Job Description :
Youll Get To :
- Evaluate and oversee the implementation of innovative technologies aimed at improving the efficiency, performance, and reliability of the Lytx Infrastructure.
- Engage with innovative technologies such as Kubernetes, MQTT, and Kafka.
- Implement new systems and frameworks to bolster a global IoT platform and elevate it to the next level.
- Develop and deliver innovative solutions that empower engineering teams.
- Develop and implement MLOps practices to improve the speed, efficiency, and quality of our AI/ML deployments.
- Design Data/Machine Learning pipelines to transform Data/Machine Learning features.
- Propel and execute enhancements in capacity, reliability, availability, monitoring, and performance of core and supporting systems.
- Fulfill other assigned duties.
What You Need :
- A bachelor's/masters degree with a technical major or equivalent experience.
- 4+ years of experience in designing, building, and supporting Infrastructure Architecture, CI/CD, and production operations within a hybrid On-Premises/Cloud environment.
- Expertise in DevOps principles, practices, and technologies, including GitOps, Amazon Web Services (AWS), and Terraform, or other Infrastructure as Code (IaC) tools.
- Proficiency in building CI/CD pipelines, with preference given to experience with GitHub and ArgoCD.
- Proficiency in managing Kubernetes and various container and cloud-native technologies.
- Proven experience in security best practices, including identity and access management, encryption, and vulnerability assessments.
- Strong knowledge of containerization technologies such as OpenShift, Kubernetes, and Docker.
- Expertise in scripting/automation using tools like PowerShell, BASH, Python, Perl, Ansible, and Terraform.
- Provide coaching, mentoring, and training for new or less experienced team members.
- Knowledge of Systems Administration/System Engineering with Microsoft Windows/Linux.
- Familiarity with networking concepts such as routing, load balancing, DNS, content delivery, and domain trusts.
- Excellent documentation and interpersonal skills, with the ability to present technical content to management and engineering teams.
- Hands-on experience with AWS compute and storage services including EKS, ECS, Lambda, EC2, MSK, AMIs, Redshift, Kinesis, RDS, DynamoDB, ElastiCache, S3, and Glacier.
- Collaborate with engineering teams to enhance their productivity, ensure they operate on reliable and scalable systems, and advocate for best practices, including GitOps principles.
Preferred :
- AWS Advanced and Specialty level Certifications.
- Experience with ML and Data platforms, including developing and implementing MLOps practices and designing Data/Machine Learning pipelines.
- Experience in managing middleware systems - Service Mesh, API Gateway, Kafka, and MQTT.
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