks like
– Uptime reaches 99.9%+ reliably
– Incidents are:
– Detected early
– Contained quickly
– Resolved permanently
– No dependency on a single individual for escalation
– System behavior becomes predictable and stable
– Engineering teams