Define and own the enterprise AI engineering strategy, vision, and solution design standards across both custom‑built and integrated AI solutions
Evaluate, select, and adopt emerging AI technologies, balancing in‑house development with vendor platforms to ensure flexibility and avoid lock‑in
Design secure, scalable AI platforms and systems spanning Azure OpenAI, multi‑provider LLMs, orchestration layers, and enterprise integration patterns
Establish and govern best‑practice engineering patterns for model integration, API‑first design, vector search, and deployment of AI services
Oversee delivery and operationalisation of AI platforms and solutions, whether internally engineered or externally sourced, ensuring they meet enterprise readiness criteria
Set and enforce AI engineering governance for model lifecycle management, testing, validation, observability, and compliance
Partner across Enterprise Architecture, Security, Data, Platforms, and business teams to ensure solutions align with regulatory, security, and risk expectations
Provide senior technical leadership across cloud infrastructure, identity, networking, and security needed to support AI workloads
Mentor and develop senior engineers, fostering communities of practice and uplifting engineering capability and reusable frameworks
Champion Responsible AI and ensure all AI solutions, built or integrated, meet ethical, fair, transparent, and secure standards

Extensive experience designing and leading enterprise-scale AI and Generative AI platforms in production environments
Deep expertise in cloud-based AI services, particularly Azure OpenAI, Cognitive Services, and advanced RAG architectures
Proven ability to design API-first, microservices-based AI systems integrated into complex enterprise ecosystems
Strong background in Azure infrastructure, networking, identity, and security architecture
Significant experience with Infrastructure as Code, CI/CD, and cloud-native deployment strategies
Demonstrated leadership in AI Ops / including monitoring, governance, and operational resilience
Broad understanding of adjacent AI disciplines such as NLP, Computer Vision, and data engineering
Prior experience in financial services or insurance sectors advantageous
Familiarity with AzureML, Databricks, related Azure technologies, Docker, Kubernetes, and containerization is advantageous

Principal AI Engineer

Key skills