AWS DevOps Engineer

Azure DevOps engineer should have a deep understanding of container principles and hands-on experience with Docker. 

They should also be able to set-up and manage clusters using Azure Kubernetes Service (AKS). Additionally, understanding of API management, Azure Key-Vaults, ACR, networking concepts like virtual networks, subnets, NSG, route tables. Awareness of any one of the software like Apigee, Kong, or APIM in Azure is a must. Strong experience with IaC technologies like Terraform, ARM/ Bicep Templates, GitHub Pipelines, Sonar etc.

• Designing DevOps strategies: Recommending strategies for migrating and consolidating DevOps tools, designing an Agile work management approach, and creating a secure development process
• Implementing DevOps development processes: Designing version control strategies, integrating source control, and managing build infrastructure
• Managing application configuration and secrets: Ensuring system and infrastructure availability, stability, scalability, and performance
• Automating processes: Overseeing code releases and deployments with an emphasis on continuous integration and delivery
• Collaborating with teams: Working with architect and developers to ensure smooth code integration and collaborating with development and operations teams to define pipelines.
• Documentation: Producing detailed Development Architecture design, setting up the DevOps tools and working together with the CI/CD specialist in integrating the automated CI and CD pipelines with those tools
• Ensuring security and compliance/DevSecOps: Managing code quality and security policies
• Troubleshooting issues: Investigating issues and responding to customer queries
• Core Skills: Azure DevOps engineer should have a deep understanding of container principles and hands-on experience with Docker. They should also be able to set-up and manage clusters using Azure Kubernetes Service (AKS). Additionally, understanding of API management, Azure Key-Vaults, ACR, networking concepts like virtual networks, subnets, NSG, route tables. Awareness of any one of the software like Apigee, Kong, or APIM in Azure is a must. Strong experience with IaC technologies like Terraform, ARM/ Bicep Templates, GitHub Pipelines, Sonar,
• Additional Skills: Self-starter and ability to execute tasks on time, Excellent communication skills, ability to come up with multiple solutions for problems, interact with client-side experts to resolve issues by providing correct pointers, excellent debugging skills, ability to breakdown tasks into smaller steps.

• At least 5 year of experience in Cloud technologies-AWS and Azure and developing. 
• Experience in implementing DevOps practices and DevOps-tools in areas like CI/CD using Jenkins environment automation, and release automation, virtualization, infra as a code or metrics tracking.
• Hands on experience in DevOps tools configuration in different environments.
• Strong knowledge of working with DevOps design patterns, processes and best practices
• Hand-on experience in Setting up Build pipelines.
• Prior working experience in system administration or architecture in Windows or Linux.
• Must have experience in GIT (BitBucket, GitHub, GitLab)
• Hands-on experience on Jenkins pipeline scripting.
• Hands-on knowledge in one scripting language (Nant, Perl, Python, Shell or PowerShell)
• Configuration level skills in tools like SonarQube (or similar tools) and Artifactory.
• Expertise on Virtual Infrastructure (VMWare or VirtualBox or QEMU or KVM or Vagrant) and environment automation/provisioning using SaltStack/Ansible/Puppet/Chef
• Deploying, automating, maintaining and managing Azure cloud based production systems including monitoring capacity.
• Good to have experience in migrating code repositories from one source control to another.
• Hands-on experience in Docker container and orchestration based deployments like Kubernetes, Service Fabric, Docker swarm.
• Must have good communication skills and problem solving skills

• Strong experience working with tools and platforms like Helm charts, Circle CI, Jenkins,
• and/or Codefresh
• Excellent knowledge of AWS offerings around Cloud and DevOps
• Strong expertise in containerization platforms like Docker and container orchestration platforms like Kubernetes & Rancher
• Should be familiar with leading Infrastructure as Code tools such as Terraform, CloudFormation, etc.
• Strong experience in Python, Shell Scripting, Ansible, and Terraform
• Good command over monitoring tools like Datadog, Zabbix, Elk, Grafana, CloudWatch, Stackdriver, Prometheus, JFrog, Nagios, etc.
• Experience with Linux/Unix systems administration.

• 5+ years of experience in DevOps including automated system configuration, application deployment, and infrastructure-as-code. 
• Advanced Linux system administration abilities. 
• Real-world experience managing large-scale AWS or GCP environments. Multi-account management a plus. 
• Experience with managing production environments on AWS or GCP. 
• Solid understanding CI/CD pipelines using GitHub, CircleCI/Jenkins, JFrog Artifactory/Nexus. 
• Experience on any configuration management tools like Ansible, Puppet or Chef is a must. 
• Experience in any one of the scripting languages: Shell, Python, etc. 
• Experience in containerization using Docker and orchestration using Kubernetes/EKS/GKE is a must. 
• Solid understanding of SSL and DNS. 
• Experience on deploying and running any open-source monitoring/graphing solution like Prometheus, Grafana, etc. 
• Basic understanding of networking concepts.
• Always adhere to security best practices.
• Knowledge on Bigdata (Hadoop/Druid) systems administration will be a plus.  
• Knowledge on managing and running DBs (MySQL/MariaDB/Postgres) will be an added advantage. 

What you get to do 

• Work with development teams to build and maintain cloud environments to specifications developed closely with multiple teams. Support and automate the deployment of applications into those environments 
• Diagnose and resolve occurring, latent and systemic reliability issues across entire stack: hardware, software, application and network. Work closely with development teams to troubleshoot and resolve application and service issues 
• Continuously improve Conviva SaaS services and infrastructure for availability, performance and security 
• Implement security best practices – primarily patching of operating systems and applications 
• Automate everything. Build proactive monitoring and alerting tools. Provide standards, documentation, and coaching to developers.
• Participate in 12x7 on-call rotations 
• Work with third party service/support providers for installations, support related calls, problem resolutions etc. 

1. Develop and Deploy Software:
1. Architect and create an effective build and release process using industry best practices and tools
2. Create and manage build scripts to deploy software in a multi-cloud environment
3. Look for opportunities to automate as much of the deployment process as possible to provide for repeatability, auditability, scalability and build in process enforcement
2. Manage Release Schedule:
1. Act as a “gate keeper” for all releases into production
2. Work closely with business stakeholders, development managers and developers to prepare a release schedule
3. Help prioritize deployment requests for version upgrades, patches and hot-fixes
3. Continuous Delivery of Software:
1. Implement Continuous Integration (CI) practices to drive development teams to implement smaller changes and commit code to the version control repo frequently
2. Implement Continuous Development (CD) practices that automates deployment of the application to several environments – Dev, Test and Production
3. Implement Continuous Testing (functional and non-functional) to execute tests in the CI/CD pipeline
4. Manage Version Control:
1. Define and implement branching policies to efficiently manage source-code
2. Implement business rules as a part of source control standards
5. Resolve Software Issues:
1. Assist technical support and development teams to troubleshoot issues and identify areas that need improvement
2. Address deployment related issues
6. Maintain Release Documentation:
1. Maintain release notes (features available in stable versions and known issues) and other documents for both internal and external end users

Striim (pronounced “stream” with two i’s for integration and intelligence) was founded in 2012 with a simple goal of helping companies make data useful the instant it’s born.

Striim’s enterprise-grade, streaming integration with intelligence platform makes it easy to build continuous, streaming data pipelines – including change data capture (CDC) – to power real-time cloud integration, log correlation, edge processing, and streaming analytics

2 - 5 Years of Experience in any Programming any language (Polyglot Preferred ) & System Operations • Awareness of Devops & Agile Methodologies • Proficient in leveraging CI and CD tools to automate testing and deployment . • Experience in working in an agile and fast paced environment . • Hands on knowledge of at least one cloud platform (AWS / GCP / Azure). • Cloud networking knowledge: should understand VPC, NATs, and routers. • Contributions to open source is a plus. • Good written communication skills are a must. Contributions to technical blogs / whitepapers will be an added advantage.

• Work towards improving the following 4 verticals - scalability, availability, security, and cost, for company's workflows and products.
• Help in provisioning, managing, optimizing cloud infrastructure in AWS (IAM, EC2, RDS, CloudFront, S3, ECS, Lambda, ELK etc.)
• Work with the development teams to design scalable, robust systems using cloud architecture for both 0-to-1 and 1-to-100 products.
• Drive technical initiatives and architectural service improvements.
• Be able to predict problems and implement solutions that detect and prevent outages.
• Mentor/manage a team of engineers.
• Design solutions with failure scenarios in mind to ensure reliability.
• Document rigorously to keep track of all changes/upgrades to the infrastructure and as well share knowledge with the rest of the team
• Identify vulnerabilities during development with actionable information to empower developers to remediate vulnerabilities
• Automate the build and testing processes to consistently integrate code
• Manage changes to documents, software, images, large web sites, and other collections of code, configuration, and metadata among disparate teams

MLOps Engineer

Required Candidate profile :

• 3+ years’ experience in developing continuous integration and deployment (CI/CD) pipelines (e.g. Jenkins, Github Actions) and bringing ML models to CI/CD pipelines
• Candidate with strong Azure expertise
• Exposure of Productionize the models
• Candidate should have complete knowledge of Azure ecosystem, especially in the area of DE
• Candidate should have prior experience in Design, build, test, and maintain machine learning infrastructure to empower data scientists to rapidly iterate on model development
• Develop continuous integration and deployment (CI/CD) pipelines on top of Azure that includes AzureML, MLflow and Azure Devops
• Proficient knowledge of git, Docker and containers, Kubernetes
• Familiarity with Terraform
• E2E production experience with Azure ML, Azure ML Pipelines
• Experience in Azure ML extension for Azure Devops
• Worked on Model Drift (Concept Drift, Data Drift preferable on Azure ML.)
• Candidate will be part of a cross-functional team that builds and delivers production-ready data science projects. You will work with team members and stakeholders to creatively identify, design, and implement solutions that reduce operational burden, increase reliability and resiliency, ensure disaster recovery and business continuity, enable CI/CD, optimize ML and AI services, and maintain it all in infrastructure as code everything-in-version-control manner.
• Candidate with strong Azure expertise
• Candidate should have complete knowledge of Azure ecosystem, especially in the area of DE
• Candidate should have prior experience in Design, build, test, and maintain machine learning infrastructure to empower data scientists to rapidly iterate on model development
• Develop continuous integration and deployment (CI/CD) pipelines on top of Azure that includes AzureML, MLflow and Azure Devops

Role and responsibilities

• Expertise in AWS (Most typical Services),Docker & Kubernetes.
• Strong Scripting knowledge, Strong Devops Automation, Good at Linux
• Hands on with CI/CD (CircleCI preferred but any CI/CD tool will do). Strong Understanding of GitHub
• Strong understanding of AWS networking and. Strong with Security & Certificates.

Nice-to-have skills

• Involved in Product Engineering