AI Infrastructure Lead Architect in London

AI Infrastructure Lead Architect in London

London Full-Time 85500 - 104500 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Design and optimise AI infrastructure for large-scale machine learning systems.
  • Company: Join Accenture, a leader in innovative technology solutions.
  • Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
  • Other info: Collaborative environment with mentorship and career advancement opportunities.
  • Why this job: Be at the forefront of AI technology and make a significant impact.
  • Qualifications: Expertise in cloud platforms like AWS, Azure, or Google Cloud required.

The predicted salary is between 85500 - 104500 £ per year.

Read the overview of this opportunity to understand what skills, including relevant soft skills and software package proficiencies, are required. hackajob is partnering directly with Accenture to hire for this role.

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 are 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.

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.

AI Infrastructure Lead Architect in London employer: Hackajob

Joining Google as a Security Platform Engineer in the UK Public Sector means becoming part of a dynamic and innovative team dedicated to delivering secure private cloud services for critical customers. With a strong emphasis on employee growth, you will have access to cutting-edge technology and collaborative opportunities that foster professional development. The inclusive work culture at Google encourages creativity and teamwork, making it an exceptional employer for those seeking meaningful and impactful work in a supportive environment.

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Contact Details:

Hackajob Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land AI Infrastructure Lead Architect in London

Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Hackajob or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Hackajob.

Tap into Online Developer Communities

Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Hackajob.

Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Hackajob that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

We think you need these skills to ace AI Infrastructure Lead Architect in London

AI/ML Infrastructure Design
Large-Scale Distributed Training
Compute Infrastructure Optimization
Cost-Efficiency Engineering
Architectural Decision-Making
GPU Cluster Design and Tuning
Security and Compliance Knowledge

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Hackajob.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Hackajob and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Hackajob

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Hackajob uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.