Flexton Inc. is hiring: Artificial Intelligence Engineer in Austin
Flexton Inc., Austin, TX, United States
This range is provided by Flexton Inc.. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base Pay Range
$50.00/hr - $60.00/hr
Location
Austin, TX
Job Summary
We are seeking an experienced Cloud and Kubernetes Engineer to design, implement, and manage workflows that enable AI systems to learn and operate effectively using Agentic AI methodologies. The ideal candidate will have strong expertise in Kubernetes, cloud-native architectures, and DevOps practices, with the ability to translate complex technical concepts into scalable AI workflows. Experience with LangGraph or LangChain is a plus. Rag models.
Key Responsibilities
Develop and manage AI learning workflows using Agentic AI principles, integrating with platforms such as LangGraph and LangChain.
Deploy, monitor, and troubleshoot Kubernetes clusters, including Pods, Deployments, Services, ConfigMaps, Secrets, API server, and Etcd.
Implement cloud-native solutions, supporting microservices, containerization, and CI/CD pipelines.
Configure and manage monitoring and logging tools (Prometheus, Grafana, ELK, or equivalent) to ensure high availability and observability.
Collaborate with cross-functional teams to design automated incident management and ticketing workflows using tools like Jira or ServiceNow.
Apply networking knowledge for DNS, Load Balancing, and Ingress to optimize system performance.
Maintain high standards of accountability and ownership, driving issues to resolution while communicating effectively with both technical and non-technical stakeholders.
Required Skills & Experience
Minimum 5 years of experience in Cloud Operations, DevOps, or Kubernetes-based environments.
Hands‑on experience with Kubernetes fundamentals, architecture, controllers, admission webhooks, and basic troubleshooting.
Strong Linux administration skills and proficiency in scripting languages (Bash, Python preferred).
Basic understanding of cloud-native concepts, microservices, and CI/CD pipelines.
Experience with monitoring/logging tools (Prometheus, Grafana, ELK, or equivalent).
Familiarity with incident management and ticketing workflows (e.g., Jira, ServiceNow).
Excellent communication skills, capable of explaining technical issues to non-technical audiences.
Kubernetes certification (CKA/CKS) or equivalent practical experience.
Preferred Skills
Experience with AI workflow orchestration and Agentic AI development.
Familiarity with LangGraph, LangChain, or other AI workflow frameworks.
Seniority Level
Mid‑Senior level
Employment Type
Contract
Job Function
Information Technology
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Base Pay Range
$50.00/hr - $60.00/hr
Location
Austin, TX
Job Summary
We are seeking an experienced Cloud and Kubernetes Engineer to design, implement, and manage workflows that enable AI systems to learn and operate effectively using Agentic AI methodologies. The ideal candidate will have strong expertise in Kubernetes, cloud-native architectures, and DevOps practices, with the ability to translate complex technical concepts into scalable AI workflows. Experience with LangGraph or LangChain is a plus. Rag models.
Key Responsibilities
Develop and manage AI learning workflows using Agentic AI principles, integrating with platforms such as LangGraph and LangChain.
Deploy, monitor, and troubleshoot Kubernetes clusters, including Pods, Deployments, Services, ConfigMaps, Secrets, API server, and Etcd.
Implement cloud-native solutions, supporting microservices, containerization, and CI/CD pipelines.
Configure and manage monitoring and logging tools (Prometheus, Grafana, ELK, or equivalent) to ensure high availability and observability.
Collaborate with cross-functional teams to design automated incident management and ticketing workflows using tools like Jira or ServiceNow.
Apply networking knowledge for DNS, Load Balancing, and Ingress to optimize system performance.
Maintain high standards of accountability and ownership, driving issues to resolution while communicating effectively with both technical and non-technical stakeholders.
Required Skills & Experience
Minimum 5 years of experience in Cloud Operations, DevOps, or Kubernetes-based environments.
Hands‑on experience with Kubernetes fundamentals, architecture, controllers, admission webhooks, and basic troubleshooting.
Strong Linux administration skills and proficiency in scripting languages (Bash, Python preferred).
Basic understanding of cloud-native concepts, microservices, and CI/CD pipelines.
Experience with monitoring/logging tools (Prometheus, Grafana, ELK, or equivalent).
Familiarity with incident management and ticketing workflows (e.g., Jira, ServiceNow).
Excellent communication skills, capable of explaining technical issues to non-technical audiences.
Kubernetes certification (CKA/CKS) or equivalent practical experience.
Preferred Skills
Experience with AI workflow orchestration and Agentic AI development.
Familiarity with LangGraph, LangChain, or other AI workflow frameworks.
Seniority Level
Mid‑Senior level
Employment Type
Contract
Job Function
Information Technology
#J-18808-Ljbffr