Job Description & How to Apply Below
About Awiros
Awiros is a Series Afunded deep-tech organization ($7M raised) building the worlds first app-based Operating System for Computer Vision. Founded in 2015, we enable developers and enterprises to build, deploy, and scale cutting-edge AI-powered applications with speed and efficiency. Our platform is built for real-time video/image inference, distributed processing, and high-throughput data handling powered by tools like Tensor Flow, Kubernetes, Kafka, and Elastic Search.
Behind it is a stellar team of researchers and engineers, focused on bringing the latest in Deep Learning and AI research to real-world applications. At Awiros, we are not just shaping the future of Computer Vision we're making it accessible to everyone.
About
The Role
As a Dev Ops Engineer at Awiros, you will be part of the core platform engineering effort that enables large-scale AI workloads to run reliably across cloud, on-premise, and hybrid environments. This is a build-oriented role, where you will design, automate, and evolve deployment systems rather than merely operating them. You will work closely with application, platform, and AI teams to develop scalable CI/CD pipelines, cloud-native infrastructure, and deployment frameworks that support real-time, GPU-driven workloads.
This role is ideal for engineers who enjoy building systems, experimenting with modern Dev Ops tooling, and owning infrastructure as a product.
What Youll Do
Design, build, and continuously improve CI/CD pipelines to accelerate development and production releases
Develop and maintain containerized applications using Docker and Kubernetes
Build and manage large-scale distributed deployments across cloud, on-premise, multi-site, and air-gapped environments
Work with GPU-enabled infrastructure and master-worker architectures to support AI inference workloads
Design and maintain highly available Kubernetes clusters, database clusters, and message queues
Develop and maintain Helm charts for multiple microservices and platform components
Build and version deployment stacks, including Kafka, queue systems, and supporting middleware
Implement Infrastructure as Code using tools such as Terraform, Cloud Formation, or Ansible
Collaborate with development teams to design new deployment workflows and automation frameworks
Improve observability by building and maintaining logging, monitoring, and alerting systems
Integrate Dev Sec Ops practices into CI/CD pipelines using tools such as Sonar Qube, Trivy, or similar
Own and evolve internal Dev Ops tooling to support fast, reliable, and secure releases
What Were Looking For
1+ years of hands-on experience in Dev Ops, Platform Engineering, SRE, or Cloud Engineering
Strong practical experience with Docker and Kubernetes
Experience building CI/CD pipelines using Jenkins, Git-based workflows, and Git Ops practices
Hands-on exposure to cloud platforms such as AWS or GCP
Experience working with distributed systems such as Kafka, Rabbit
MQ, Redis, or similar technologies
Familiarity with Infrastructure as Code tools like Terraform and Cloud Formation
Scripting skills in Bash, Python, or equivalent languages
Exposure to Dev Sec Ops tooling and secure pipeline practices
Strong debugging, analytical thinking, documentation, and collaboration skills
Experience with monitoring and logging stacks such as Prometheus, Grafana, ELK/EFK
Good To Have
Exposure to additional cloud platforms such as Azure or Oracle Cloud
Understanding of cloud-native, microservices-based system design
Experience managing multi-environment deployments (dev, staging, production)
Knowledge of security best practices in containerized and cloud environments
Relevant certifications (AWS, Kubernetes, or Dev Ops-focused)
WHY JOIN AWIROS
Build and scale real-time AI and Computer Vision platforms used in production environments
Work on complex, distributed systems spanning cloud, edge, and on-premise deployments
Learn by building in a high-ownership, deep-tech engineering culture
Collaborate closely with experienced platform, AI, and systems engineers
Influence how modern Dev Ops and platform engineering practices are implemented at scale
(t.tech)
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