AI Engineer Expert

Experteer Overview You will design, build, and continuously improve production-grade AI and GenAI solutions to advance AXA Group’s strategic priorities. You’ll work across AXA entities to turn innovative AI ideas into real business value, driving scalable, reliable, and responsible AI capabilities. In this high-visibility role, you’ll collaborate with cross-functional teams to shape evaluation, observability, cost governance, and lifecycle management for GenAI applications. This is an opportunity to influence AI transformation at scale and contribute to a mission-driven, tech-led insurer. Ready to lead the future of AI engineering with hands-on delivery and practical guardrails? Pay / Benefits * Collaborate with AXA entities and business units to understand needs and translate them into practical AI solutions for real operations * Design, develop, deploy, and operate AI and GenAI solutions delivering measurable value * Contribute to evolving shared AI engineering practices (evaluation, observability, performance, cost efficiency, safety, lifecycle governance) * Support GenAI evaluation and AI consumption optimization while remaining adaptable to new priorities * Work with data scientists, data engineers, product managers, platform teams, and stakeholders to identify opportunities and implement robust technical solutions * Promote reusable engineering patterns, standards, and guardrails for scalable, secure, and responsible AI systems * Share practices, document learnings, and foster collaboration across teams Tasks * 3+ years delivering AI/ML-enabled products, GenAI apps, or agentic systems in production * Experience with evaluation, observability, reliability, or optimization of GenAI apps (e.g., RAG, conversational assistants, workflow automation) * Solid understanding of AI operational drivers: quality, latency, cost, usage, safety, privacy, business value * Experience delivering technical work in cross-functional teams and owning work packages * Experience in insurance/financial services or regulated industries is a plus * Strong software engineering foundations (Python or similar, APIs, integration patterns, monitoring, automation) * Understanding of GenAI patterns (RAG, conversational assistants, workflow automation, agentic/tool-using systems) * Ability to define and operate GenAI evaluation approaches (quality criteria, regression testing, human feedback, performance, reliability, risk controls) * Knowledge of AI consumption and cost drivers (model selection, context management, prompt design, caching, routing, orchestration, governance) * Experience with observability and operational monitoring for AI (tracing, latency, reliability, usage, cost, continuous improvement) * Ability to establish guardrails balancing performance, cost, safety, privacy, security, sustainability, compliance Key requirements * equal opportunities and diversity & inclusion commitment * hybrid work model * global, multicultural teams * opportunity to influence AI transformation * career growth in a leading insurer * fast-paced, innovative environment

observability, performance, cost efficiency, safety, lifecycle governance) * Support GenAI evaluation and AI consumption optimization while remaining adaptable to new priorities * Work with data scientists, data engineers, product managers, platform teams, and stakeholders to identify opportunities and implement robust technical solutions * Promote reusable engineering patterns, standards, and guardrails for scalable, secure, and responsible AI systems * Share practices, document learnings, and foster collaboration across teams Tasks * 3+ years delivering AI/ML-enabled products, GenAI apps, or agentic systems in production * Experience with evaluation, observability, reliability, or optimization of GenAI apps (e.g., RAG, conversational assistants, workflow automation) * Solid understanding of AI operational drivers: quality, latency, cost, usage, safety, privacy, business value * Experience delivering technical work in cross-functional teams and owning work packages * Experience in aaaaaaaa priorities. services or regulated industries is a plus * Strong software engineering foundations (Python or similar, APIs, integration patterns, monitoring, automation) * Understanding of GenAI patterns (RAG, conversational assistants, workflow automation, agentic/tool-using systems) * Ability to define and operate GenAI evaluation approaches (quality criteria, regression testing, human feedback, performance, reliability, risk controls) * Knowledge of AI consumption and cost drivers (model selection, context management, prompt design, caching, routing, orchestration, governance) * Experience with observability and operational monitoring for AI (tracing, latency, reliability, usage, cost, continuous improvement) * Ability to establish guardrails balancing performance, cost, safety, privacy, security, sustainability, compliance Key requirements * equal opportunities and diversity & inclusion commitment * hybrid work model * global, multicultural teams * opportunity to influence AI transformation * career growth in a leading insurer * fast-paced, innovative environment