Role at a glance
- Salary
- Not Disclosed
- Location
- Kronberg, Campus Kronberg 1
- Employment
- Full-time
- Experience
- Practical experience in coding, building, monitoring, troubleshooting applications of AI/ML models; selecting, designing and infrastructure for deploying and running them on premise or on public cloud. Strong understanding of AI and machine learning as a subject. Strong understanding of computing infrastructure a subject, preferred knowledge of AI infrastructure. Proficiency in programming languages such as Python, Java, or C++. Experience with data pipeline and workflow management tools (e.g., Apache Airflow, Kubeflow). Strong problem-solving skills and ability to work in a fast-paced environment. Excellent communication and collaboration skills. Proven experience in AI/ML infrastructure engineering or related roles on a hyperscaler platform for deploying large scale solutions.
- Education
- Bachelor's Degree in Computer Science, Computer Engineering, related Engineering field
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Role Summary
The AI Infrastructure Architect designs, deploys, and optimizes infrastructure for AI and machine learning systems across cloud and on-premises environments. The role covers compute resources, production deployments, data pipelines, and the monitoring and reliability of AI infrastructure.
What You'll Do
- Write, review, and debug code, scripts, infrastructure-as-code, and automation; maintain deployment automation and CI/CD pipelines.
- Architect and provision cloud and on-premises compute resources, including GPU clusters and distributed training environments,...
- Deploy AI systems, models, and data pipelines into production, and lead container orchestration and model serving.
- Monitor AI system and infrastructure performance, reliability, and utilization across InfraOps and MLOps; troubleshoot complex issues...
- Evaluate tools and platforms, integrate AI systems with enterprise systems, define and document architecture standards, and mentor...
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View full postingQualifications
Required qualifications include a bachelor's degree in computer science, computer engineering, or a related engineering field; practical experience building, monitoring, and troubleshooting AI/ML model applications and deploying them on-premises or on public cloud; strong understanding of AI/ML and computing infrastructure; proficiency in Python, Java, or C++; experience with data pipeline and workflow management tools; and experience in AI/ML infrastructure engineering or related hyperscaler roles deploying large-scale solutions. Strong problem-solving, communication, and collaboration skills are also required.
Required
- Bachelor's degree in Computer Science, Computer Engineering, or a related Engineering field
- Practical experience coding, building, monitoring, and troubleshooting AI/ML model applications, and selecting, designing, and deploying...
- Strong understanding of AI and machine learning
- Strong understanding of computing infrastructure
- Proficiency in Python, Java, or C++
- Experience with data pipeline and workflow management tools such as Apache Airflow or Kubeflow
- Strong problem-solving skills and ability to work in a fast-paced environment
- Excellent communication and collaboration skills
Preferred
- Knowledge of AI infrastructure
Original job description
Content provided by the employer
Original job description
Content provided by the employer
AI Infrastructure Architect
Industry: Infrastructure & Capital Projects Engineering (Construction / Infrastructure / Capital Projects)
YOU ARE
As a hands-on AI Infrastructure Architect, you are an experienced engineer with several years in infrastructure engineering who now takes on more complex, higher-impact work designing and optimizing the AI and machine learning infrastructure that powers real-world applications. Working alongside senior architects and engineers — and increasingly leading your own workstreams — you apply proven skills in coding, testing, configuring, deploying, monitoring, and troubleshooting AI systems and the infrastructure they run on. Day to day, you architect and optimize infrastructure components, write and review code and deployment scripts, design and tune cloud and on-premises compute resources such as GPU clusters and distributed training environments, deploy AI systems and models into production, and build and optimize data pipelines that feed AI and ML workflows. You optimize the computational stack for performance, cost, power, and scalability, monitor AI systems and infrastructure health across both InfraOps and MLOps disciplines, perform AI monitoring to track model and system performance, and independently troubleshoot and resolve complex issues across the stack. You also mentor junior engineers, contribute to architectural decisions, and help establish best practices. This is a hands-on, ownership-driven role where you apply and deepen your expertise across modern tools and platforms — including container orchestration, model serving, CI/CD pipelines, InfraOps, MLOps, and AI monitoring — while making meaningful contributions to infrastructure that enables AI-driven business outcomes.
THE WORK
- Write, review, and debug code, scripts, and infrastructure-as-code for AI infrastructure, automation, and tooling, setting standards for quality across the team.
- Architect, configure, and provision compute resources across cloud and on-premises environments, including GPU clusters and distributed training setups, optimizing for performance and utilization.
- Design and maintain deployment automation and CI/CD pipelines to support reliable, repeatable releases of AI systems, models, and applications.
- Deploy AI systems, models, and data pipelines into production, defining and improving the processes and best practices others follow.
- Lead container orchestration and model serving using tools such as Docker, Kubernetes, and model deployment frameworks.
- Architect and optimize the computational stack for performance, power, cost, and scalability, balancing trade-offs against business goals.
- Evaluate and select tools, frameworks, and platforms, making recommendations that shape the infrastructure roadmap.
- Integrate AI models and systems into existing enterprise systems, ensuring interoperability, security, and regulatory compliance.
- Own AI monitoring and infrastructure health across InfraOps and MLOps, tracking performance, reliability, and utilization, and driving remediation.
- Independently troubleshoot and resolve complex issues across the computational stack — hardware, networking, software, and models — and lead root-cause analysis.
- Mentor junior engineers and lead code reviews, providing technical direction and supporting their growth.
- Define and document architecture standards, processes, and procedures, and apply security, cost-efficiency, and scalability best practices across the infrastructure.
EDUCATION
• Bachelor's Degree in Computer Science, Computer Engineering, related Engineering field
BASIC (REQUIRED) QUALIFICATION
Practical experience in coding, building, monitoring, troubleshooting applications of AI/ML models; selecting, designing and infrastructure for deploying and running them on premise or on public cloud.
Strong understanding of AI and machine learning as a subject.
Strong understanding of computing infrastructure a subject, preferred knowledge of AI infrastructure.
Proficiency in programming languages such as Python, Java, or C++.
Experience with data pipeline and workflow management tools (e.g., Apache Airflow, Kubeflow).
Strong problem-solving skills and ability to work in a fast-paced environment.
Excellent communication and collaboration skills.
Proven experience in AI/ML infrastructure engineering or related roles on a hyperscaler platform for deploying large scale solutions.
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us at www.accenture.com
Erklärung zur Chancengleichheit am Arbeitsplatz
Wir sind der Meinung, dass niemand aufgrund seiner Andersartigkeit diskriminiert werden sollte. Alle Einstellungsentscheidungen werden unabhängig von Alter, Rasse, Glaubensbekenntnis, Hautfarbe, Religion, Geschlecht, nationaler Herkunft, Abstammung, Behinderung, Veteranenstatus, sexueller Orientierung, Geschlechtsidentität oder -ausdruck, genetischen Informationen, Familienstand, Staatsbürgerschaft oder anderen gesetzlich geschützten Kriterien getroffen. Unsere große Vielfalt macht uns innovativer, wettbewerbsfähiger und kreativer und hilft uns, unsere Kunden und unsere Gemeinschaften besser zu betreuen.
About the company
Accenture
Large Enterprise
Accenture is a global professional services company that specializes in providing consulting, technology, and outsourcing services. With a diverse range of industries served, including financial services, healthcare, and telecommunications, Accenture leverages advanced technologies and data analytics to help organizations improve their performance and drive innovation. Committed to sustainable progress, the company emphasizes its dedication to inclusivity, digital transformation, and building a more sustainable future for its clients and communities. With a presence in over 120 countries, Accenture is known for its expertise in integrating cutting-edge solutions that address complex business challenges.