Senior DevOps Engineer

About the Company

Fusemachines (http://www.fusemachines.com) builds AI Schools in underserved communities (AI Education Solution) and connects the graduates to AI job opportunities (AI Talent Solution). Fusemachines AI Schools run AI Microdegree® and Certificate programs in physical classrooms using its proprietary content and learning platform.

Qualification & Experience :

  • Must have a full-time Bachelor's degree in Computer Science or similar.
  • At least 3-4 years of working experience in the related field.

Required Skills:

  • Good understanding of at least one programming language like Python. 
  • Good understanding of different package/dependency managers like Gradle, Maven, NPM.
  • Good knowledge of AWS and its core services S3, SES, Queuing services, Container Services, Load Balancing, Data Warehousing, and data pipeline services
  • Good understanding of configuring, monitoring, maintaining, and debugging different types of load balancers. Should be able to select the type of load balancer based on the requirement and the technologies used. Knowledgeable of scaling infrastructure and the components. Minimize downtime in scaling infrastructure. A good grasp on the key scaling components like SQS, Kinesis, etc.
  • Robust understanding of production application delivery pipelines, tools and technologies, and use cases. Tools include but not limited to Jenkins, Circle CI, AWS Code Build, AWS Code Deploy, AWS CodePipeline. Should be able to configure and maintain multi-branch pipelines in Jenkins.
  • Good grasp in operating, deploying and maintaining a multi-region production system for In-house products and our customers. Good understanding of on-premise infrastructure and provide alternative solutions to cloud services
  • Good grasp of vendor-neutral automation and configuration management tools like Terraform, Ansible. Familiarity with writing automated production automation code for multiple services.
  • Hands-on experience in setting up monitoring, logging, and tracing tools like Datadog, Sumo Logic, AWS Cloudwatch, and Container Insights. Create dashboards and alerts based on KPI and any critical production components.
  • Robust understanding of common security best practices, AWS security best practices. Good understanding of implementing AWS security and governance tools like AWS Cloud Trail, AWS Guard Duty, AWS Shield, AWS Certificate Manager
  • Good grasp in using common cloud-native technologies like Kubernetes
  • Good understanding of Different SQL and NoSQL databases like MySQL, PostgreSQL, MongoDB. Familiarity with query and performance tuning and profiling. Good understanding of deployment replica sets and use cases.
  • Good understanding of when and how to conduct any incident response cycle, conduct blameless post mortems. Familiarity with generating post mortem repost and communicating them with cross-functional teams

Roles and Responsibilities:

  • Drive to a key conclusion for scaling in or scaling out for the various client and internal products based on monitoring, tracking, and traffic patterns, etc.
  • Execute and plan secure, smooth, fast, and repeatable application integration best practices and delivery pipelines.
  • Take ownership of the production system and involve and help key stakeholders in decision making. Create a balance in budget analysis, cost reduction.
  • Write modular, expandable, and pluggable code to deploy and automate infrastructure and services.
  • Learn and analyze the current process in product, DevOps, teams, and suggest improvements. Create well defined and structured documents. 
  • Research and implement security vulnerabilities, solutions to mitigate security vulnerabilities. 
  • Develop plans to deploy containers, service mesh, container orchestration tools in the cloud.
  • Plan, document, and implement production replica sets. 
  • Conduct blameless postmortems, find problems, root causes, and solutions to mitigate them. 
  • Independently shortlist, analyze, and select prospective team members based on their skill and expertise. 
  • Research, plan, suggest, and implement distributed services like microservices, design patterns, and architectures.
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