AI Infrastructure Principal Architect

Hackajob Ltd; Greater London; On-site; GBP 61,000 - 101,000; Full time

Job summary

Hackajob Ltd, in partnership with Accenture, seeks a Principal AI Infrastructure Architect to lead the design and delivery of large-scale AI compute systems. You will own core architecture across compute, networking, storage, and model serving, driving cost-optimized, scalable solutions.

The role requires deep hyperscaler experience, hands-on prototyping, and the ability to align projects with business outcomes. Leadership, mentoring, and collaboration across cross-functional teams are essential.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or a related Engineering field.
• Experience in coding, building, monitoring, and troubleshooting AI/ML model applications, incl. infrastructure for deployment on‑premise or cloud.
• Strong understanding of AI and machine learning.
• Strong understanding of computing infrastructure, with preferred knowledge of AI infrastructure.
• Proficient in Python, Java, or C++.
• Experience with data pipeline and workflow management tools such as Apache Airflow or Kubeflow.
• Strong problem-solving skills and the ability to work in a fast-paced environment.
• Excellent communication and collaboration skills.
• Longstanding experience in AI/ML infrastructure engineering or related roles on a hyperscaler platform for deploying large-scale solutions.
• Proven experience leading and managing AI projects and teams.
• Strong project management skills, with the ability to manage multiple projects simultaneously.
• Demonstrated experience evaluating and selecting AI technologies and frameworks.
• Ability to work with cross-functional teams and drive project alignment.

Responsibilities

• Set the overarching technical vision and strategy for compute infrastructure supporting large-scale AI/ML systems.
• Own the most complex architecture decisions across compute, networking, storage, orchestration, and model serving.
• Architect and hands-on prototype large-scale, cost-optimized compute and distributed training systems.
• Define reference architectures, standards, and architectural patterns, and implement foundational tooling, infrastructure-as-code, and automation.
• Lead enterprise-scale architecture assessments and design reviews, getting hands-on in the environment to validate findings and profile workloads.
• Shape and steward the AI infrastructure roadmap and technology strategy.
• Identify, evaluate, and hands-on pilot emerging technologies and innovations.
• Drive hands-on performance and cost optimization of the computational stack.
• Serve as the principal authority across hyperscaler cloud platforms.
• Lead deep troubleshooting and root-cause analysis across hardware, networking, software, and models.
• Cultivate and lead relationships with infrastructure partners and partnering organizations.
• Provide executive- and client-level technical advisory and translate complex trade-offs into clear recommendations tied to business outcomes.
• Define monitoring, observability, and reliability strategy across InfraOps and MLOps, and implement instrumentation, SLAs, SLOs, and cost/performance governance.
• Ensure enterprise integration, security, compliance, and regulatory alignment of AI/ML infrastructure.
• Mentor, elevate, and grow the architect community.
• Champion cost-efficiency and value realization for AI/ML infrastructure.

Skills

AI/ML infra

Programming (Python/Java/C++)

Cross-functional collaboration

Project management

Problem solving

Education

Bachelor's degree in CS/Engineering

Tools

Airflow

Kubeflow

Cloud platforms

Model Serving

Security

Architect

Python

Java

C++

Job description

Salary: £61,000 - 101,000 per year

Requirements:

• Bachelors degree in Computer Science, Computer Engineering, or a related Engineering field.
• Significant experience in coding, building, monitoring, and troubleshooting AI/ML model applications, including selecting, designing, and building infrastructure for deployment and runtime on-premise or on public cloud.
• Strong understanding of AI and machine learning.
• Strong understanding of computing infrastructure, with preferred knowledge of AI infrastructure.
• Well-versed and proven experience in programming languages such as Python, Java, or C++.
• Experience with data pipeline and workflow management tools such as Apache Airflow or Kubeflow.
• Strong problem-solving skills and the ability to work in a fast-paced environment.
• Excellent communication and collaboration skills.
• Longstanding experience in AI/ML infrastructure engineering or related roles on a hyperscaler platform for deploying large-scale solutions.
• Proven experience leading and managing AI projects and teams.
• Strong project management skills, with the ability to manage multiple projects simultaneously.
• Demonstrated experience evaluating and selecting AI technologies and frameworks.
• Ability to work with cross-functional teams and drive project alignment.

Responsibilities:

• Set the overarching technical vision and strategy for compute infrastructure supporting large-scale AI/ML systems.
• Own the most complex architecture decisions across compute, networking, storage, orchestration, and model serving.
• Architect and hands-on prototype large-scale, cost-optimized compute and distributed training systems.
• Define reference architectures, standards, and architectural patterns, and implement foundational tooling, infrastructure-as-code, and automation.
• Lead enterprise-scale architecture assessments and design reviews, getting hands-on in the environment to validate findings and profile workloads.
• Shape and steward the AI infrastructure roadmap and technology strategy.
• Identify, evaluate, and hands-on pilot emerging technologies and innovations.
• Drive hands-on performance and cost optimization of the computational stack.
• Serve as the principal authority across hyperscaler cloud platforms.
• Lead deep troubleshooting and root-cause analysis across hardware, networking, software, and models.
• Cultivate and lead relationships with infrastructure partners and partnering organizations.
• Provide executive- and client-level technical advisory and translate complex trade-offs into clear recommendations tied to business outcomes.
• Define monitoring, observability, and reliability strategy across InfraOps and MLOps, and implement instrumentation, SLAs, SLOs, and cost/performance governance.
• Ensure enterprise integration, security, compliance, and regulatory alignment of AI/ML infrastructure.
• Mentor, elevate, and grow the architect community.
• Champion cost-efficiency and value realization for AI/ML infrastructure.

Technologies:

• AI
• Airflow
• Architect
• Cloud
• Hardware
• Java
• Kubeflow
• Machine Learning
• MLOps
• Model Serving
• Python
• Security

More:

We are partnering directly with Accenture on this role for a Principal AI Infrastructure Architect. We are a leading global professional services company helping the worlds leading businesses, governments, and organizations build their digital core, optimize operations, accelerate revenue growth, and enhance citizen services. We have approximately 791,000 people serving clients in more than 120 countries, with strong ecosystem relationships and deep capabilities across cloud, data, and AI. Our broad services span Strategy & Consulting, Technology, Operations, Industry X, and Song, and we are committed to creating 360 value for our clients, our people, our shareholders, our partners, and our communities.

last updated 40 week of 2026