Principal Engineer - AI/ML

As a Principal Engineer - AI/ML, you will design and lead the development of the Cognitive Operating System: the core infrastructure enabling autonomous agents to reason, learn, and operate at scale.

We are building the next evolution of intelligent systems, moving from isolated models toward a unified, agentic ecosystem.

You’ll sit within a high-impact engineering leadership group, partnering closely with Product, Data, and Engineering leaders to shape AI-native capabilities. This role embodies the values of lead, deliver, and care by driving innovation while fostering collaboration and shared success.

This is a defining opportunity to influence a major technology shift, helping transition from traditional software to adaptive, intelligent systems that continuously improve and deliver value for customers.

About this role

• Architect and evolve the Cognitive Runtime, enabling multi-step reasoning, tool usage, and self-correcting agent workflows.
• Build and standardise a Skill Catalog so agents can discover and interact with internal APIs and legacy systems seamlessly.
• Design scalable memory and context systems, bridging short-term interactions with long-term organisational knowledge.
• Develop next-generation AI infrastructure optimised for high-throughput inference, GPU orchestration, and non-deterministic workloads.
• Lead Continuous Evaluation frameworks, including automated testing, LLM-as-a-judge systems, and real-time safety monitoring.
• Create feedback loops that capture agent interactions to continuously improve model performance and system intelligence.
• Collaborate with data teams to build low-latency pipelines that transform raw data into retrieval-ready knowledge for AI systems.
• Define semantic governance standards, including embedding strategies, versioning, and caching for reliable agent performance.
• Influence engineering teams to adopt agent-ready architectures, ensuring systems are interoperable and machine-readable.
• Provide technical leadership on AI ethics, security, and cost efficiency, helping teams deliver responsibly at scale.

What will you bring to the team?

• Deep expertise in agentic frameworks (e.g. LangGraph, CrewAI, AutoGen) or custom multi-agent orchestration systems.
• Strong experience with vector databases, graph databases, and knowledge graph-based retrieval systems.
• Proven ability to design and scale AI infrastructure, including inference systems, GPU orchestration, and fine-tuning pipelines.
• Solid background in distributed systems, event-driven architectures, and high-scale backend engineering (Python, Go, or Rust).
• Strong collaboration skills, working closely with product, data, and engineering leaders to deliver shared outcomes.
• Ability to simplify complex systems and create clear, scalable architectural patterns for broader adoption.
• Experience building platforms that continuously learn and improve through data feedback loops.
• A mindset focused on innovation, challenging the status quo and driving forward-thinking technical solutions.
• Strong sense of ownership and accountability, balancing speed with quality and long-term impact.
• Passion for shaping the future of AI, with a responsible approach to ethics, safety, and system reliability.