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DevOps Engineer
Hiring for B2B product based organization
DevOps Engineer

DevOps Engineer at Hiring for B2B product based organization · Bengaluru (Bangalore) · 4 - 10 years · ₹18L - ₹33L / yr · Posted 29 Sep 2022

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DevOps Engineer

at Hiring for B2B product based organization

Agency job
4 - 10 yrs
₹18L - ₹33L / yr
Bengaluru (Bangalore)
Skills
DevOps
Linux/Unix
Operating systems
Network
Systems architecture
skill iconAmazon Web Services (AWS)

Role Purpose:

As a DevOps ,  You should be strong in both the Dev and Ops part of DevOps. We are looking for someone who has a deep understanding of systems architecture, understands core CS concepts well, and is able to reason about system behaviour rather than merely working with the toolset of the day. We believe that only such a person will be able to set a compelling direction for the team and excite those around them. 

If you are someone who fits the description above, you will find that the rewards are well worth the high bar. Being one of the early hires of the Bangalore office, you will have a significant impact on the culture and the team; you will work with a set of energetic and hungry peers who will challenge you, and you will have considerable international exposure and opportunity for impact across departments.

Responsibilities

  1. Deployment, management, and administration of web services in a public cloud environment
  2. Design and develop solutions for deploying highly secure, highly available, performant and scalable services in elastically provisioned environments
  3. Design and develop continuous integration and continuous deployment solutions from development through production
  4. Own all operational aspects of running web services including automation, monitoring and alerting, reliability and performance
  5. Have direct impact on running a business by thinking about innovative solutions to operational problems
  6. Drive solutions and communication for production impacting incidents
  7. Running technical projects and being responsible for project-level deliveries
  8. Partner well with engineering and business teams across continents

Required Qualifications

  1. Bachelor’s or advanced degree in Computer Science or closely related field
  2. 4 - 6 years professional experience in DevOps, with at least 1/2 years in Linux / Unix
  3. Very strong in core CS concepts around operating systems, networks, and systems architecture including web services
  4. Strong scripting experience in Python and Bash
  5. Deep experience administering, running and deploying AWS based services
  6. Solid experience with Terraform, Packer and Docker or their equivalents
  7. Knowledge of security protocols and certificate infrastructure.
  8. Strong debugging, troubleshooting, and problem solving skills 
  9. Broad experience with cloud hosted applications including virtualization platforms, relational and non relational data stores, reverse proxies, and orchestration platforms
  10. Curiosity, continuous learning and drive to continually raise the bar
  11. Strong partnering and communication skills

Preferred Qualifications

  1. Past experience as a senior developer or application architect strongly preferred.
  2. Experience building continuous integration and continuous deployment pipelines
  3. Experience with Zookeeper, Consul, HAProxy, ELK-Stack, Kafka, PostgreSQL.
  4. Experience working with, and preferably designing, a system compliant to any security framework (PCI DSS, ISO 27000, HIPPA, SOC 2, ...)
  5. Experience with AWS orchestration services such as ECS and EKS.
  6. Experience working with AWS ML pipeline services like AWS Sagemak
Read more
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Shubham Vishwakarma

Full Stack Developer - Averlon
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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  • Maintain infrastructure documentation, configuration standards, and version-controlled deployment workflows.

5. Monitoring, Reliability & Production Operations

  • Establish centralized monitoring, logging, alerting, and observability across cloud environments.
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  • Monitor application availability, infrastructure health, resource utilization, and system performance.
  • Lead troubleshooting and resolution of complex production incidents.
  • Conduct root cause analysis and implement permanent corrective actions.
  • Establish operational practices for backup, disaster recovery, availability, and business continuity.
  • Improve system reliability through proactive monitoring and performance optimization.

6. Cloud Security & Governance

  • Implement cloud security best practices across infrastructure and application environments.
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  • Secure cloud networking, virtual networks, firewalls, and infrastructure access.
  • Implement container security and infrastructure hardening practices.
  • Ensure cloud environments follow organizational security and compliance requirements.
  • Identify infrastructure vulnerabilities and coordinate remediation activities.
  • Establish secure deployment and configuration management practices.

7. AI Infrastructure & Engineering Collaboration

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  • Support the deployment and operation of LLM-based applications, AI services, and AI-enabled platforms.
  • Design cloud infrastructure capable of supporting AI workloads, including compute, storage, networking, and containerized services.
  • Support the infrastructure requirements of AI applications across development, testing, and production environments.
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8. Technical Leadership & Team Development

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  • Establish engineering standards, infrastructure best practices, and operational procedures.
  • Mentor team members on cloud architecture, automation, CI/CD, Kubernetes, and production operations.
  • Lead technical discussions and make architecture decisions involving infrastructure and DevOps technologies.
  • Collaborate with engineering, security, and product teams to align infrastructure capabilities with business requirements.
  • Drive continuous improvement across DevOps processes, tools, and engineering practices.

Required Technical Skills & Experience

1. Cloud Platforms

  • 10+ years of overall experience in DevOps, cloud infrastructure, or platform engineering.
  • Strong hands-on expertise in at least one major cloud platform: AWS or Azure.
  • Practical experience designing, deploying, and operating production-grade cloud infrastructure.

AWS: EC2, S3, IAM, VPC, EKS, Lambda, ECR, CloudWatch, and related infrastructure services.

Azure: Azure Virtual Machines, VNets, AKS, Azure DevOps, Azure Container Registry, Azure Monitor, Key Vault, and related infrastructure services.

Candidates do not need to be experts in both AWS and Azure. Deep expertise in either platform is the priority.

2. DevOps & CI/CD

  • Strong experience designing and maintaining CI/CD pipelines.
  • Hands-on experience with Azure DevOps, Jenkins, GitHub Actions, GitLab CI, or equivalent tools.
  • Understanding of multi-stage pipelines, automated deployments, release approvals, and artifact management.
  • Experience implementing deployment automation and rollback strategies.
  • Strong understanding of Git workflows and version control practices.

3. Containers & Kubernetes

  • Strong hands-on experience with Docker and Kubernetes.
  • Practical experience managing EKS or AKS environments.
  • Understanding of Kubernetes networking, scaling, storage, secrets, and workload management.
  • Experience with Helm and container orchestration.
  • Ability to troubleshoot production container and Kubernetes environments.

4. Infrastructure as Code & Scripting

  • Strong experience with Terraform and Infrastructure as Code practices.
  • Familiarity with CloudFormation, Bicep, ARM templates, or similar tools.
  • Working knowledge of Python, Bash, or PowerShell for infrastructure automation.
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5. Monitoring & Reliability Engineering

  • Experience implementing infrastructure and application monitoring.
  • Familiarity with CloudWatch, Azure Monitor, Prometheus, Grafana, and centralized logging solutions.
  • Understanding of incident management, root cause analysis, performance optimization, and system availability.
  • Experience establishing alerting, operational dashboards, and reliability practices.

6. AI/ML Infrastructure Exposure

  • Prior experience supporting AI/ML applications, Generative AI platforms, LLM applications, or AI-enabled products.
  • Understanding of infrastructure requirements for deploying and operating AI-powered applications.
  • Familiarity with containerized AI services, cloud-based model integrations, and scalable application environments.

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Preferred Skills

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  • Exposure to cloud security, enterprise networking, governance, and landing-zone architecture.
  • Experience with cloud cost optimization and FinOps practices.
  • Familiarity with AI/ML infrastructure and production GenAI applications.
  • Experience with Python-based automation and infrastructure tooling.
  • Relevant AWS, Azure, Kubernetes, or Terraform certifications.

What We're Looking For Beyond Skills

  • Cloud Expertise: Deep technical specialization in AWS or Azure, with the ability to design and manage production infrastructure independently.
  • Hands-on Engineering: Someone who actively builds, automates, troubleshoots, and improves infrastructure rather than focusing only on team management.
  • Technical Ownership: Takes responsibility for infrastructure reliability, deployment quality, security, and operational performance.
  • System Thinking: Understands how cloud infrastructure, applications, networking, databases, and deployment pipelines work together.
  • Problem-Solving: Ability to diagnose complex production issues and implement long-term engineering solutions.
  • Automation Mindset: Continuously identifies opportunities to eliminate manual work and improve operational efficiency.
  • Technical Leadership: Can mentor engineers, establish best practices, and drive technical decisions.
  • AI Readiness: Has practical exposure to supporting AI-powered applications and understands their infrastructure requirements.
  • Collaboration: Works effectively with software engineering, AI/ML, security, and product teams.

Typical Technology Environment

AreaTechnologiesCloud PlatformsAWS, AzureCI/CDAzure DevOps, GitHub Actions, Jenkins, GitLab CIContainersDocker, Kubernetes, EKS, AKS, HelmInfrastructure as CodeTerraform, CloudFormation, Bicep, ARMGitOpsArgo CD, Git-based deployment workflowsMonitoring & ObservabilityCloudWatch, Azure Monitor, Prometheus, GrafanaAutomationPython, Bash, PowerShellOperating SystemsLinux, WindowsSecurityIAM, RBAC, Secrets Management, Network SecurityAI ExposureAI/ML Applications, GenAI, LLM Platforms, AI-enabled Products

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Shubham Vishwakarma's profile image

Shubham Vishwakarma

Full Stack Developer - Averlon
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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