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Updated 2026-06-11 13:00 UTC·© 2025–2026 RoleSuite
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Azure DevOps Engineer (AI / Agentic) ML Ops Engineer

Jobgether · Brazil

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior MLOps Engineer (DevOps AI / Agentic Focus) based in Brazil.

This role sits at the intersection of cloud engineering, DevOps, and applied AI, with a strong emphasis on building intelligent, autonomous infrastructure systems.
You will contribute to a high-impact engineering environment focused on evolving traditional DevOps into AI-driven platform engineering.
The work goes beyond standard pipeline management, pushing toward self-healing, scalable, and highly automated cloud ecosystems.
You will play a strategic role in shaping architecture and introducing LLM-powered automation into real-world infrastructure workflows.
The environment is remote-first, collaborative, and aligned with North American time zones, requiring strong communication and autonomy.
This is an opportunity to influence system design at scale while working on cutting-edge automation and cloud innovation.

Accountabilities:

  • Drive AI-driven automation initiatives by designing and implementing workflows that integrate LLMs and AI tools to reduce operational toil and improve DevOps efficiency.
  • Architect, deploy, and optimize scalable cloud infrastructure on Microsoft Azure, ensuring performance, security, and reliability.
  • Define and evolve CI/CD and Infrastructure as Code strategies using modern tools to enable robust delivery pipelines.
  • Act as a strategic technical advisor, contributing to architecture decisions, system design reviews, and technical alignment.
  • Improve system observability, reliability, and cost efficiency through monitoring, reviews, and continuous optimization.
  • Requirements:

    • 7+ years of experience in DevOps, Cloud Engineering, Platform Engineering, or Infrastructure Architecture.
    • Strong expertise in Microsoft Azure, including AKS, networking, compute, and native monitoring tools.
    • Advanced experience with Infrastructure as Code tools such as Terraform, Bicep, or ARM templates.
    • Strong programming and automation skills in Python, Bash, or PowerShell.
    • Practical experience applying AI or Large Language Models to DevOps or engineering workflows.
    • Expertise in CI/CD tools such as GitHub Actions or Jenkins.
    • Strong research and experimentation mindset focused on scalable system design.
    • Experience working in agile, fully remote environments with fluent English communication.
    • Benefits:

      • Fully remote opportunity across Latin America
      • Long-term international engineering projects
      • Exposure to AI-driven DevOps and platform engineering innovation
      • Collaborative and innovation-focused environment
      • Flexible schedule aligned with EST (5–6 hours overlap required)
      • Opportunity to work on advanced cloud and automation challenges

AI Engineering pay context

Based on 638 disclosed AI Engineering salaries on RoleSuite, the role pays a median of $202K/year, with most offers between $162K and $246K (10th–90th percentile: $131K–$285K).

See the full AI Engineering salary breakdown →
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