AI Ops Engineer
Infosys Pontoon
5 days ago
Contract
On-site
Dallas, Texas, United States
Automation
Job Title: AI Ops Engineer
Work Location: Dallas, TX or Bothell, WA
Contract duration: 06 Months
Detailed Job Description:
⦁The role involves building intelligent AI agents capable of autonomous decision-making, incident analysis, remediation recommendations, workflow orchestration, and operational support across cloud-native ecosystems. The candidate will work closely with cloud, application, and platform engineering teams to deliver scalable AI-driven operations solutions.
Key Responsibilities
⦁Design and implement an Agentic AI framework for Cloud Infrastructure and Application Operations.
⦁Build and orchestrate AI agents for monitoring, diagnostics, knowledge retrieval, incident triaging, remediation, and operational automation.
⦁Develop knowledge frameworks utilizing enterprise documentation, operational runbooks, and support processes.
⦁Integrate AI agents with enterprise platforms and operational tools using APIs.
⦁Enable AI-driven automation for cloud monitoring, observability, application support, and operational intelligence.
⦁Collaborate with Cloud and Platform Engineering teams to architect scalable and secure AI-enabled solutions.
⦁Design reusable frameworks, accelerators, and governance models for AI-based operations.
⦁Support Azure cloud environments, Kubernetes platforms, MuleSoft integrations, and enterprise application ecosystems.
⦁Mentor engineering teams and drive adoption of AI-driven operational practices.
Must Have Skills:
⦁Agentic AI / AI Agents development and orchestration
⦁LLM-based solution design and knowledge frameworks
⦁Azure Cloud and Kubernetes
⦁MuleSoft and REST API integrations
⦁AI-driven monitoring, support, and automation
⦁AI Ops Knowledge
⦁Enterprise application and cloud operations
⦁Telecom/OSS Domain is mandatory
⦁Skill Mix: 60% AI / Agentic AI, 40% Cloud & Enterprise Technology.
Nice to Have Skills:
⦁RAG and AI knowledge management frameworks
⦁AIOps and intelligent automation solutions
⦁GenAI governance and observability
⦁Python automation and scripting
⦁Cloud-native architecture and DevOps practices
Minimum Years of Experience: 6 to 7 years
Work Location: Dallas, TX or Bothell, WA
Contract duration: 06 Months
Detailed Job Description:
⦁The role involves building intelligent AI agents capable of autonomous decision-making, incident analysis, remediation recommendations, workflow orchestration, and operational support across cloud-native ecosystems. The candidate will work closely with cloud, application, and platform engineering teams to deliver scalable AI-driven operations solutions.
Key Responsibilities
⦁Design and implement an Agentic AI framework for Cloud Infrastructure and Application Operations.
⦁Build and orchestrate AI agents for monitoring, diagnostics, knowledge retrieval, incident triaging, remediation, and operational automation.
⦁Develop knowledge frameworks utilizing enterprise documentation, operational runbooks, and support processes.
⦁Integrate AI agents with enterprise platforms and operational tools using APIs.
⦁Enable AI-driven automation for cloud monitoring, observability, application support, and operational intelligence.
⦁Collaborate with Cloud and Platform Engineering teams to architect scalable and secure AI-enabled solutions.
⦁Design reusable frameworks, accelerators, and governance models for AI-based operations.
⦁Support Azure cloud environments, Kubernetes platforms, MuleSoft integrations, and enterprise application ecosystems.
⦁Mentor engineering teams and drive adoption of AI-driven operational practices.
Must Have Skills:
⦁Agentic AI / AI Agents development and orchestration
⦁LLM-based solution design and knowledge frameworks
⦁Azure Cloud and Kubernetes
⦁MuleSoft and REST API integrations
⦁AI-driven monitoring, support, and automation
⦁AI Ops Knowledge
⦁Enterprise application and cloud operations
⦁Telecom/OSS Domain is mandatory
⦁Skill Mix: 60% AI / Agentic AI, 40% Cloud & Enterprise Technology.
Nice to Have Skills:
⦁RAG and AI knowledge management frameworks
⦁AIOps and intelligent automation solutions
⦁GenAI governance and observability
⦁Python automation and scripting
⦁Cloud-native architecture and DevOps practices
Minimum Years of Experience: 6 to 7 years