Remote Senior AI & MLOps Engineer: GenAI & Cloud

Infoya

United States

Remote

USD 140,000 - 200,000

Full time

2 days ago
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Job summary

Infoya is a remote-friendly senior AI & MLOps Engineer role focused on deploying and managing AI-powered products across enterprise cloud environments. The candidate will work with client architects, infrastructure teams and business stakeholders to ensure scalability, security and reliable production deployments.

The role requires hands-on experience with Agentic AI, GenAI, cloud engineering, and MLOps/LLMOps, including monitoring and performance optimization.

Qualifications

  • 7–12 years of overall IT experience.
  • 4+ years in Cloud/DevOps/MLOps engineering.
  • 2+ years of hands-on AI/GenAI deployment or integration.
  • Proven experience deploying enterprise applications into production.
  • Ability to independently manage client technical discussions and deployment challenges.
  • Experience deploying Agentic AI products in enterprise environments (preferred).

Responsibilities

  • Deploy and manage Agentic AI/GenAI solutions across AWS, Azure and GCP.
  • Design scalable, secure cloud architectures for AI applications.
  • Build and manage CI/CD pipelines, containerization and deployment automation.
  • Implement MLOps/LLMOps practices, AI monitoring, observability and performance optimization.
  • Integrate AI platforms with enterprise applications, APIs, databases and authentication systems.
  • Work directly with client cloud, infrastructure and security teams to manage deployments.
  • Own end-to-end technical implementation from POC to production go-live.
  • Collaborate with internal AI product engineering teams to improve deployment efficiency and reliability.

Skills

AI/GenAI
Cloud
MLOps/LLMOps
Monitoring
Security
Soft Skills

Tools

MLflow
Vertex AI
SageMaker
Prometheus
Grafana
OpenTelemetry

Job description

Infoya is a remote-friendly senior AI & MLOps Engineer role focused on deploying and managing AI-powered products across enterprise cloud environments. The candidate will work with client architects, infrastructure teams and business stakeholders to ensure scalability, security and reliable production deployments.

The role requires hands-on experience with Agentic AI, GenAI, cloud engineering, and MLOps/LLMOps, including monitoring and performance optimization.

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