DevOps Engineer

Reposted 10 Days Ago
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Kakkanad, Ernakulam, Kerala
In-Office
Mid level
Artificial Intelligence • Information Technology • Software • Database • Analytics
The Role
A DevOps Engineer at PAI designs and supports cloud-native and hybrid environments, ensuring system performance and security while automating processes and collaborating with developers.
Summary Generated by Built In

Company Profile:

 

Prevalent AI (PAI) is a Security Data Science Company, founded in the UK, by experts recognized globally, for solving the world’s toughest security problems. We apply the world’s best Security Data Science knowledge and expertise to help companies understand, deploy and support the most advanced security solutions, by developing a security architecture based on a deep understanding of Data Science, Security Tradecraft and Big Data Technologies.

 

PAI’s Security Data Science (SDS) platform is a big data security analytics platform that can ingest wide range of security telemetry data and apply advanced analytical approaches to identify and detect control weakness and security risks within enterprises.

 

PAI team consists of Cyber Security Domain Specialists, Information Security Analysts, Data Scientists, Data Engineers and Data Analysts focused on developing advanced security analytics solutions (Solution Development) and delivering security insights to our clients.

Prevalent AI India Pvt Ltd., a subsidiary of Prevalent AI, has offices in Infopark, Cochin, Kerala. For more information, please visit https://www.prevalent.ai


Role Purpose and Key Accountabilities:

 

The role of a DevOps Engineer at PAI is to design, deploy, support, scale and enhance our open-source big data and analytics platform and to model, test, and capture performance bottlenecks and stability issues, at the application level, in a complex distributed environment. This role is part of a talented team of engineers that demonstrate superb technical competency, delivering mission-critical infrastructure and ensuring the highest levels of availability, performance, and security.

 

Key accountabilities include:

  • Identifying, designing and deploying DevOps solutions to cloud-native, on-premises data centers or hybrid environments.
  • Designing, developing and building security reference DevOps architecture for public, private, and hybrid Cloud-based systems with Amazon Web Services (AWS), Azure, or other cloud providers
  • Working closely with IT security to monitor the company's cloud privacy and adhere to Security and Compliance standards ( ISO/ IEC 27001 , SOC2, etc.)
  • Supporting and maintaining developed DevOps solutions to meet agreed service level targets and quality objectives while ensuring the readiness and availability of disaster recovery environments
  • Working with application developers to automate and accelerate applications' testing, release, and deployment into a runtime environment quickly, repeatably, and reliably.
  • Collaborating with team members to improve the company's engineering tools, systems and procedures/processes, and data security.

Skills & Experience:

  • Proficiency in scripting using Bash, Python, or other common scripting languages for automation.
  • Relevant hands-on experience with cloud service providers such as AWS, Azure, Google Cloud, or others to deploy and manage cloud-based resources and services.
  • Proficiency with Git and GitHub workflows to ensure efficient collaboration and tracking of code changes.
  • Relevant experience in designing, developing and managing infrastructure using IaC tools such as Terraform, CloudFormation, ARM Templates, or similar technologies to provision and configure cloud resources.

  • Relevant hands-on experience in

    • Implementing and maintaining CI/CD pipelines to automate application build, test, and deployment using tools like Jenkins, JFrog Artifactory, Ansible, and ArgoCD.

    • Managing and orchestrating containers using Kubernetes, including deployment, scaling, and updates of containerized applications.

    • deploying, configuring, and maintaining Kubernetes clusters in a production environment.

    • continuously analyzing and optimizing resource utilization, cost, and performance of Cloud resources and Kubernetes clusters.

    • performing root cause analysis for production and non-production environment errors. Investigating and resolving technical issues.

    • implementing security best practices and monitoring for vulnerabilities, applying patches and updates as needed. Enforcing access controls and encryption mechanisms.

    • setting up and configuring monitoring, logging, and alerting systems (e.g., Prometheus, Grafana, AWS Cloud Watch, Azure Monitor, etc) to ensure system performance and security.

  • Self-motivated individual capable of working in a fast-paced environment.   
  • Great verbal and written communication skills.  

    Education and Certifications:

    • Master’s/Bachelor's equivalent degree in Computer Science, Engineering or relevant field.

    Top Skills

    Ansible
    Argocd
    Arm Templates
    AWS
    Aws Cloud Watch
    Azure
    Azure Monitor
    Bash
    CloudFormation
    Git
    Git
    GCP
    Grafana
    Jenkins
    Jfrog Artifactory
    Kubernetes
    Prometheus
    Python
    Terraform
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    The Company
    HQ: London
    157 Employees
    Year Founded: 2017

    What We Do

    Prevalent AI was founded to assemble the world’s best AI and Data Science talent, a team capable of building the security analytics of the future.

    In a security technology landscape filled with rigid, siloed solutions and disparate data, organizations are unable to tackle threats and vulnerabilities effectively. By combining our Security Data Fabric with AI-powered Exposure Management, we provide our clients with complete clarity of their cyber risk.

    Our Security Data Fabric automates the integration of complex and disparate data into a single unified knowledge graph, turning data chaos into data clarity with AI-powered entity resolution.

    Our Exposure Management platform identifies every attack surface, contextualizes and prioritizes risk findings, and rapidly remediates exposures — so you’ll always stay one step ahead of attackers.

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