Captivation Software is looking for a mid level software engineer to join a team actively developing and maintaining a large-scale, streaming processing, AI/ML system deployed to a Kubernetes cluster. The team is primarily focused on applying AI/ML analytics to large streams of data for content triage purposes. The team is actively migrating the existing system to an AWS cloud-native implementation.
Requirements
- Experience writing applications in Python
- Experience creating, debugging, and tuning performant microservices
- Experience creating containerized applications using docker or equivalent tool
- Experience deploying and managing applications in a container orchestration system such as Kubernetes
- Experience writing applications in Kotlin, Java, and/or Golang
- Experience with AWS & terraform
- Experience with large-scale streaming processing and/or messaging systems such as Apache Kafka, RabbitMQ, or Amazon SQS
Responsibilities
- developing and maintaining a large-scale, streaming processing, AI/ML system deployed to a Kubernetes cluster
- applying AI/ML analytics to large streams of data for content triage purposes
- migrating the existing system to an AWS cloud-native implementation
- writing applications in Python
- creating, debugging, and tuning performant microservices
- creating containerized applications using docker or equivalent tool
- deploying and managing applications in a container orchestration system such as Kubernetes
Other
- Must currently hold a Top Secret/SCI U.S. Government security clearance with a favorable Polygraph, therefore all candidates must be a U.S. citizen
- Seven (7) years experience as a SWE in programs and contracts of similar scope, type, and complexity is required
- Bachelor's degree in Computer Science or related discipline from an accredited college or university is required
- Four (4) years of SWE experience on projects with similar software processes may be substituted for a bachelor's degree.
- Intelligent, adaptable, willing to dive into an array of things ranging from machine learning analytics to Kubernetes to Amazon Web Services
