Principal Product Engineer in London

Nscale is taking on the hyperscalers by building a vertically integrated GenAI cloud platform that spans from sustainable data centres to advanced AI infrastructure and enterprise applications. We’re shaping the next generation of AI-native computing — secure, efficient, and transparent. Our culture is built on relentless innovation, accountability, and excellence. As a Nscaler, you’ll join a team that values open collaboration, speed, and respect. We encourage bold thinking and trust every individual to take ownership and deliver impact — together.

Nscale is seeking a Principal AI Engineer to lead the design, implementation, and strategic direction of AI systems powering our GenAI cloud. This is a pivotal role that combines deep hands‑on expertise with visionary, system‑level leadership. You will be responsible for steering Nscale’s AI strategy, identifying new ways to harness AI for efficient, effective, and collaborative execution, and aligning technical progress with business priorities and available resources. You’ll operate at the intersection of engineering, strategy, and execution — ensuring that innovation translates into scalable, secure, and valuable outcomes.

Responsibilities

• Lead and shape the long‑term AI engineering vision, defining architecture, frameworks, and standards for how AI is built, deployed, and governed at Nscale.
• See the big picture — apply system‑level thinking to design coherent AI ecosystems that connect infrastructure, data, and product layers.
• Translate strategy into action by identifying key milestones, dependencies, and capability development paths aligned with business priorities and resourcing realities.
• Steer AI direction and create new methodologies to harness AI for automation, intelligent decision‑making, and cross‑functional collaboration.
• Architect and oversee large‑scale, distributed systems for model training, fine‑tuning, inference, and integration across multimodal and LLM‑based architectures.
• Champion security, IAM, and data governance, embedding compliance and trust into every layer of the AI stack.
• Collaborate across disciplines — partnering with Data, DevOps, and Security teams to ensure observability, scalability, and operational resilience.
• Drive operational excellence through automation, telemetry, and continuous improvement, fostering a DevOps mindset and data‑driven culture.
• Mentor and guide senior engineers and cross‑functional teams, promoting engineering rigor, design thinking, and a culture of excellence.
• Evaluate and integrate models and AI providers (OpenAI, Anthropic, open‑source frameworks, etc.) while optimising for performance, reliability, and cost.
• Influence company‑wide strategy, helping executives and technical leaders make informed trade‑offs in capability development and delivery sequencing.

Requirements

• 15+ years of experience in software, data, or AI engineering, including extensive hands‑on experience designing and deploying production‑scale AI systems.
• Proven success leading and delivering AI initiatives that bridge innovation and pragmatic business impact.
• Deep understanding of transformer architectures, LLMs, and AI agent frameworks, and practical experience orchestrating them in enterprise‑grade systems.
• Proficiency in Python, PyTorch, and modern MLOps/AIOps ecosystems (e.g., LangChain, Ray, Kubeflow, MLflow, Hugging Face).
• Strong foundation in data management, IAM, governance, and security, with experience embedding these principles into AI lifecycle workflows.
• Expertise in distributed systems, Kubernetes, and GPU orchestration at scale.
• Ability to connect engineering initiatives to business outcomes, translating complex AI concepts into actionable strategic roadmaps.
• Demonstrated systems‑level thinking — designing architectures that are scalable, interoperable, and measurable.
• Commitment to observability, metrics, and data‑driven decision‑making to guide prioritisation and continuous improvement.
• Excellent communicator and collaborator, able to influence across technical and executive teams.

Preferred Qualifications

• Experience as a principal, architect, or head of AI in a complex or fast‑scaling environment.
• Hands‑on work with multi‑agent orchestration, RAG pipelines, or enterprise‑scale AI automation frameworks.
• Contributions to open‑source AI projects or thought leadership in AI system design and governance.
• Deep familiarity with observability stacks (Prometheus, Grafana, OpenTelemetry) and ML observability frameworks.
• Track record of designing AI capability roadmaps that balance innovation, security, and sustainability.
• Expertise in AI governance, trust and risk frameworks, or policy‑aligned AI deployment.

Benefits

• Lead a world‑class AI engineering team tackling the hardest problems in modern AI infrastructure.
• Shape how enterprises securely and efficiently adopt and scale generative AI.
• Influence the direction of Nscale’s AI ecosystem — from vision to capability development to delivery.
• Collaborate with some of the brightest minds across AI infrastructure, systems, and applied research.
• Competitive compensation, equity, and a culture of autonomy, trust, and excellence.

At Nscale, we are committed to fostering an inclusive, diverse, and equitable workplace. We believe that a variety of perspectives enriches our work environment, and we encourage applications from candidates of all backgrounds, experiences, and abilities. We strongly encourage applications from people of colour, the LGBTQ+ community, people with disabilities, neurodivergent people, parents, carers, and people from lower socio‑economic backgrounds.

If there’s anything we can do to accommodate your specific situation, please let us know. The responsibilities outlined in this job description are not exhaustive and are intended to provide a general overview of the position. The employee may be required to perform additional duties, tasks, and responsibilities as assigned by management, consistent with the skills and qualifications required for the role.