Senior Systems Engineer

B.S or higher in Computer Science, Mathematics, Physics (or equivalent work experience)
Have worked with a cloud provider for at least 5 years. Bonus points for AWS experience.
Heavy experience with Docker in a production environment using a clustering product like Kubernetes, ECS, Mesos, Swarm etc.
Proficient in a Linux environment, including experience with scripting.
Programming skills in at least one of the major scripting languages (Bash, Python, Ruby, Node, etc)
Knowledge of all major Web standard protocols, web servers (Apache/Nginx) and load balancing.
Experience designing a continuous integration/deployment process from scratch, whether via Jenkins, Travis, Circle, Bamboo, or TeamCity, etc.
Experience managing large scale data storage and processing systems such as Apache Hadoop, Aerospike, Apache Spark, Apache Kafka, or Amazon Redshift
You need robust communication, presentation, and interpersonal skills. You should be skilled at explaining complex design ideas in a clear and engaging manner.

Improve the scalability and durability of our systems via regular infrastructure updates. We’re cloud first and hosted on Amazon Web Services.
You will be working within Kargo’s Kubernetes environment on AWS to build infrastructure across regions that deliver services as quickly as possible.
Help the data engineering team deploy data streaming solutions to aid in real-time collection of data to be used by our machine learning services.
You will be helping to set up and manage continuous integration tools like Travis-CI to ensure proper testing across Kargo’s software.
You will identify and initiate investigations into new technologies, prototype and test infrastructure solutions, and design and validate production designs that help all engineers get the job done.
You will be tasked with continuously finding new ways to improve Kargo’s infrastructure stack and internal services that the development team uses on a day to day basis.
You will be up for scripting and writing code when necessary or in between systems tasks in order to help the team.
Take ownership over the monitoring and logging tools that the rest of the department will use to gain insight into our environments (InfluxDB, Prometheus, Grafana)