Staff Software Engineer - Data & AI Platforms

As a Staff Software Engineer, you will design and deliver data systems, AI-enabled platform capabilities, enterprise solutions and technical frameworks that span multiple teams, establishing architectural patterns for how enterprise knowledge is modelled, connected, and consumed. You will operate at the intersection of Data (logical and semantic), AI/LLM retrieval and grounding, and distributed systems and APIs. You will consult on architectural decisions in collaboration with enterprise architects, providing technical expertise on system design, balancing hands-on coding in critical areas with advisory responsibilities across teams, and ensuring technical solutions deliver measurable business value. You will mentor engineers at all levels, including emerging technical leaders, identify and resolve critical engineering challenges spanning multiple systems, and drive initiatives that improve developer productivity, code quality, and system reliability at organisational scale. This role may require availability outside of standard business hours, including on-call support, based on business needs.

Responsibilities:

Design and evolve canonical semantic models (taxonomies, ontologies, knowledge graphs) for enterprise domains such as product, customer, and supply chain.

Design systems that provide high-quality context for LLMs, Retrieval pipelines (RAG / GraphRAG), Semantic search (embeddings, hybrid search), and evidence-based reasoning layers.

Partner with AI/ML Science teams to ensure model correctness to reduce errors, hallucination risk, and improve trust.

Address challenges of data ambiguity, duplication, and inconsistencies at scale through systemic data validation, schema governance and versioning practices.

Design and implement enterprise software solutions and technical frameworks spanning multiple teams, establishing coding patterns and practices that scale across the organisation.

Drive complex, multi-team initiatives with minimal supervision, making key technical decisions independently while navigating ambiguity and competing priorities.

Write exemplary code in critical areas demonstrating best-in-class engineering practices when situations require deep technical expertise.

Consult with principal engineers and enterprise architects on architectural decisions, providing technical expertise on implementation feasibility, scalability considerations, and operational implications.

Recommend technology options and tools to architects based on technical evaluation, team capabilities, and implementation requirements.

Establish engineering and coding standards adopted across the organisation, including testing strategies, development workflows, and quality practices.

Lead technical design reviews across the organisation, providing expert guidance on implementation approaches, scalability, and maintainability.

Requirements:

Bachelor's degree in Computer Science, Software Engineering, or related technical field, or equivalent experience; Master's degree preferred.

12 -16 years of software development experience defining technical strategy and establishing engineering standards across the organisation, or equivalent.

Track record of writing exemplary code in critical areas requiring deep technical expertise; experience establishing coding and quality standards adopted at an organisational level.

Proven ability to decompose highly ambiguous technical challenges into effective, non-over-engineered solutions; experience anticipating technical impacts and trade-offs across multiple systems and teams at enterprise scale.

Experience designing enterprise integration solutions and establishing implementation patterns adopted across the organisation.

Experience defining organisational operational strategies and reliability practices; familiarity with championing SLO/SLI frameworks, cost optimisation, and platform reliability at scale.

Demonstrated ability to establish and articulate technical strategy across the organisation in alignment with business objectives and strategic initiatives.

Experience building knowledge bases in retail or similar domains.

Familiarity with search, recommender and RAG/GraphRAG hybrid retrieval architectures.

Experience defining enterprise semantic layers used across multiple product teams.

Exposure to AI-driven systems - optimisation, predictions and Agents.

Experience working with knowledge representation for LLM-powered applications.

Must-haves:

Acknowledge the presence of choice in every moment and take personal responsibility for your life.

Possess an entrepreneurial spirit and continuously innovate to achieve great results.

Communicate with honesty and kindness and create the space for others to do the same.

Lead with courage, knowing the possibility of greatness is bigger than the fear of failure.

Foster connection by putting people first and building trusting relationships.

Integrate fun and joy as a way of being and working, aka don't take yourself too seriously.