Remote MLOps & AI Infrastructure Engineer

Aimlroles

United States

Remote

USD 150,000 - 190,000

Full time

4 days ago
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Benefits offered by this job

Remote First Work Environment (US Base
Medical, Dental, Vision
401K, 401K Match
Life and Disability Benefits
Unaccrued Paid Time Off
11 Paid Holidays
Employee Discounts
Employee Assistance Program
Educational Assistance Program
Employee Referral Program
Paid Parental Leave

Job summary

Mission Underwriters seeks an MLOps and AI Infrastructure Engineer to build and operate production-grade infrastructure across our AI platforms. This hands-on role sits at the intersection of cloud engineering, DevOps, AI platform operations, and governance.

You will ensure secure, observable, scalable, and auditable AI infrastructure ready for enterprise production use. This role owns practices that move AI workloads safely from development to production, including deployment automation, CI/CD,

Qualifications

  • Five+ years in cloud infrastructure, DevOps, MLOps, or AI platform engineering on AWS/Azure.
  • Hands-on with IAM, network security, encryption, DR/BC.
  • Experience deploying AI workloads with LLMs, RAG, or agent frameworks.

Responsibilities

  • Define production-readiness standards for agentic AI platforms.
  • Design, build, and operate Azure and AWS AI infrastructure.
  • Create reference architectures, landing zones, and governance controls.
  • Build CI/CD pipelines for infrastructure, models, prompts, agents, and services.
  • Monitor, secure, and audit AI platforms across environments.

Skills

Cloud infrastructure
DevOps
MLOps
AI platform operations
Cloud security
Observability
Incident response
Governance
APIs
Terraform
Bicep
Azure DevOps
Bitbucket Pipelines
CI/CD

Education

Bachelor's degree in CS/Engineering/IS
AWS & Azure architecture certifications

Tools

Terraform
Bicep
Azure DevOps
Bitbucket Pipelines

Job description

Mission Underwriters seeks an MLOps and AI Infrastructure Engineer to build and operate production-grade infrastructure across our AI platforms. This hands-on role sits at the intersection of cloud engineering, DevOps, AI platform operations, and governance.

You will ensure secure, observable, scalable, and auditable AI infrastructure ready for enterprise production use. This role owns practices that move AI workloads safely from development to production, including deployment automation, CI/CD,

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