Burberry Senior Developer, AI & Emerging Tech
- 5+ years' experience in AI/ML engineering, platform engineering or software engineering roles. • Hands-on experience designing, building and operating agentic AI systems, LLM-based platforms or multi agent orchestration frameworks on Azure, AWS or GCP (or similar).
- Core technical skills should include Python and modern software engineering practices; experience with LLM and agent development frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen or CrewAI; practical knowledge of RAG patterns, vector databases and embeddings; API design and integration using REST, event-driven and workflow-based patterns; CI/CD, automated testing and infrastructure-as-code; containerisation and deployment using Docker and Kubernetes; and hands-on experience with cloud AI services, preferably Microsoft Azure AI Foundry, Azure OpenAI, Microsoft Copilot Studio or equivalent services on AWS or GCP.
- Operational experience should include building production-grade services with monitoring, alerting, logging, incident management, release management, rollback procedures and service ownership disciplines, with the ability to define and operate SLOs for platform capabilities used by multiple teams.
- Strong understanding of enterprise integration patterns and how agents interact with systems, APIs and data sources.
- Practical familiarity with AI governance, risk and security controls, including model and prompt versioning, auditability, human-in-the-loop review, responsible AI guardrails, agent identity and access control, secrets management, data classification, data loss prevention, policy enforcement, bias monitoring and evaluation evidence suitable for internal assurance review.
- Thrives in ambiguous, greenfield environments where engineering practices and standards must be established from scratch; balances pace of delivery with sustainable, well-documented foundations.
- Proven ability to influence and collaborate with senior technical stakeholders (architecture, security, data, delivery) across a matrixed enterprise organisation.
- Familiarity with AI evaluation methodologies: automated testing of agent outputs, hallucination detection, regression testing for prompt changes, and human-in-the-loop feedback loops.
- Detail-oriented with a commitment to documentation, knowledge sharing and engineering consistency.
- Experience in Retail, Luxury or Consumer goods industries is beneficial.
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