AI engineer in insurance

This is your opportunity to join AXIS Capital – a trusted global provider of specialty lines insurance and reinsurance. We stand apart for our outstanding client service, intelligent risk taking and superior risk adjusted returns for our shareholders. We also proudly maintain an entrepreneurial, disciplined and ethical corporate culture. As a member of AXIS, you join a team that is among the best in the industry.

• Design, build, and operate production-grade AI services, data pipelines, and platform capabilities on Azure and Databricks.
• Develop LLM-powered and agentic workflows that support business process automation, document intelligence, orchestration, and decision support.
• Expose AI capabilities through secure, maintainable APIs and Azure Function or Container App backend services, including FastAPI-based or other services where appropriate.
• Own CI/CD delivery pipelines for AI and data workloads, including build, release, deployment, validation, and environment promotion.
• Implement infrastructure-as-code using Terraform and Azure-native tooling, ensuring environments are repeatable, secure, and supportable.
• Build and manage Databricks jobs, workflows, asset bundles, and data engineering pipelines.
• Implement monitoring, logging, tracing, and alerting using OpenTelemetry or equivalent observability tools.
• Support production AI systems, including incident response, troubleshooting, operational runbooks, release readiness, and service improvement.
• Contribute to architecture decisions, engineering standards, reusable patterns, and platform strategy.
• Collaborate with engineering, data science, product, security, infrastructure, and business teams to deliver end-to-end solutions.
• Mentor engineers, lead technical enablement sessions, and promote strong engineering practices across the team.

• Strong production-level Python engineering experience, with the ability to build maintainable, tested, and supportable services.
• Experience with PySpark or equivalent large-scale data processing frameworks.
• Hands-on experience designing and operating CI/CD pipelines using Azure DevOps or similar tooling.
• Experience deploying and supporting workloads on Azure, including identity, access control, networking, and secure resource configuration.
• Practical experience with infrastructure-as-code, preferably Terraform.
• Experience building APIs, backend services, and service integrations for data or AI workloads.
• Experience with monitoring, logging, alerting, incident response, and operational support for production systems.
• Strong engineering discipline across testing, code quality, branching, release management, and automated validation.
• Ability to troubleshoot across application, data, infrastructure, deployment, and security boundaries.
• Strong communication skills, with the ability to work with technical and non-technical stakeholders.
• Будет плюсом: Experience with Databricks Jobs, Workflows, Asset Bundles, Apps, and medallion-style data architectures; Experience with Azure AI Foundry, Azure OpenAI, LLM-based application development, or agent SDKs and frameworks; Experience with MLflow, model lifecycle management, evaluation, tracing, and AI observability; Experience with containers, Docker, Kubernetes, AKS, OpenShift, or equivalent container platforms; Experience building reusable platform components, shared libraries, templates, or engineering standards; Experience working in regulated environments with strong security, governance, auditability, and operational control requirements

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