Lead Software Engineer (Safety)
Faculty is hiring a Lead Software Engineer (Safety) for a remote role open to applicants in United Kingdom. Level rates it ; you can apply on Faculty.
Level's read on this job
- On Level's scale, this software engineer role is Builds AI ●●●●: the job is building AI systems.
- This is listed as a remote role.
- The posting mentions PyTorch, TensorFlow and AI safety among its tools and skills.
- Faculty has 73 other open roles on Level.
- Posted in the last few days.
AI in this role
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 role
As a Lead Software Engineer at Faculty, you’ll drive the technical strategy, architecture, and deployment of cutting-edge, secure AI systems across high-stakes domains. Bridging AI research and production impact, you’ll set the benchmark for engineering excellence and operationalise scalable ML infrastructure.
Working alongside Frontier Labs, you will champion practical, safety-first AI frameworks, model capability evaluations, and multi-agent systems. You will act as a principal advisor to client leadership, mentor engineering talent, and steer cross-functional teams to solve critical, real-world AI challenges.
What you'll be doing:
Steering technical strategy, system architecture, and rigorous capability testing for complex ML systems and Frontier AI models
Architecting production-grade, secure ML software, orchestration tools, and scalable cloud infrastructure
Establishing company-wide standards and best practices for safe, reliable, and ethical machine learning deployment at scale
Collaborating with cross-functional teams and executive stakeholders to translate high-impact client needs into resilient AI solutions
Advising senior clients and partners as a trusted AI safety and technical authority, articulating complex strategies clearly
Mentoring and developing engineering talent, actively elevating team capabilities and nurturing an inclusive, high-performing culture
Partnering with Frontier Labs to advance safety evaluation procedures, multi-agent harness tooling, and robust AI governance frameworks
Who we're looking for:
You have significant leadership experience designing, deploying, and securing scalable LLM applications, multi-agent frameworks, and AI safety evaluation processes.
You bring exceptional software engineering fundamentals and advanced Python expertise, with a focus on building resilient, enterprise-ready systems.
You demonstrate deep hands-on experience with cloud platforms (AWS, Azure, GCP), scalable cloud architectures, container orchestration (Docker, Kubernetes), agent sandboxing, and end-to-end cybersecurity.
You possess mastery over the full ML lifecycle, with proven expertise operationalising production systems using PyTorch, TensorFlow, or similar frameworks.
You excel in fast-paced, high-growth environments, bringing autonomy, strategic ownership, and a track record of guiding technical decisions.
You communicate persuasively with both technical teams and senior non-technical stakeholders, translating complex technical risks into clear strategic direction.
The Interview Process
Talent Team Screen (30 minutes)
Introduction to the Hiring Manager (30 minutes)
Pair Programming Interview (90 minutes)
System Design Interview (90 minutes)
Commercial & Leadership Interview (60 minutes)
#LI-PRIO
Our Recruitment Ethos
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.
How we rate this
Lead Software Engineer (Safety) at Faculty rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- Typical software engineer job
- $168k
This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs
Questions you could be asked
- How do you think about the risk of an AI system in this kind of role failing silently?
- Tell me about a research question you investigated. What did you find?
- What are the limits of PyTorch that you've run into, and how did you work around them?
- What's a project where you used TensorFlow hands-on?
- How would you decide a model or AI system is ready to ship?
Adapt your resume
- List these exact terms on your resume: AI Safety, AI Research, PyTorch, and TensorFlow. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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