Jobs / Accenture

AI Infrastructure Architect

Accenture · London, ENG, United Kingdom
London, ENG, United KingdomOnsite
Remuneration
Not specified
Location
London, ENG, United Kingdom
Visa sponsorship
Not specified

Job summary

The Infrastructure Architect designs, deploys, and optimizes infrastructure for production AI and machine learning systems across cloud and on-premises environments. The role covers GPU clusters, distributed training, data pipelines, CI/CD, container orchestration with Docker and Kubernetes, model serving, and monitoring across InfraOps and MLOps. It also includes troubleshooting complex infrastructure issues, setting architecture standards, and mentoring engineers.

Qualifications

  • Practical experience building, monitoring, and troubleshooting AI/ML applications and designing infrastructure for on-premises or public-cloud deployment.
  • Strong understanding of AI, machine learning, and computing infrastructure.
  • Proficiency in Python, Java, or C++.
  • Experience with data pipeline and workflow management tools such as Apache Airflow or Kubeflow.
  • Experience in AI/ML infrastructure engineering or a related role deploying large-scale solutions on a hyperscaler platform.
  • Strong problem-solving, communication, and collaboration skills.

Responsibilities

  • Write, review, and debug code, scripts, and infrastructure as code for AI infrastructure and automation.
  • Architect and provision cloud and on-premises compute resources, including GPU clusters and distributed training environments.
  • Design and maintain deployment automation and CI/CD pipelines.
  • Deploy AI systems, models, and data pipelines into production.
  • Lead container orchestration and model serving.
  • Evaluate tools, frameworks, and platforms and recommend infrastructure choices.
  • Integrate AI systems with enterprise systems while addressing interoperability, security, and regulatory compliance.
  • Monitor AI systems and infrastructure health across InfraOps and MLOps and drive remediation.
  • Troubleshoot complex issues across hardware, networking, software, and models; lead root-cause analysis.
  • Mentor junior engineers and lead code reviews.
  • Define and document architecture standards, processes, and procedures.

Skills

AirflowC++DockerJavaKubernetesPython

Degrees

Bachelor's degree in Computer Science, Computer Engineering, or a related engine

Industry

Artificial intelligenceMachine learning

Relocation

No