Software Engineer (Safety)

Join us as a Software Engineer to deliver bespoke, impactful AI solutions for our diverse clients.

You will bridge the gap between AI research and real-world impact by building scalable, production-grade machine learning systems. Partnering with clients and cross-functional teams, you will champion technical feasibility, ensure seamless delivery, and collaborate with Frontier Labs to reinforce our leadership in practical, high-stakes AI safety.

• Building and deploying production-grade ML software, tools, and infrastructure.

• Creating reusable, scalable solutions that accelerate the delivery of ML systems and capability testing of Frontier AI models.

• Collaborating with engineers, data scientists, and commercial leads to solve critical client challenges.

• Leading technical scoping and architectural decisions to ensure project feasibility and impact.

• Defining and implementing Faculty's standards for deploying machine learning at scale.

• Acting as a technical advisor to customers and partners, translating complex ML concepts for stakeholders.

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.

• You are comfortable building LLM applications, and are familiar with multi-agent harness tooling and AI Safety evaluation procedures.

• You possess strong Python skills and solid experience in software engineering best practices.

• You bring hands-on experience with cloud platforms and infrastructure (e.g., AWS, Azure, GCP), including architecture and security.

• You've worked with container and orchestration tools such at Docker & Kubernetes to build and manage applications at scale

• You are comfortable with core ML concepts, including probability, statistics, and common learning techniques.

• You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch.

• You're an excellent communicator, able to guide technical teams and confidently advise non-technical stakeholders.

• You thrive in a fast-paced environment, and enjoy the autonomy to own scope, solve and delivery solutions