Lead Infrastructure Architect (all genders)

Accenture; Wien; Hybride; EUR 85 000 - 104 000; Plein temps

Avantages offerts par ce poste

Voluntary Equity Investment Program (V

Résumé du poste

Accenture PLC is seeking a Lead and Principal Infrastructure Architect to own end-to-end compute infrastructure for large-scale AI/ML, translating SLAs into scalable, cost-efficient architectures.

You will design GPU clusters, orchestrate training environments, lead architecture reviews, and mentor engineers while ensuring security and regulatory compliance across hyperscaler platforms such as AWS, Azure, or GCP.

Qualifications

• Experience coding, building and monitoring AI/ML applications and deploying to cloud or on-prem.
• Strong understanding of AI/ML concepts.
• Strong understanding of computing infrastructure and AI infrastructure.
• Proficiency in Python, Java, or C++.
• Experience with data pipelines/workflow tools (Airflow, Kubeflow).
• Excellent problem-solving and fast-paced environment.
• Excellent communication and collaboration.
• Proven leadership in AI projects and teams on a hyperscaler.
• Strong project management, multi-project capability.
• Experience evaluating AI technologies/frameworks.
• Ability to work with cross-functional teams.

Responsabilités

• Own end-to-end architecture and design of optimized compute infrastructure for large-scale AI/ML systems.
• Develop and evaluate architecture options across compute, networking, storage, orchestration, and model serving.
• Lead architecture assessments, identify gaps, risks, bottlenecks, and remediation.
• Drive architectural decisions with documented rationale and SLAs alignment.
• Define and maintain AI infrastructure roadmap and capacity planning.
• Architect and optimize the full computational stack for performance, power, cost, and scalability.
• Design and tune large-scale GPU clusters and distributed training systems.
• Serve as authoritative AI infrastructure expert in at least one hyperscaler cloud.
• Design deployment, automation, and CI/CD strategies for production releases.
• Establish AI monitoring and observability strategy with SLAs/SLOs and cost tracking.
• Integrate AI/ML into enterprise environments with security/compliance.
• Lead capacity planning and cost modeling.
• Collaborate with clients and engineers to align decisions with business outcomes.
• Set technical direction, standards, and mentor engineers; lead reviews.

Connaissances

Python/Java/C++

AI/ML infrastructure

HPC / GPU clusters

Leadership & mentoring

Cloud platforms (AWS/Azure/GCP)

Formation

Bachelor's Degree in CS/Engineering

Outils

Airflow/Kubeflow

GPU clusters (NVIDIA)

CI/CD tools

Description du poste

#LI-EU

Shape the infrastructure behind large-scale AI. Architect high-performance compute environments that balance scale, reliability, performance, and cost.

Your Mission

As a Lead and Principal Infrastructure Architect, you own end-to-end responsibility for designing optimized compute infrastructure for large-scale AI and machine learning systems, including large-scale distributed training environments. You’re the authority who translates business goals, SLAs, and client standards into infrastructure architectures that perform at scale while being deliberately engineered for cost-efficiency. Drawing on deep experience, you weigh multiple viable solutions for any given problem — across compute, networking, storage, orchestration, and model serving — and make rational, well-justified architectural decisions tailored to each client's situation, constraints, and standards. You architect and optimize the full computational stack for performance, power, cost, and scalability; design and tune large-scale GPU clusters and distributed training systems; and ensure infrastructure meets security, compliance, and regulatory requirements. As the recognized AI infrastructure expert in at least one hyperscaler cloud (such as AWS, Azure, or Google Cloud), you bring authoritative knowledge of that platform's AI/ML services, accelerators, networking, and cost levers, and apply it to deliver best-in-class solutions. Beyond design, you set technical direction and standards, lead and mentor engineers and architects, partner with clients and stakeholders to shape the infrastructure roadmap, and are ultimately accountable for delivering AI/ML infrastructure that meets business SLAs, controls cost, and scales to enterprise and frontier workloads.

At Accenture, you shape the environment in which you thrive – with ways of working that suit you. You stay flexible and become part of a team full of unique individuals who make a difference together.

Your Daily Work

• Own the end-to-end architecture and design of optimized compute infrastructure for large-scale AI/ML systems, including large-scale distributed training environments, from concept through delivery.
• Develop and evaluate architecture alternatives, weighing trade-offs across compute, networking, storage, orchestration, and model serving to make rational, well-justified decisions tailored to each client's situation and standards.
• Lead architecture assessments and reviews of existing and proposed environments, identifying gaps, risks, bottlenecks, and optimization opportunities, and recommending remediation.
• Drive architectural decision‑making, documenting rationale, trade‑offs, and assumptions so decisions are transparent, defensible, and aligned with business SLAs and standards.
• Define and maintain the AI infrastructure roadmap, planning capacity, scaling, and technology evolution in step with business and product goals.
• Architect and optimize the full computational stack for performance, power, cost, and scalability, ensuring infrastructure meets business SLAs while being deliberately engineered for cost‑efficiency.
• Design and tune large‑scale GPU clusters and distributed training systems, including accelerator selection, interconnect/networking, and storage for high‑throughput training workloads.
• Serve as the authoritative AI infrastructure expert in at least one hyperscaler cloud (AWS, Azure, or GCP), applying deep knowledge of its AI/ML services, accelerators, networking, and cost levers.
• Design deployment, automation, and CI/CD strategies for reliable, repeatable, and scalable releases of AI systems, models, and data pipelines into production.
• Establish AI monitoring and observability strategy across InfraOps and MLOps, defining SLAs, SLOs, alerting, and performance/cost tracking, and driving continuous optimization.
• Integrate AI/ML systems into enterprise environments, ensuring interoperability, security, compliance, and adherence to regulatory and client standards.
• Lead capacity planning and cost modeling, forecasting compute needs and engineering cost‑efficiency into the architecture without compromising performance.
• Collaborate with clients, stakeholders, and engineering teams to align infrastructure decisions with business outcomes, translating requirements into actionable architecture and standards.
• Set technical direction, standards, and best practices, mentoring engineers and architects and leading design and code reviews across the team.

Who You Are

EDUCATION

• Bachelor's Degree in Computer Science, Computer Engineering, related Engineering field

BASIC (REQUIRED) QUALIFICATION

• Professional 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.
• Strong 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.
• Considerable experience in AI/ML infrastructure engineering or related roles on a hyperscaler platform for deploying large scale solutions.
• Proven experience in leading and managing AI projects and teams.
• Strong project management skills, with the ability to manage multiple projects simultaneously.
• Demonstrated experience in evaluating and selecting AI technologies and frameworks.
• Ability to work with cross‑functional teams and drive project alignment.

What We Offer

• Voluntary Equity Investment Program (VEIP) for leaders
• Flexible working models including home office
• Mentoring and coaching programmes

The Accenture Culture: Here, YOU are the catalyst for change

Your unique combination of skills, personality, and aspirations sets you apart. When distinct talents, strengths, and perspectives merge, the result is nothing short of extraordinary: ideas that propel the world forward. This is why we champion diversity and personal development at Accenture. Create a working environment where you truly thrive; with responsibilities that resonate deeply; with a workload that is perfectly aligned with your capabilities; and methods that are tailored to your objectives. How you wish to connect, further your development, and personally evolve rests in your hands. This is your career. We are mere facilitators, helping you shape it exactly as you envision.

Contact Us

Any questions? Feel free to contact our recruiting team at [e-mail].

In addition to exciting projects, we offer an attractive compensation package, flexible working hours, a modern environment, and many additional benefits. You also have the opportunity to positively influence your annual income based on your individual performance. The annual gross salary for this position starts, depending on qualifications and experience, at €94,400