AI Engineer Expert
Indexed description
About The Job
Job purpose
As an AI Engineer Expert, your main objective is to design, build, deploy, and continuously improve production-grade AI and GenAI solutions that support AXA Group’s strategic priorities. Working at the forefront of GenAI and Agentic AI technologies, you will help transform innovation into concrete business value across AXA entities.
This is a high-exposure opportunity to contribute to AXA’s AI transformation through visible, business-critical initiatives. You will work closely with AXA Group and entity stakeholders, bringing strong hands-on engineering expertise across topics such as GenAI evaluation, AI usage, and cost governance, while contributing to scalable, reliable, secure, and measurable AI capabilities.
Main missions
Your Responsibilities Include
- Work closely with AXA entities and business units to understand needs, clarify requirements, and contribute to AI solutions that are adopted and useful in real operational contexts.
- Design, develop, deploy, and operate AI and GenAI solutions that deliver measurable value for AXA entities.
- Contribute to the evolution of shared AI engineering practices, including evaluation, observability, performance, cost efficiency, safety, and lifecycle governance.
- Support key topics such as GenAI application evaluation and AI consumption optimisation, while maintaining flexibility to take ownership of new AI engineering priorities over time.
- Collaborate with cross-functional teams including data scientists, data engineers, product managers, platform teams, and business stakeholders to identify opportunities and translate them into robust technical solutions.
- Apply and contribute to reusable engineering patterns, standards, and guardrails for scalable, reliable, secure, and responsible AI systems across the organisation.
- Contribute to the broader AI engineering community by sharing practices, documenting learnings, and supporting collective improvement across teams.
Experience
- 3+ years delivering AI/ML-enabled products, GenAI applications, or agentic systems in production environments, with experience across the full lifecycle from design and implementation to monitoring and continuous improvement.
- Experience contributing to evaluation, observability, reliability, or optimisation practices for GenAI applications such as RAG, conversational assistants, workflow automation, or agentic systems.
- Good understanding of AI operational drivers, including quality, latency, cost, usage, safety, privacy, and business value, with the ability to balance them pragmatically.
- Experience contributing to technical delivery in cross-functional teams, with the ability to take ownership of work packages and collaborate effectively with peers.
- Experience working in the insurance, financial services, or another regulated industry is a plus.
- Strong software engineering foundations for production-grade AI systems, including Python or similar languages, APIs, integration patterns, monitoring, and automation.
- Solid understanding of GenAI application patterns, including RAG, conversational assistants, workflow automation, and agentic or tool-using systems.
- Ability to define and operate evaluation approaches for GenAI systems, covering quality criteria, regression testing, human feedback, performance measurement, reliability, and risk controls.
- Understanding AI consumption and cost drivers, such as model selection, context management, prompt design, caching, routing, orchestration, infrastructure choices, and usage governance.
- Experience with observability and operational monitoring for AI applications, including tracing, latency, reliability, usage, cost efficiency, and continuous improvement indicators.
- Ability to establish practical guardrails for responsible AI engineering, balancing performance, cost, safety, security, privacy, sustainability, and compliance requirements.
- Collaboration: ability to work effectively with engineers, data scientists, product teams, and business stakeholders in multicultural, cross-functional environments.
- Delivery mindset: organize and prioritize work, contribute to planning, manage dependencies, and help deliver GenAI initiatives with pragmatism and quality.
- Stakeholder interaction: translate business needs into concrete technical requirements, provide clear updates, and support alignment with product, compliance, security, legal, and operations teams.
- Communication: explain technical choices, results, and trade-offs clearly to technical and non-technical audiences, including through concise summaries and metrics.
- Agile mindset with a commitment to continuous improvement, iterative delivery, backlog prioritization, and value-driven outcomes.
- Collaboration and adaptability: strong teamwork across cross-functional and multicultural environments; excellent English communication and interpersonal skills.
- Passion for solving challenging problems with cutting-edge GenAI technologies, coupled with curiosity and a proven ability to learn and apply new techniques and research advances.
About The Entity
AXA is becoming a sustainable tech-led company and at AXA Group Operations we are one of the major catalysts for this transformation.
We set the tone by triggering and empowering the evolution of our insurance business model through technology and innovation, driving its concrete implementation globally at speed, with a high quality of advisory and execution.
We are present across 17 countries with committed, highly qualified teams. We leverage technology, data, sourcing, security and investment allocation in a global way, but also achieve economies of scale and synergies when necessary.
At AXA Group Operations, we want to be recognized in three fields of action:
- State-of-the-art Data Technology to drive customer experience
- State-of-the-art Procurement & Sourcing to drive efficiency and better manage risks
- High-Performing Global Team for stronger partnerships with AXA entities
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