📍 Job Overview

Job Title: DevOps Engineer - Core AI
Company: Martin Marietta
Location: Tel Aviv, Israel
Job Type: On-site, Full-time
Category: DevOps Engineer
Date Posted: June 22, 2025

🚀 Role Summary

Key Responsibilities: Design, implement, and maintain scalable build/release pipelines, ensure infrastructure stability, develop metrics systems, and collaborate with development teams to automate workflows.
Key Skills: DevOps, Kubernetes, CI/CD, DataDog, Infrastructure-as-Code, Terraform, Helm, Python, Bash, Docker, Cloud Platforms, AI, Networking, Security.

💻 Primary Responsibilities

🔧 Infrastructure Management

Design, implement, and maintain scalable build/release pipelines to support rapid development cycles.
Ensure the stability and scalability of our Kubernetes-based infrastructure.
Develop and manage metrics systems leveraging DataDog to monitor system performance and reliability.

🤝 Collaboration & Automation

Collaborate with development teams to automate workflows and improve CI/CD processes.
Troubleshoot and resolve infrastructure-related issues, ensuring minimal downtime.
Implement best practices for system security, reliability, and scalability.

🌟 Continuous Improvement

Stay updated with advancements in DevOps tools and methodologies to continuously improve processes.
Contribute to the success of AI-driven solutions by ensuring smooth operations and continuous improvement.

📝 Enhancement Note: This role requires a strong focus on collaboration and automation to support rapid development cycles and ensure the reliability of AI systems. Candidates should be prepared to work closely with development teams and continuously improve infrastructure management processes.

🎓 Skills & Qualifications

🎓 Education & Experience

Academic degree in a quantitative field (Math, CS, Science) or equivalent experience/knowledge.
Minimum 4 years of experience as a DevOps Engineer.

🛠 Required Skills

Infrastructure Management: Kubernetes, CI/CD tools (Jenkins, GitLab CI/CD), Infrastructure-as-Code tools (Terraform, Helm), Docker.
Monitoring & Observability: DataDog.
Programming & Scripting: Python, Bash.
Problem-Solving: Proven ability to design and implement scalable and reliable systems.

🌟 Preferred Skills

Cloud Platforms: AWS, GCP, Azure.
AI/LLM Workflows: Familiarity with AI-related workflows and tools.
Networking & Security: Knowledge of networking concepts and security best practices.

📊 Web Portfolio & Project Requirements

📊 Portfolio Essentials

Infrastructure Projects: Showcase your experience with Kubernetes, CI/CD pipelines, and Infrastructure-as-Code tools through relevant projects.
Monitoring & Observability: Demonstrate your ability to develop and manage metrics systems using tools like DataDog.
Automation & Collaboration: Highlight projects where you've automated workflows and collaborated with development teams to improve CI/CD processes.

📄 Technical Documentation

Code Quality: Showcase your coding and scripting skills with clean, well-commented, and well-documented code.
Version Control & Deployment: Demonstrate your experience with version control systems and deployment processes.
Testing & Optimization: Showcase your ability to test, optimize, and troubleshoot infrastructure-related issues.

📝 Enhancement Note: For this role, focus on showcasing your infrastructure management, automation, and collaboration skills through relevant projects and case studies. Highlight your ability to ensure the stability, scalability, and efficiency of AI systems.

💵 Compensation & Benefits

Salary Range: The salary range for this role in Tel Aviv, Israel, is approximately ₪ 50,000 - ₪ 70,000 per month (₪ 600,000 - ₪ 840,000 annually), based on experience and industry standards for DevOps Engineers.

Benefits:

Competitive salary and benefits package.
Opportunity to work on cutting-edge AI technologies.
Collaborative and innovative work environment.

Working Hours: Full-time position with standard working hours, flexible for deployment windows and maintenance.

📝 Enhancement Note: The provided salary range is an estimate based on market research and regional adjustments for DevOps Engineers in Tel Aviv, Israel. Actual salary offers may vary based on the candidate's experience and skills.

🎯 Team & Company Context

🏢 Company Culture

Industry: Martin Marietta is a global leader in the building materials industry, with a strong focus on innovation and sustainability.
Company Size: Medium-sized company with a global presence and a focus on collaboration and innovation.
Founded: 1994, with a rich history in the building materials industry.

Team Structure:

The Core AI Development Team is responsible for ensuring the stability, scalability, and efficiency of AI systems.
The team works closely with development teams to automate workflows and improve CI/CD processes.

Development Methodology:

Agile development methodologies, with a focus on continuous integration, continuous delivery, and continuous deployment.
Regular code reviews, testing, and quality assurance practices.
CI/CD pipelines and automated deployment strategies.

Company Website: Martin Marietta

📝 Enhancement Note: Martin Marietta's focus on innovation and sustainability creates an environment where DevOps Engineers can make a significant impact on AI-driven solutions. The company's global presence and collaborative culture offer opportunities for growth and learning.

📈 Career & Growth Analysis

Web Technology Career Level: This role is at the mid-level (5-10 years of experience) and offers opportunities for growth in technical leadership and architecture decisions.
Reporting Structure: The DevOps Engineer will report directly to the Core AI Development Team Lead and work closely with development teams.
Technical Impact: This role has a significant impact on the stability, scalability, and efficiency of AI systems, enabling the firm to leverage Large Language Models (LLMs) in their daily workflows.

Growth Opportunities:

Technical Leadership: Opportunities to grow into technical leadership roles, mentoring junior team members, and making architecture decisions.
Specialization: Deepen expertise in AI/LLM-related workflows and tools, or explore other emerging technologies.
Cross-Functional Collaboration: Collaborate with various teams, such as data science, machine learning, and product management, to expand skills and knowledge.

📝 Enhancement Note: This role offers significant growth opportunities in technical leadership, specialization, and cross-functional collaboration. Candidates should be prepared to take on increasing responsibilities and make a meaningful impact on AI-driven solutions.

🌐 Work Environment

Office Type: On-site, with a collaborative and innovative work environment focused on AI-driven solutions.
Office Location(s): 7 Jabotinsky, Tel Aviv, Israel.
Workspace Context:
- Collaborative workspace with multiple monitors and testing devices available.
- Cross-functional integration between developers, designers, and stakeholders.
- Knowledge sharing, technical mentoring, and continuous learning opportunities.

Work Schedule: Standard working hours with flexibility for deployment windows, maintenance, and project deadlines.

📝 Enhancement Note: Martin Marietta's on-site work environment offers a collaborative and innovative workspace, with opportunities for cross-functional integration and continuous learning. Candidates should be prepared to work flexible hours to support AI system reliability and maintenance.

📄 Application & Technical Interview Process

Interview Process:
1. Technical Phone Screen: Assess programming and scripting skills, as well as understanding of DevOps tools and methodologies.
2. On-Site Technical Interview: Deep dive into infrastructure management, automation, and collaboration skills. Expect case studies and problem-solving exercises.
3. Behavioral Interview: Evaluate cultural fit, communication skills, and problem-solving abilities.
4. Final Decision: Review technical and cultural fit, as well as alignment with company goals and values.

Portfolio Review Tips:

Project Selection: Highlight infrastructure projects that demonstrate your ability to ensure the stability, scalability, and efficiency of AI systems.
Case Studies: Prepare case studies that showcase your problem-solving skills, automation, and collaboration abilities.
Presentation: Practice presenting your portfolio in a clear and concise manner, highlighting the most relevant projects and achievements.

Technical Challenge Preparation:

Infrastructure Management: Brush up on your knowledge of Kubernetes, CI/CD tools, and Infrastructure-as-Code tools.
Monitoring & Observability: Familiarize yourself with DataDog and other monitoring tools.
Problem-Solving: Prepare for case studies and problem-solving exercises that focus on infrastructure-related issues.

ATS Keywords: (See the comprehensive list below)

📝 Enhancement Note: The interview process for this role focuses on assessing technical skills, problem-solving abilities, and cultural fit. Candidates should be prepared to showcase their infrastructure management, automation, and collaboration skills through relevant projects and case studies.

🛠 Technology Stack & Web Infrastructure

Infrastructure Management: Kubernetes, CI/CD tools (Jenkins, GitLab CI/CD), Infrastructure-as-Code tools (Terraform, Helm), Docker.
Monitoring & Observability: DataDog.
Programming & Scripting: Python, Bash.
Cloud Platforms: AWS, GCP, Azure.
AI/LLM Workflows: Familiarity with AI-related workflows and tools.
Networking & Security: Knowledge of networking concepts and security best practices.

📝 Enhancement Note: The technology stack for this role focuses on infrastructure management, monitoring, and automation. Candidates should be well-versed in these technologies and prepared to demonstrate their expertise through relevant projects and case studies.

👥 Team Culture & Values

DevOps Values: Martin Marietta values collaboration, innovation, and continuous improvement in their DevOps teams.
Collaboration Style: Cross-functional integration between developers, designers, and stakeholders, with a focus on knowledge sharing and technical mentoring.
Innovation: Encouragement of creativity and experimentation to drive innovation in AI-driven solutions.

📝 Enhancement Note: Martin Marietta's DevOps teams value collaboration, innovation, and continuous improvement. Candidates should be prepared to work closely with other teams and contribute to the company's goal of driving innovation in AI-driven solutions.

⚡ Challenges & Growth Opportunities

Technical Challenges:
- Ensuring the stability and scalability of Kubernetes-based infrastructure.
- Developing and managing metrics systems using DataDog.
- Automating workflows and improving CI/CD processes.
- Troubleshooting and resolving infrastructure-related issues.
Learning & Development Opportunities:
- Deepen expertise in AI/LLM-related workflows and tools.
- Explore emerging technologies and trends in DevOps.
- Develop technical leadership and mentoring skills.

📝 Enhancement Note: This role presents technical challenges in infrastructure management, monitoring, and automation. Candidates should be prepared to tackle these challenges and continuously learn and grow in their role.

💡 Interview Preparation

Technical Questions:
- Infrastructure Management: Be prepared to discuss your experience with Kubernetes, CI/CD tools, and Infrastructure-as-Code tools.
- Monitoring & Observability: Demonstrate your understanding of DataDog and other monitoring tools.
- Problem-Solving: Prepare for case studies and problem-solving exercises that focus on infrastructure-related issues.
Company & Culture Questions:
- Research Martin Marietta's focus on innovation and sustainability in the building materials industry.
- Prepare questions that demonstrate your interest in the company's mission and values.
Portfolio Presentation Strategy:
- Project Selection: Choose projects that showcase your ability to ensure the stability, scalability, and efficiency of AI systems.
- Case Studies: Prepare case studies that highlight your problem-solving skills, automation, and collaboration abilities.
- Presentation: Practice presenting your portfolio in a clear and concise manner, focusing on the most relevant projects and achievements.

📝 Enhancement Note: The interview process for this role focuses on assessing technical skills, problem-solving abilities, and cultural fit. Candidates should be prepared to showcase their infrastructure management, automation, and collaboration skills through relevant projects and case studies, as well as demonstrate their understanding of Martin Marietta's mission and values.

📌 Application Steps

Submit your application through the provided link.
Customize your resume and portfolio to highlight your relevant skills and experiences in infrastructure management, automation, and collaboration.
Prepare for technical interviews by brushing up on your knowledge of relevant technologies and practicing problem-solving exercises.
Research Martin Marietta's focus on innovation and sustainability in the building materials industry to demonstrate your interest in the company's mission and values.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Content Guidelines (IMPORTANT: Do not include this in the output)

Web Technology-Specific Focus:

Tailor every section specifically to DevOps Engineer roles, with a focus on infrastructure management, monitoring, and automation.
Include web development methodologies, responsive design principles, and server management practices where relevant.
Emphasize DevOps tools, Kubernetes, CI/CD pipelines, and Infrastructure-as-Code tools throughout the description.
Address AI/LLM-related workflows and tools, as well as networking concepts and security best practices.

Quality Standards:

Ensure no content overlap between sections - each section must contain unique information.
Only include Enhancement Notes when making significant inferences about DevOps processes, infrastructure management, or team structure.
Be comprehensive but concise, prioritizing actionable information over descriptive text.
Strategically distribute web development, server administration, and DevOps-related keywords throughout all sections naturally.
Provide realistic salary ranges based on location, experience level, and DevOps specialization.

Industry Expertise:

Include specific DevOps tools, Kubernetes, CI/CD pipelines, and Infrastructure-as-Code tools relevant to the role.
Address DevOps career progression paths and technical leadership opportunities in infrastructure management and automation.
Provide tactical advice for portfolio development, live demonstrations, and project case studies with a focus on infrastructure management, monitoring, and automation.
Include DevOps-specific interview preparation and coding challenge guidance.
Emphasize infrastructure reliability, scalability, and efficiency principles.

Professional Standards:

Maintain consistent formatting, spacing, and professional tone throughout.
Use web development, server administration, and DevOps industry terminology appropriately and accurately.
Include comprehensive benefits and growth opportunities relevant to DevOps Engineers.
Provide actionable insights that give DevOps candidates a competitive advantage.
Focus on DevOps team culture, cross-functional collaboration, and user impact measurement.

Technical Focus & Portfolio Emphasis:

Emphasize DevOps best practices, infrastructure management, monitoring, and automation principles.
Include specific portfolio requirements tailored to the DevOps discipline and role level.
Address Kubernetes, CI/CD pipelines, and Infrastructure-as-Code tools in portfolio projects and case studies.
Focus on problem-solving methods, performance optimization, and scalable infrastructure design.
Include technical presentation skills and stakeholder communication for infrastructure management projects.

Avoid:

Generic business jargon not relevant to DevOps Engineer roles.
Placeholder text or incomplete sections.
Repetitive content across different sections.
Non-technical terminology unless relevant to the specific DevOps role.
Marketing language unrelated to DevOps, infrastructure management, or user experience.

Generate comprehensive, DevOps-focused content that serves as a valuable resource for DevOps Engineers evaluating career opportunities and preparing for technical interviews in the DevOps industry.

DevOps Engineer - Core AI