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Faculty

Platform Engineer

LocationUK - London
Work modehybrid
Typefull-time
DepartmentNational Security & AI Safety
Company size201–500 people
First seen1w ago
Last seen2h ago
Why Faculty?
We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.
We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.
Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.
AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen.
About the team
Our National Security and AI Safety business unit is dedicated to advancing the responsible development and deployment of AI in support of national security and global stability. From strengthening mission-critical capabilities across national security and intelligence, to working with frontier labs to provide robust AI safety red teaming and evaluation, we work at the frontier of high-stakes, high-impact missions.
We understand that powerful AI systems bring both transformative opportunities and complex risks and we are proud to partner with Government and the biggest tech organisations in the world to ensure AI is not just transformative but is also secure, trustworthy and safe for all.
Because of the nature of the work we do with our Government clients, you may need to be eligible for UK Developed Vetting (DV) and willing to work on site with our clients from time to time.
About the role
As a Platform Engineer at Faculty, you will build and optimise cloud platform infrastructure and automated deployment solutions to ensure operational efficiency across complex projects.
You will take ownership of account structures, security controls, and deployment automation while designing multi-environment setups. This is an opportunity to lead the execution of infrastructure problems, driving them from initial requirements to production-ready solutions.
What you’ll be doing:
•
Designing and building cloud platform infrastructure across multi-environment setups, including ownership of security controls.
•
Creating and managing scalable Infrastructure as Code (IaC) for complex client environments.
•
Optimising container orchestration via Kubernetes to ensure high availability and resource efficiency.
•
Implementing advanced monitoring, logging, and alerting frameworks to maintain production system health.
•
Managing production environments and taking ownership of incident response and root cause analysis.
•
Collaborating with Software and ML engineers to ensure applications are architected for production readiness.
•
Mentoring and coaching Engineers through peer reviews and the sharing of engineering best practices.
Who we’re looking for:
•
You maintain high environment stability and drive infrastructure projects with minimal supervision, taking full accountability for system uptime.
•
You apply deep experience in cloud networking, security, and identity management (IAM) to harden infrastructure against threats.
•
You utilise Terraform or CloudFormation alongside hands-on code proficiency to deliver consistent, repeatable infrastructure.
•
You possess the expertise to manage Kubernetes clusters and Docker environments at scale for modern ML platforms.
•
You leverage strong Python skills to build robust platform tooling that allows agentic systems to interact reliably with infrastructure.
•
You translate complex requirements into clear solutions, effectively communicating technical trade-offs to both engineering teams and client stakeholders.
Our Interview Process
1.
Talent Team Screen (30 minutes)
2.
Pair Programming Interview (90 minutes)
3.
System Design Interview (90 minutes)
4.
Commercial Interview (60 minutes)
Our Recruitment Ethos
Legal
We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.
If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don’t hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.
A note on AI: we’re happy for you to use it for research and interview prep, but please don’t use it to generate answers during live interviews. We also use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of just let us know,) and every application is reviewed by a human, never decided by AI.
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