L1 Cloud Infra Engineer - AWS

JOB DETAILS:

- Job Title: Senior Devops Engineer 1

- Industry: Ride-hailing

- Experience: 4-6 years

- Working Days: 5 days/week

- Work Mode: ONSITE

- Job Location: Bangalore

- CTC Range: Best in Industry

Required Skills: Cloud & Infrastructure Operations, Kubernetes & Container Orchestration, Monitoring, Reliability & Observability, Proficiency with Terraform, Ansible etc., Strong problem-solving skills with scripting (Python/Go/Shell)

Criteria:

1. Candidate must be from a product-based or scalable app-based startups company with experience handling large-scale production traffic.

2. Candidate must have strong Linux expertise with hands-on production troubleshooting and working knowledge of databases and middleware (Mongo, Redis, Cassandra, Elasticsearch, Kafka).

3. Candidate must have solid experience with Kubernetes.

4. Candidate should have strong knowledge of configuration management tools like Ansible, Terraform, and Chef / Puppet. Add on- Prometheus & Grafana etc.

5. Candidate must be an individual contributor with strong ownership.

6. Candidate must have hands-on experience with DATABASE MIGRATIONS and observability tools such as Prometheus and Grafana.

7. Candidate must have working knowledge of Go/Python and Java.

8. Candidate should have working experience on Cloud platform - AWS

9. Candidate should have Minimum 1.5 years stability per organization, and a clear reason for relocation.

Description 

Job Summary:

As a DevOps Engineer at company, you will be working on building and operating infrastructure at scale, designing and implementing a variety of tools to enable product teams to build and deploy their services independently, improving observability across the board, and designing for security, resiliency, availability, and stability. If the prospect of ensuring system reliability at scale and exploring cutting-edge technology to solve problems, excites you, then this is your fit.

Job Responsibilities:

- Own end-to-end infrastructure right from non-prod to prod environment including self-managed DBs.

- Understanding the needs of stakeholders and conveying this to developers.

- Working on ways to automate and improve development and release processes.

- Identifying technical problems and developing software updates and ‘fixes’.

- Working with software developers to ensure that development follows established processes and works as intended.

- Do what it takes to keep the uptime above 99.99%.

- Understand DevOps philosophy and evangelize the principles across the organization.

- Strong communication and collaboration skills to break down the silos

Job Requirements:

- B.Tech. / B.E. degree in Computer Science or equivalent software engineering degree/experience.

- Minimum 4 yrs of experience working as a DevOps/Infrastructure Consultant.

- Strong background in operating systems like Linux.

- Understands the container orchestration tool Kubernetes.

- Proficient Knowledge of configuration management tools like Ansible, Terraform, and Chef / Puppet. Add on- Prometheus & Grafana etc.

- Problem-solving attitude, and ability to write scripts using any scripting language.

- Understanding programming languages like GO/Python, and Java.

- Basic understanding of databases and middlewares like Mongo/Redis/Cassandra/Elasticsearch/Kafka.

- Should be able to take ownership of tasks, and must be responsible. - Good communication skills

The DevOps Engineer will play a critical role in operationalizing artificial intelligence across Bell Techlogix client environments. This role focuses on building and supporting cloud infrastructure, CI/CD pipelines, and automation frameworks that power AI and machine learning workloads. The ideal candidate has experience supporting AI platforms such as Azure AI, Azure Machine Learning, Azure OpenAI, and ServiceNow or conversational AI platforms, and understands the operational requirements of production AI systems, including reliability, scalability, and security. 

Key Responsibilities 

•Design, build, and operate cloud infrastructure and platform services that support AI and machine learning workloads in production, SLA-driven managed services environments 

•Implement CI/CD and MLOps pipelines to enable automated training, testing, deployment, and rollback of AI and ML models 

•Develop and maintain Infrastructure as Code to provision AI-ready environments consistently across dev/test/prod 

•Support AI platform operations including monitoring model health, pipeline execution, compute utilization, and data dependencies 

•Partner with Machine Learning Engineers and Data Engineers to standardize deployment patterns for AI services and LLM-based solutions 

•Enable secure and scalable AI integrations using APIs, messaging, and event-driven architectures 

•Implement observability solutions for AI platforms, including logging, metrics, alerting, and drift detection integrations 

•Troubleshoot AI platform incidents, perform root cause analysis, and implement remediation to improve reliability and automation coverage 

•Apply security best practices for AI environments including secrets management, identity and access controls, network isolation, and policy enforcement 

•Support AI-driven automation use cases across platforms such as Microsoft Copilot, ServiceNow, and conversational AI tools 

•Collaborate with service desk, security, and architecture teams to continuously improve AI service delivery and operational maturity 

Required Qualifications 

•Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience 

•5+ years of experience in DevOps, cloud engineering, or platform operations, with exposure to AI or data workloads 

•Hands-on experience with Microsoft Azure, including compute, networking, storage, and monitoring services 

•Experience building CI/CD pipelines using Azure DevOps, GitHub Actions, or similar tools 

•Working knowledge of Infrastructure as Code (Terraform and/or Bicep/ARM) 

•Scripting experience using PowerShell and/or Python 

•Experience supporting production platforms with incident management, change control, and root cause analysis 

•Understanding of cloud security fundamentals and enterprise governance requirements 

Preferred Qualifications 

•Experience with Azure Machine Learning, Azure AI Services, Azure OpenAI, or MLOps frameworks 

•Exposure to containerization and orchestration technologies (Docker, Kubernetes, AKS) 

•Experience supporting data pipelines or feature stores used by machine learning systems 

•Familiarity with ServiceNow, AI-driven ITSM workflows, or automation platforms 

•Experience with observability tools 

•Knowledge of Responsible AI, data governance, and compliance considerations for AI systems 

•Relevant certifications (Microsoft Azure Administrator, Azure DevOps Engineer, Azure AI Engineer)

1. Design cloud infrastructure that is secure, scalable, and highly available on AWS, Azure and GCP
2. Work collaboratively with software engineering to define infrastructure and deployment requirements
3. Provision, configure and maintain AWS, Azure, GCP cloud infrastructure defined as code
4. Ensure configuration and compliance with configuration management tools
5. Administer and troubleshoot Linux based systems
6. Troubleshoot problems across a wide array of services and functional areas
7. Build and maintain operational tools for deployment, monitoring, and analysis of AWS, Azure Infrastructure and systems
8. Perform infrastructure cost analysis and optimization

We are now seeking a talented and motivated individual to contribute to our product in the Cloud data

protection space. Ability to clearly comprehend customer needs in a cloud environment, excellent

troubleshooting skills, and the ability to focus on problem resolution until completion are a requirement.

Responsibilities Include:

Review proposed feature requirements

Create test plan and test cases

Analyze performance, diagnosis, and troubleshooting

Enter and track defects

Interact with customers, partners, and development teams

Researching customer issues and product initiatives

Provide input for service documentation

Required Skills:

Bachelor's degree in Computer Science, Information Systems or related discipline

3+ years' experience inclusive of Software as a Service and/or DevOps engineering experience

Experience with AWS services like VPC, EC2, RDS, SES, ECS, Lambda, S3, ELB

Experience with technologies such as REST, Angular, Messaging, Databases, etc.

Strong troubleshooting skills and issue isolation skills

Possess excellent communication skills (written and verbal English)

Must be able to work as an individual contributor within a team

Ability to think outside the box

Experience in configuring infrastructure

Knowledge of CI / CD

Desirable skills:

Programming skills in scripting languages (e.g., python, bash)

Knowledge of Linux administration

Knowledge of testing tools/frameworks: TestNG, Selenium, etc

Knowledge of Identity and Security

We are looking for an experienced Sr.Devops Consultant Engineer to join our team. The ideal candidate should have at least 5+ years of experience.

We are retained by a promising startup located in Silicon valley backed by Fortune 50 firm with veterans from firms as Zscaler, Salesforce & Oracle. Founding team has been part of three unicorns and two successful IPO’s in the past and well funded by Dell Technologies and Westwave Capital. The company has been widely recognized as an industry innovator in the Data Privacy, Security space and being built by proven Cybersecurity executives who have successfully built and scaled high growth Security companies and built Privacy programs as executives.

Responsibilities:

• Develop and maintain infrastructure as code using tools like Terraform, CloudFormation, and Ansible
• Manage and maintain Kubernetes clusters on EKS and EC2 instances
• Implement and maintain automated CI/CD pipelines for microservices
• Optimize AWS costs by identifying cost-saving opportunities and implementing cost-effective solutions
• Implement best security practices for microservices, including vulnerability assessments, SOC2 compliance, and network security
• Monitor the performance and availability of our cloud infrastructure using observability tools such as Prometheus, Grafana, and Elasticsearch
• Implement backup and disaster recovery solutions for our microservices and databases
• Stay up to date with the latest AWS services and technologies and provide recommendations for improving our cloud infrastructure
• Collaborate with cross-functional teams, including developers, and product managers, to ensure the smooth operation of our cloud infrastructure
• Experience with large scale system design and scaling services is highly desirable

Requirements:

• Bachelor's degree in Computer Science, Engineering, or a related field
• At least 5 years of experience in AWS DevOps and infrastructure engineering
• Expertise in Kubernetes management, Docker, EKS, EC2, Queues, Python Threads, Celery Optimization, Load balancers, AWS cost optimizations, Elasticsearch, Container management, and observability best practices
• Experience with SOC2 compliance and vulnerability assessment best practices for microservices
• Familiarity with AWS services such as S3, RDS, Lambda, and CloudFront
• Strong scripting skills in languages like Python, Bash, and Go
• Excellent communication skills and the ability to work in a collaborative team environment
• Experience with agile development methodologies and DevOps practices
• AWS certification (e.g. AWS Certified DevOps Engineer, AWS Certified Solutions Architect) is a plus.

Notice period : Can join within a month

• Extensive experience in designing & supporting Azure Managed Services Operations.  
• Maintaining the Azure Active Directory and Azure AD authentication. 
• Azure update management – Handling updates/Patching. 
• Good understanding of Azure services (Azure App Service, Azure SQL,  Azure Storage Account..etc). 
• Understanding of load balancers, DNS, virtual networks, NSG and firewalls in cloud environment. 
• ARM templates writing, setup automation for resources provisioning. 
• Knowledge on Azure automation and Automation Desire State Configuration. 
• Good understanding of High Availability and Auto scaling. 
• Azure Backups and ASR (Azure Site Recovery) 
• Azure Monitoring and Configuration monitoring (performance metrics, OMS) 
• Cloud Migration Experience(On premise to Cloud). 
• PowerShell scripting for custom tasks automation. 
• Strong experience in configuring, maintaining, and troubleshooting Microsoft based production systems. 
  
  Certification: 
  
  Azure Administrator (AZ-103) & Azure Architect (AZ-300 & AZ-301) 

• Works independently without any supervision
• Work on continuous improvement of the products through innovation and learning. Someone with a knack for benchmarking and optimization
• Experience in deploying highly complex, distributed transaction processing systems.
• Stay abreast with new innovations and the latest technology trends and explore ways of leveraging these for improving the product in alignment with the business.
• As a component owner, where the component impacts across multiple platforms (5-10-member team), work with customers to obtain their requirements and deliver the end-to-end project.

Required Experience, Skills, and Qualifications

• 5+ years of experience as a DevOps Engineer. Experience with the Golang cycle is a plus
• At least one End to End CI/CD Implementation experience
• Excellent Problem Solving and Debugging skills in DevOps area· Good understanding of Containerization (Docker/Kubernetes)
• Hands-on Build/Package tool experience· Experience with AWS services Glue, Athena, Lambda, EC2, RDS, EKS/ECS, ALB, VPC, SSM, Route 53
• Experience with setting up CI/CD pipeline for Glue jobs, Athena, Lambda functions
• Experience architecting interaction with services and application deployments on AWS
• Experience with Groovy and writing Jenkinsfile
• Experience with repository management, code scanning/linting, secure scanning tools
• Experience with deployments and application configuration on Kubernetes
• Experience with microservice orchestration tools (e.g. Kubernetes, Openshift, HashiCorp Nomad)
• Experience with time-series and document databases (e.g. Elasticsearch, InfluxDB, Prometheus)
• Experience with message buses (e.g. Apache Kafka, NATS)
• Experience with key-value stores and service discovery mechanisms (e.g. Redis, HashiCorp Consul, etc)