Lead AI Infra Architect for Scalable ML Systems

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

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.