About the Role

We are looking for a Cloud DevOps & AI Automation Manager with strong experience leading engineering teams while remaining actively involved in the design, implementation, and operation of cloud platforms.

This role will lead initiatives across DevOps, automation, Infrastructure as Code, and cloud engineering, while also driving the practical adoption of Artificial Intelligence to improve engineering productivity, operational efficiency, and process quality.

The ideal candidate combines technical leadership with a hands-on mindset, has experience working directly with clients and business stakeholders, and can effectively communicate technical decisions, risks, priorities, and business impact.

Key Responsibilities

- Lead the design, development, implementation, and evolution of cloud platforms, primarily on Microsoft Azure, as well as AWS or GCP.
- Lead and coordinate distributed engineering teams using Agile methodologies such as Scrum or Kanban.
- Design and implement CI/CD pipelines, infrastructure automation, and Infrastructure as Code using Terraform or similar technologies.
- Work with Kubernetes and scalable, secure, and resilient cloud architectures.
- Maintain high engineering standards across code quality, peer reviews, documentation, and DevOps best practices.
- Remain hands-on and actively participate in troubleshooting, infrastructure automation, and technical implementation.
- Collaborate with Product Owners, Architects, clients, and business stakeholders to define technical roadmaps and priorities.
- Communicate and negotiate technical decisions based on risk, effort, priorities,



and business impact.
- Drive continuous improvement through automation of operational and engineering processes.
- Mentor engineers and promote strong standards of collaboration and technical excellence.
- Identify and implement opportunities to incorporate AI into DevOps, automation, and engineering productivity workflows.

Required Experience

- Bachelor's degree in Engineering, Computer Science, or a related field, or equivalent professional experience.
- 5 years of experience in DevOps, Cloud Engineering, Software Development, Software Architecture, or related areas.
- 2 years of experience leading technical teams in Engineering, DevOps, or Cloud.
- Strong hands-on experience with:
- Microsoft Azure preferred
- AWS and/or GCP
- Kubernetes
- Terraform / Infrastructure as Code
- CI/CD
- Azure DevOps, GitHub Actions, Jenkins, or similar tools
- Experience implementing DevOps practices, automation, and observability.
- Experience leading teams using Scrum or Kanban.
- Strong problem-solving skills across cloud infrastructure and applications.
- Experience working directly with clients and business stakeholders, ideally in consulting, professional services, or global organizations.
- Advanced English proficiency (C1),



as the role requires frequent interaction with international teams and stakeholders, including teams in the United States.

AI & Automation Experience

We are looking for candidates who have practical, professional experience applying AI to solve real business or engineering problems, rather than only using AI tools for personal productivity.

Relevant experience may include

- Designing and implementing AI-enabled automations.
- Integrating generative AI, LLMs, agents, prompts, or AI services into enterprise workflows.
- Using technologies such as Azure OpenAI, Azure AI Services, Microsoft Copilot Studio, GitHub Copilot, Claude, Gemini, or equivalent tools.
- Integrating AI solutions with cloud platforms, APIs, and DevOps tools.
- Demonstrating measurable improvements in productivity, time, quality, or cost through AI-enabled solutions.

Experience with fine-tuning, RAG, embeddings, or vector databases is not required, unless these technologies were part of presente implemented solutions.

Key Competencies

- Technical leadership
- Strong communication and stakeholder management
- Client-facing skills
- Analytical thinking
- Results orientation
- Problem solving
- Negotiation and prioritization
- Collaboration
- Continuous improvement
- Ability to drive innovation through AI

Selection Process

Our process begins with a brief 15–20 minute virtual interview with Paula, our AI Recruiter, to better understand your experience before moving forward with our recruitment team and subsequent client interviews.

📌 Cloud DevOps & AI Automation Manager (Ciudad de México)
🏢 Ingeniosi
📍 Ciudad de México