📍 Job Overview

Job Title: Middle Infrastructure Engineer (ML/AI)
Company: Workato
Location: Nicosia, Lefkosía, Cyprus
Job Type: On-site
Category: DevOps Engineer
Date Posted: 2025-07-15
Experience Level: Mid-level (2-5 years)

🚀 Role Summary

📝 Enhancement Note: This role focuses on deploying, scaling, and maintaining services for the ML/AI team, working closely with ML Engineers and Data Scientists. The ideal candidate will have a strong background in infrastructure engineering, with a focus on AI and machine learning.

💻 Primary Responsibilities

📝 Enhancement Note: The primary responsibilities of this role involve infrastructure architecture decisions, modernizing and maturing the platform, and collaborating with cross-functional teams to ensure seamless integration and deployment of AI models.
📝 Enhancement Note: This role requires a deep understanding of infrastructure as code (IaC) principles, experience with cloud platforms (AWS, Azure), and proficiency in containerization (Kubernetes) to manage and scale services efficiently.
📝 Enhancement Note: The candidate should be comfortable working in a dynamic, fast-paced environment and have a strong problem-solving mindset to tackle complex infrastructure challenges.

🎓 Skills & Qualifications

Education: BS/MS degree in Computer Science, Engineering, or a related subject (or equivalent experience)

Experience: 3-5 years of professional experience in hands-on engineering roles (DevOps/SRE)

Required Skills:

📝 Enhancement Note: Proficiency in Python is essential, and experience with other programming languages such as Go, Ruby, or JavaScript is a plus.
Kubernetes expertise: Strong experience managing Kubernetes clusters and workloads, specifically using EKS (Elastic Kubernetes Service)
Experience with hosting AI models (ML flow, AWS SageMaker, Azure AI, Kubernetes)
Experience with ML Ops (ML flow, vector databases (Qdrant), Dagster)
📝 Enhancement Note: Familiarity with infrastructure as code (IaC) tools (Terraform, CloudFormation) and version control systems (Git) is expected.

Preferred Skills:

Experience with cloud platforms (AWS, Azure, GCP)
📝 Enhancement Note: Knowledge of AI/ML frameworks (TensorFlow, PyTorch) and data processing tools (Apache Spark, Pandas) is a plus.

Soft Skills / Personal Characteristics:

Readiness to communicate in English with colleagues
📝 Enhancement Note: The ideal candidate should possess strong communication skills, be a team player, and have a growth mindset to continuously learn and adapt in a fast-paced environment.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

📝 Enhancement Note: A well-structured portfolio showcasing previous infrastructure projects, AI/ML model deployments, and Kubernetes cluster management is essential.
📝 Enhancement Note: Include case studies demonstrating problem-solving, performance optimization, and scalability in infrastructure projects.

Technical Documentation:

📝 Enhancement Note: Provide clear and concise documentation for infrastructure projects, including architecture decisions, deployment processes, and server configuration.
📝 Enhancement Note: Include testing methodologies, performance metrics, and optimization techniques used in previous projects.

💵 Compensation & Benefits

Salary Range: €45,000 - €65,000 per year (based on market research for mid-level DevOps engineers in Cyprus)

Benefits:

Competitive salary and equity compensation
📝 Enhancement Note: Workato offers comprehensive health, dental, and vision insurance plans for employees and their dependents.
Flexible time off and company-wide holidays
📝 Enhancement Note: Workato provides a flexible work environment with remote work options and a focus on work-life balance.
Professional development opportunities and career growth
📝 Enhancement Note: Workato invests in employee growth through training, workshops, and conference attendance.
📝 Enhancement Note: Workato offers additional perks, such as wellness reimbursements, commuter benefits, and employee discounts.

Working Hours: Full-time (40 hours/week) with flexible scheduling and maintenance windows

🎯 Team & Company Context

🏢 Company Culture

Industry: Enterprise automation and integration software

Company Size: Medium (250-999 employees)

Founded: 2013

Team Structure:

📝 Enhancement Note: The ML/AI team consists of international senior-level professionals with experience in integration, cloud, and consumer experience.
📝 Enhancement Note: The team is unique in its multinational composition and collaborative approach to building high-performing, scalable enterprise-grade applications.

Development Methodology:

📝 Enhancement Note: Workato follows Agile methodologies, with a focus on continuous integration, delivery, and deployment.
📝 Enhancement Note: The company emphasizes code reviews, testing, and quality assurance practices to ensure high-quality software delivery.
📝 Enhancement Note: Workato uses CI/CD pipelines and automated deployment tools to streamline the development process and ensure rapid iteration.

Company Website: workato.com

📈 Career & Growth Analysis

Web Technology Career Level: Mid-level infrastructure engineer, responsible for deploying, scaling, and maintaining services for the ML/AI team, with a focus on AI and machine learning.

Reporting Structure: This role reports directly to the ML/AI team lead and works closely with ML Engineers, Data Scientists, and other cross-functional teams.

Technical Impact: The middle infrastructure engineer will have a direct impact on the modernization and maturation of the platform, including infrastructure architecture decisions, and will collaborate with cross-functional teams to ensure seamless integration and deployment of AI models.

Growth Opportunities:

📝 Enhancement Note: Workato offers opportunities for professional development and career growth within the ML/AI team and across the organization.
📝 Enhancement Note: As the company continues to grow, there will be opportunities for the middle infrastructure engineer to take on more responsibilities and advance their career in the field of AI and machine learning.

🌐 Work Environment

Office Type: On-site with remote work options available

Office Location(s): Nicosia, Lefkosía, Cyprus

Workspace Context:

📝 Enhancement Note: Workato provides a vibrant and dynamic work environment, with a focus on balancing productivity with self-care.
📝 Enhancement Note: The company offers a multitude of benefits to help employees enjoy their work lives, both inside and outside the office.

Work Schedule: Full-time (40 hours/week) with flexible scheduling and maintenance windows

📄 Application & Technical Interview Process

Interview Process:

📝 Enhancement Note: The interview process for this role will consist of a combination of technical assessments, behavioral interviews, and case studies to evaluate the candidate's technical skills and cultural fit.
📝 Enhancement Note: The candidate should expect to demonstrate their expertise in infrastructure engineering, AI/ML model deployment, and Kubernetes cluster management throughout the interview process.

Portfolio Review Tips:

📝 Enhancement Note: Candidates should focus on showcasing their infrastructure projects, AI/ML model deployments, and Kubernetes cluster management skills in their portfolio.
📝 Enhancement Note: Include case studies demonstrating problem-solving, performance optimization, and scalability in infrastructure projects to highlight the candidate's technical expertise.

Technical Challenge Preparation:

📝 Enhancement Note: Candidates should expect to complete technical challenges related to infrastructure engineering, AI/ML model deployment, and Kubernetes cluster management during the interview process.
📝 Enhancement Note: Familiarize yourself with the latest trends and best practices in AI/ML and infrastructure engineering to demonstrate your expertise and commitment to continuous learning.

ATS Keywords:

📝 Enhancement Note: Include relevant keywords related to infrastructure engineering, AI/ML, and Kubernetes in your resume and portfolio to optimize your application for Applicant Tracking Systems (ATS).

🛠 Technology Stack & Web Infrastructure

Frontend Technologies:

📝 Enhancement Note: Not applicable for this role, as it focuses on infrastructure engineering and AI/ML.

Backend & Server Technologies:

Kubernetes (EKS)
AWS (SageMaker, RDS, EKS)
Azure (AI, AKS)
MLflow
Qdrant
Dagster
Terraform
CloudFormation
Python
Go
Ruby
JavaScript

Development & DevOps Tools:

Git
Jenkins
CircleCI
Docker
📝 Enhancement Note: Familiarity with CI/CD pipelines, automated deployment, and infrastructure as code (IaC) tools is expected.

👥 Team Culture & Values

Web Development Values:

📝 Enhancement Note: Workato values innovation, collaboration, and a growth mindset in its team members.
📝 Enhancement Note: The company emphasizes continuous learning, technical excellence, and a strong commitment to user experience and accessibility.

Collaboration Style:

📝 Enhancement Note: Workato fosters a collaborative work environment, with a focus on cross-functional integration between teams.
📝 Enhancement Note: The company encourages knowledge sharing, technical mentoring, and continuous learning to drive innovation and growth.

⚡ Challenges & Growth Opportunities

Technical Challenges:

📝 Enhancement Note: This role presents challenges in deploying, scaling, and maintaining services for the ML/AI team, with a focus on AI and machine learning.
📝 Enhancement Note: The middle infrastructure engineer will need to stay up-to-date with the latest trends and best practices in AI/ML and infrastructure engineering to tackle these challenges effectively.

Learning & Development Opportunities:

📝 Enhancement Note: Workato offers opportunities for professional development and career growth within the ML/AI team and across the organization.
📝 Enhancement Note: The company encourages continuous learning and provides resources for employees to develop their skills and advance their careers in the field of AI and machine learning.

💡 Interview Preparation

Technical Questions:

📝 Enhancement Note: Candidates should expect to be asked technical questions related to infrastructure engineering, AI/ML model deployment, and Kubernetes cluster management during the interview process.
📝 Enhancement Note: Brush up on your knowledge of infrastructure as code (IaC) principles, cloud platforms (AWS, Azure), and containerization (Kubernetes) to demonstrate your expertise in these areas.

Company & Culture Questions:

📝 Enhancement Note: Prepare for questions about Workato's company culture, values, and mission to demonstrate your cultural fit and commitment to the organization.

Portfolio Presentation Strategy:

📝 Enhancement Note: Candidates should focus on presenting their infrastructure projects, AI/ML model deployments, and Kubernetes cluster management skills in their portfolio.
📝 Enhancement Note: Include case studies demonstrating problem-solving, performance optimization, and scalability in infrastructure projects to highlight the candidate's technical expertise.

📌 Application Steps

To apply for this middle infrastructure engineer (ML/AI) position at Workato:

Submit your application through the application link provided.
Customize your portfolio with live demos and responsive examples, highlighting your infrastructure projects, AI/ML model deployments, and Kubernetes cluster management skills.
Optimize your resume for web technology roles, emphasizing your project highlights and technical skills, with a focus on infrastructure engineering, AI/ML, and Kubernetes.
Prepare for technical interviews by completing coding challenges and portfolio presentations, focusing on your expertise in infrastructure engineering, AI/ML model deployment, and Kubernetes cluster management.
Research Workato's company culture, values, and mission to demonstrate your cultural fit and commitment to the organization.

📝 Enhancement Note: This enhanced job description includes AI-generated insights and web development/server administration industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Middle Infrastructure Engineer (ML/AI)